International journal of advanced trends in computer science and engineering最新文献_第2页

Sentiment Analysis - An optimized Weighted Horizontal Ensemble approach 情感分析 - 一种优化的加权水平集合方法

International journal of advanced trends in computer science and engineering Pub Date : 2024-04-10 DOI: 10.30534/ijatcse/2024/061322024

{"title":"Sentiment Analysis - An optimized Weighted Horizontal Ensemble approach","authors":"","doi":"10.30534/ijatcse/2024/061322024","DOIUrl":"https://doi.org/10.30534/ijatcse/2024/061322024","url":null,"abstract":"Sentiment Analysis has gained authority as one of the primary means of analyzing feedbacks and opinion by individuals, organizations and governments. The result of sentiment analysis informs an organization on areas to improve and how best to manage customers. While sentiment analysis may be misleading as no algorithm has been considered 100% efficient, the choice of algorithms can optimize the result based on the dataset in question. This paper aims at studying various algorithms and implementing a weighted horizontal ensemble algorithm as a panacea to low confidence level in the results of sentiment analysis. We designed a system that implements the original Naive Bayes algorithm, Multinomial Naïve Bayes algorithm, Bernoulli Native Bayes algorithm, Logistic Regression algorithm, Linear Support Vector Classifier algorithm and the Stochastic Gradient Descent algorithm. Our dataset was sourced from the Stanford University. It contains fifty thousand (50,000) movie reviews. Dataset from the Nigerian movie review was used to test the models. The reviews were encoded as a sequence of word indices. An accuracy of over 91% was achieved. The Ensemble technique delivered an F1-measure of 90%. Ensemble technique provides a more reliable confidence level on sentiment analysis. The researchers also discovered that change in writing style can affect the performance of sentiment analysis","PeriodicalId":483282,"journal":{"name":"International journal of advanced trends in computer science and engineering","volume":"510 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140719397","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 Mobile Application Based Optimized Out-Patient Emergency Request Model 基于移动应用的优化门诊急诊申请模式

International journal of advanced trends in computer science and engineering Pub Date : 2024-04-10 DOI: 10.30534/ijatcse/2024/021322024

{"title":"A Mobile Application Based Optimized Out-Patient Emergency Request Model","authors":"","doi":"10.30534/ijatcse/2024/021322024","DOIUrl":"https://doi.org/10.30534/ijatcse/2024/021322024","url":null,"abstract":"This paper developed a mobile APP called Health Emergency Request APP (HER-APP). The App sends out-patients‘ emergency request to any closest health personnel within a particular location and matches a patient to a particular health personnel for immediate attention. We observed that the process of responding to out-of-hospital emergencies after a crisis have faced a lot of communication challenges between patients and the nearest healthcare personnel especially in Nigeria. There is also a problem of assigning a patient to the most qualified health personal for better care. This has resulted in increased mortality even when such emergency could better be handled. It becomes compelling to develop a mobile APP that allows a seamless communication between patient under emergency and the nearest medical expert with medical facility to save lives prior to the full engagement of the attention of a medical doctor or ambulance. This emergency request service-oriented mobile application helps patients contact any closest health personnel within a particular location using a location tracking service. The mobile application implements a matching algorithm between patients and responders, and assists people in emergency to get quick pre-clinical treatment. It uses an optimized service-oriented architecture which reduces the communication process between a patient in an emergency and the doctor or responder using a Google global positioning system as a location tracking service to helps track a patient requesting for assistance as well as all available responders. The APP uses location factor to determine a model to enhance the system on a large scale basis to provide a dispatch method to allocate patients to responders. This paper enhanced the Hungarian model and determines the best patient-responder match. The mobile APP is available at www.github.com/magnifikuc.","PeriodicalId":483282,"journal":{"name":"International journal of advanced trends in computer science and engineering","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717676","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

Is destination management data-driven and technology based? The perspective of the authorities responsible for destination management in a geographically diverse destination area 目的地管理是否以数据和技术为导向？一个地理位置多样的目的地地区负责目的地管理的当局的观点

International journal of advanced trends in computer science and engineering Pub Date : 2024-04-10 DOI: 10.30534/ijatcse/2024/041322024

{"title":"Is destination management data-driven and technology based? The perspective of the authorities responsible for destination management in a geographically diverse destination area","authors":"","doi":"10.30534/ijatcse/2024/041322024","DOIUrl":"https://doi.org/10.30534/ijatcse/2024/041322024","url":null,"abstract":"n order to determine whether the entities responsible for destination management at the local level are keeping up with market trends, especially the requirements on implementing “smartness”, and whether there is a recognition of the need for their decision-making to be guided by real-time information and data, this research surveyed most of the local tourism authorities in the recognized tourism region of the Adriatic, which regularly records high numbers of tourist arrivals and overnight stays in the Republic of Croatia, a country where tourism is an extremely important component of GDP. To explore the topic, a survey was conducted by using the methods of Computer-Assisted Web Interviewing (CAWI) and Computer-Assisted Personal Interviews (CAPI), depending on the preferences of the respondents, primarily heads of destination management entities. The study of a specific topic related to tourism development decision-making, the application of smart technologies in the destination, and the collection of input from visitors to the destination included 73.53% of tourism management bodies (tourist boards of cities/municipalities) in the observed region and resulted in interesting findings. It is indicative that the application of technologies varies by sub-region and that decision-making is based on similar sources, regardless of the strategic importance of a particular decision and its long-term impact. Also, the fact that a large proportion of destination planning and development managers interviewed had no knowledge about the existence of strategic documents on sustainable development, and that only a very small proportion implement a strategy for the application of smart technologies and recognize the benefits of such an approach, is somewhat alarming. The limitations in this research are mostly caused by the determinants imposed by the funding source","PeriodicalId":483282,"journal":{"name":"International journal of advanced trends in computer science and engineering","volume":"9 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140720204","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 Study of Transformer-based Models for Text Summarization of News Articles 基于变换器模型的新闻文章文本摘要比较研究

International journal of advanced trends in computer science and engineering Pub Date : 2024-04-10 DOI: 10.30534/ijatcse/2024/011322024

引用次数: 0

Evaluation of the effects of K-Means Clustered-Based Weight Quantization on a Keras Library Based Convolutional Neural Network for Hand Written Digit Image Recognition 评估基于 K-Means 聚类的权重量化对基于 Keras 库的卷积神经网络进行手写数字图像识别的影响

International journal of advanced trends in computer science and engineering Pub Date : 2024-04-10 DOI: 10.30534/ijatcse/2024/051322024

{"title":"Evaluation of the effects of K-Means Clustered-Based Weight Quantization on a Keras Library Based Convolutional Neural Network for Hand Written Digit Image Recognition","authors":"","doi":"10.30534/ijatcse/2024/051322024","DOIUrl":"https://doi.org/10.30534/ijatcse/2024/051322024","url":null,"abstract":"A lot of Convolutional Neural Networks (CNNs) have been implemented using FPGAs for the past years. Subsequently, memory saving features were added to the CNN through weight quantization using K-means clustering. A future goal on an ASIC design, involving CNN and weight quantization working together in one chip, can give way to an automated procedure of memory-saving CNN design. In this paper an evaluation was done on the effect of quantizing the weights of a Keras library-based CNN using K means clustering. Various values of K in K-means clustering were tested to see its effects on the CNN accuracy performance. This paper presents first the design approach of a Keras library based Convolutional Neural Network (CNN) for hand-written digit images. It then presents a hardware model design of K-Means clustering algorithm using VHDL. The performance of CNN for image recognition was then tested for various levels of weight quantization using K-means clustering algorithm. Simulation results showed a compression of weights as high as 60% resulted to less than 1% reduction in CNN’s accuracy. The findings in this paper will serve as guide in determining the relevant values of K i.e. the compression ratio, for future ASIC design on this topic.","PeriodicalId":483282,"journal":{"name":"International journal of advanced trends in computer science and engineering","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140717072","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