Remittances Review最新文献_第2页

Sustainability and Green Technology Innovation 可持续发展和绿色科技创新

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2408

V. D

{"title":"Sustainability and Green Technology Innovation","authors":"V. D","doi":"10.47059/rr.v7i2.2408","DOIUrl":"https://doi.org/10.47059/rr.v7i2.2408","url":null,"abstract":"This study investigates the relationships between investments in green technology and involvement in sustainability. Small firms' interest in investing in green technology is influenced by how involved they are with sustainability. Investments in green technologies, however, do not seem to be primarily motivated by participation in environmental sustainability. The study's findings demonstrate that businesses using green technologies do not prioritise environmental sustainability over other goals like creating economic and social value. Supposedly, the triple bottom line, which operates in this space, aims to assess corporate performance in terms of its effects on the environment and interested parties in addition to concerns about profitability. The study of sustainability in management information systems has thus far been constrained by the field of green IT, which largely focuses on reducing the energy consumption of corporate IT systems. It shows how to integrate human, supply chain, and IT resources to help businesses develop sustainability capabilities that enable them to deliver sustainable values to relevant stakeholders and maintain competitive advantage. In particular, the development of sustainability capabilities is addressed in relation to the role of automate, inform, transform, and infrastructure IT resources. The project calls for IT to play a daring new role in sustainability that goes beyond lowering energy usage. The ramifications for future IT and sustainability research and management practise are also discussed.","PeriodicalId":281881,"journal":{"name":"Remittances Review","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125587947","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

On Solving Multi-Attribute Decision Making Problem Using AHP 用层次分析法求解多属性决策问题

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2409

Jayapriya J, S. K, K. S

引用次数: 0

The Impact of Current in Resistance and Inductance of Rl Circuit in the Applications of Stochastic Differential Equations Using Caputo-Fabrizio Derivative 用Caputo-Fabrizio导数求解随机微分方程中电流对Rl电路电阻和电感的影响

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2410

Piriadarshani D, M. M, K. G, Geetha Lakshmi N

引用次数: 0

Performance Analysis of Spatio-temporal Human Detected Keyframe Extraction 时空人体检测关键帧提取的性能分析

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i1.2404

C. Priscilla, D. Rajeshwari

引用次数: 0

An Experimental Study and Analysis of Long-Term Multi-Trending Trajectory Forecasting of Stock Indices Using Time Series Inferential Statistical Projection 基于时间序列推理统计投影的股票指数长期多趋势轨迹预测实验研究与分析

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2418

G. Kavitha, S. Bhuvaneswari, D. Piriadarshani

{"title":"An Experimental Study and Analysis of Long-Term Multi-Trending Trajectory Forecasting of Stock Indices Using Time Series Inferential Statistical Projection","authors":"G. Kavitha, S. Bhuvaneswari, D. Piriadarshani","doi":"10.47059/rr.v7i2.2418","DOIUrl":"https://doi.org/10.47059/rr.v7i2.2418","url":null,"abstract":"The focus of this study is on time series inferential statistical projection and analysis for long-term multi-trending trajectory forecast modelling. Inferential statistics was used for projection and analysis of long-term multi-trending trajectory forecasting. The proposed model is trained, tested and validated on three different types of stocks viz. NVIDIA, UNG and IBM taken from the NASDAQ stock market index. In Phase I, the long-term deterministic multi-trending model is assessed and fitted. Model skewed residual series is assessed using the goodness of fit in Phase II. The future stock close prices and long-term multi-trending trajectory paths are simulated and analyzed in Phase III. Finally, in Phase IV, epsilon-skew-normal results and normal distribution assumptions are compared. The experimental result shows that an uptrend trajectory of historical close price simulates an uptrend trajectory in the forecasted close price, a downtrend trajectory of historical close price simulates a downtrend trajectory in the forecasted close price, a sideways or mixed trend trajectory of historical close price simulates a sideways or mixed trend trajectory in the forecasted close price.","PeriodicalId":281881,"journal":{"name":"Remittances Review","volume":"82 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129376828","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

The Path of Remittances to Consumption or Saving! Albania Case Study 汇款是消费还是储蓄的途径!阿尔巴尼亚案例研究

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v8i1.rr80002

Nevila Mehmetaj

{"title":"The Path of Remittances to Consumption or Saving! Albania Case Study","authors":"Nevila Mehmetaj","doi":"10.47059/rr.v8i1.rr80002","DOIUrl":"https://doi.org/10.47059/rr.v8i1.rr80002","url":null,"abstract":"Since the change of the political systems in the 1990-s in Albania, massive emigration has been a continuous phenomenon of different scales in Albania. The outflow migration phenomenon is associated with the inflow of remittances to the origin families. Remittances have been a vital financial source of living for a considerable number of households. Therefore, they constitute an important financial mechanism for funding the country's economy. Empirical regression analysis in emerging economies suggests ambiguous results of remittances in the economy. Therefore, it is the purpose of this paper to investigate the effect of remittances on macroeconomic variables such as aggregate consumption, national saving, and the economic growth rate in Albania. Econometric models based on the ordinary least squared method (OLS) are performed to analyze the effect among the variables, and time series data are retrieved from the World Bank and Institute of Statistics of Albania databases. Model results based on data from the period 1992-2019 show that most of the remittance income is consumed by the recipient families contributing to the aggregate consumption demand. According to the model’s results, a 1 percent increase in remittances contributes to a 3.2 percent increase in aggregate consumption in the country. While remittances have neither a significant effect on a country's national aggregate saving nor the country's economic growth rates.","PeriodicalId":281881,"journal":{"name":"Remittances Review","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128180374","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

The Impact of Current in Resistance and Inductance of Rl Circuit in the Applications of Stochastic Differential Equations Using Caputo-Fabrizio Derivative 用Caputo-Fabrizio导数求解随机微分方程中电流对Rl电路电阻和电感的影响

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2417

D. Piriadarshani, M. Maheswari, G. Kavitha, N. G. Lakshmi

引用次数: 0

A Systematic Review on Tanpin Kandri Based Crime Prediction 基于Tanpin Kandri的犯罪预测系统综述

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2407

V. K, Amal Prakash

{"title":"A Systematic Review on Tanpin Kandri Based Crime Prediction","authors":"V. K, Amal Prakash","doi":"10.47059/rr.v7i2.2407","DOIUrl":"https://doi.org/10.47059/rr.v7i2.2407","url":null,"abstract":"Predictive policing refers to the potential preventive measure to fight crimes in the modern age. Crimes are social issues that have a negative effect on society. The number of cases filed under the Indian Penal Code (IPC) in 2020 increased by over 430 percent compared to the same year-ago period. Data analytics is the process of inspecting, transforming, and modelling unstructured data into useful information. Predictive policing and crime analytics with Artificial intelligence increase attention among a multifarious scientific community. Crime pattern analysis is the computational approach to examining aspects of volume crime for the purposes of prevention where it either targets one crime or a series of discrete crimes for detection. Currently, there are not many sufficing analysis methods for the Law and order agencies. By using the Tanpin Kanri model, a Japanese business strategy, this idea makes decision points on what crime and at what rate. Crime analysis functions are generally focused on seven key areas: crime pattern detection, target profiles, forecast crime rates, resource allocation, and criminal investigations, according to a study by the International Association of Chiefs of Police. Generally, it is implemented for the most recurring crimes. This idea helps in the prevention of crimes using crime forecasting and gives a unique perspective on the areas one may not be aware of. Thus crime prediction is a valuable strategy to identify and profile those areas which are at risk, and those can be prevented.","PeriodicalId":281881,"journal":{"name":"Remittances Review","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114623103","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 Hybrid Model for Brain Tumor Detection Using EfficientNet and Fuzzy C Means Clustering Algorithm 基于高效网络和模糊C均值聚类算法的脑肿瘤检测混合模型

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i1.2403

Dr. G. Lavanya, K.L. Vinoci, D. Samvardani, V. Subiksa

{"title":"A Hybrid Model for Brain Tumor Detection Using EfficientNet and Fuzzy C Means Clustering Algorithm","authors":"Dr. G. Lavanya, K.L. Vinoci, D. Samvardani, V. Subiksa","doi":"10.47059/rr.v7i1.2403","DOIUrl":"https://doi.org/10.47059/rr.v7i1.2403","url":null,"abstract":"This paper describes the detection of brain tumors from Magnetic Resonance Images (MRI) using the deep learning EfficientNet model and the Fuzzy C means algorithm. The earlier detection of brain tumors can reduce the risk of death. Deep Learning is a highly adoptable technique for the detection of brain tumors at an early stage. It potentially lowers the fatality rate rather than machine learning as it allows the processing of large amounts of data to be more accurate in medical diagnosis. The existing EfficientNet model did not include a segmentation algorithm which is required for model training because it provides a clear image of the training model that is deployed in the EfficientNet model. It was reviewed that the Fuzzy C Means clustering algorithm is the best used for segmentation along with the enhancement of the existing EfficientNet model. This proposed system uses a transfer learning approach for training the model which was evaluated that led to an accuracy of 99.68%. The integrated Fuzzy C Means and EfficientNet model have been tested with various MRI images, and it outperforms the existing EfficientNet models in terms of accuracy.","PeriodicalId":281881,"journal":{"name":"Remittances Review","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124808066","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

Applications of Multi Attribute Decision Making Problem 多属性决策问题的应用

Remittances Review Pub Date : 2022-11-19 DOI: 10.47059/rr.v7i2.2416

P. Shoba, K. Selvakumari, S. Kavitha

引用次数: 0