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i-manager's Journal on Mobile Applications and Technologies最新文献

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Smart antenna design for mobile application 移动应用智能天线设计
Pub Date : 1900-01-01 DOI: 10.26634/jmt.9.2.19065
B.M Sachin, Singh Chaudhary Virendra
Digitalization is becoming more and more important. Building smart houses and industries to offer humans longer lives is one of the main goals of the digitization movement. The main aim of this work is to make those verbal exchange modules more powerful with the aid of either improving the antennas to have a higher layout or changing it with new varieties of antennas that are better able to facilitate powerful verbal exchange. This paper proposes an antenna that can be applied to a verbal exchange module to be able to perform inside the Industrial, Scientific, and Medical (ISM) band at 2.4 GHz. After designing and simulating a complete Printed Circuit Board (PCB) antenna, it found that a few designs produced advanced simulation effects in terms of gain, reflection coefficient, voltage standing wave ratio (VSWR), and band width. Always-pointing antennae are protected by the layout of the antenna, allowing it to protect features inside the Global Positioning System (GPS) and ISM (Industrial, Scientific, and Medical) bands for Wi-Fi devices.
数字化变得越来越重要。建设智能住宅和智能产业以延长人类寿命是数字化运动的主要目标之一。这项工作的主要目的是通过改进天线以具有更高的布局或使用能够更好地促进强大的语言交换的新型天线来改变这些语言交换模块,从而使这些语言交换模块更强大。本文提出了一种可应用于语音交换模块的天线,使其能够在2.4 GHz的工业、科学和医疗(ISM)频段内工作。在对一个完整的印刷电路板(Printed Circuit Board, PCB)天线进行设计和仿真后,发现有几种设计在增益、反射系数、电压驻波比(VSWR)和带宽等方面产生了先进的仿真效果。始终指向的天线受到天线布局的保护,使其能够保护Wi-Fi设备的全球定位系统(GPS)和ISM(工业,科学和医疗)频段内的功能。
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引用次数: 0
Gradify: Analysis of twitter account using classification algorithm gradient:使用分类算法对twitter账户进行分析
Pub Date : 1900-01-01 DOI: 10.26634/jmt.9.2.19147
Gaur Gunjan, Bangad Naman, Jain Siddhi, Rana Manish, Kanchan Pranita
With technology's increasing capabilities, social media has become the largest pool of data from which it can extract public opinion and begin to gather informative data on the success or failure of a brand, product, or marketing campaign in the eyes of the public. People share their experiences, opinions, and daily activities on social media, which results in enormous amounts of online data that attract developers to carry out data mining and analysis. Thus, there is a necessity for social media screening to obtain results that can be used for analysis. Twitter is an online networking site driven by tweets, which are 140-character limited messages. Thus, the character limit enforces the use of hashtags for text classification. Currently, around 5500–6000, tweets are published every second, which results in approximately 561.6 million tweets per day. Performing sentiment analysis of tweets can help us to determine the polarity and inclination of a vast population toward a specific topic, term, or entity. The applications of such analysis can easily be observed during public elections, movie promotions, brand endorsements, and many other fields. This proposed system uses a Naïve Bayes classifier to determine the tweets based on sentiment. In the implemented system, tweets are collected, and sentiment analysis is performed on them. Based on the sentiment analysis results, a few suggestions can be provided to the user. The primary aim is to provide a method for analyzing sentiment scores based on grades. This paper reports on the design of sentiment analysis, extracting vast numbers of tweets. Results classify users' perceptions via tweets into positive and negative categories. Secondly, it discusses various techniques to carry out a sentiment analysis on Twitter data in detail.
随着技术能力的不断增强,社交媒体已经成为最大的数据池,它可以从中提取民意,并开始收集公众眼中品牌,产品或营销活动的成功或失败的信息数据。人们在社交媒体上分享他们的经历、观点和日常活动,从而产生了大量的在线数据,吸引了开发人员进行数据挖掘和分析。因此,有必要对社交媒体进行筛选,以获得可用于分析的结果。Twitter是一个由tweet驱动的在线社交网站,tweet是140个字符的限制信息。因此,字符限制强制使用hashtag进行文本分类。目前,每秒大约有5500-6000条推文发布,每天大约有5.616亿条推文发布。对tweet进行情感分析可以帮助我们确定大量人群对特定主题、术语或实体的极性和倾向。这种分析的应用可以很容易地在公共选举、电影宣传、品牌代言和许多其他领域中观察到。该系统使用Naïve贝叶斯分类器根据情感来确定推文。在实现的系统中,收集推文并对其进行情感分析。基于情感分析结果,可以为用户提供一些建议。主要目的是提供一种基于分数分析情绪得分的方法。本文报道了情感分析的设计,提取了大量的推文。结果将用户通过推特的看法分为积极和消极两类。其次,详细讨论了对Twitter数据进行情感分析的各种技术。
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引用次数: 0
EVALUATION OF MOBILE BANKING SERVICES USAGE IN MINNA, NIGER STATE 尼日尔州米纳斯市移动银行服务使用情况评估
Pub Date : 1900-01-01 DOI: 10.26634/jmt.6.1.15705
Baba Meshach, Moses Dogonyaro Noel, L. Y. Victor, Majeedah Omobolanle Olatunde
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引用次数: 0
COVID-19 ANDROID-BASED TEXT-TO-SPEECH APPLICATION: ANINCLUSION OF PEOPLE LIVING WITH READING AND SIGHTINGDISABILITIES 基于COVID-19的安卓文本转语音应用程序:包括有阅读和视力障碍的人
Pub Date : 1900-01-01 DOI: 10.26634/jmt.7.2.18340
M. S. Yahaya, Pam Davou Benjamin, Ibitoye Olanrewaju Emmanuel, Moses Dogonyaro Noel
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引用次数: 0
DIABETIC RETINOPATHY BASED ON GUI 基于GUI的糖尿病视网膜病变
Pub Date : 1900-01-01 DOI: 10.26634/jmt.8.1.18159
B. Sreenidhi, G. Thamotharan, A. Lalitha, C. Thanuprasanth
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引用次数: 0
FORENSIC ANALYSIS OF MOBILE BANKING APPLICATIONS IN NIGERIA 尼日利亚手机银行应用程序的法医分析
Pub Date : 1900-01-01 DOI: 10.26634/JMT.6.1.15704
A. Andrew, Osho Oluwafemi, I. Idris, M. A. Shafi'i
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引用次数: 2
A SIGN TRANSLATION APP TO CONVERT TO ASL TO AUDITORYENGLISH LANGUAGE 一个标志翻译应用程序转换为手语听力英语语言
Pub Date : 1900-01-01 DOI: 10.26634/jmt.8.1.18433
Farooqui Ayaan, Hatekar Aayush, Angadi Prateek, Shrikant Khyaati
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引用次数: 0
U-FARM: THE UNIFIED FRAMEWORK FOR AGRICULTURALEXTENSION U-farm:农业推广的统一框架
Pub Date : 1900-01-01 DOI: 10.26634/jmt.7.2.18370
R. Latha
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引用次数: 0
ENHANCING EFFICACY OF LEARNING DISABILITY CHILDRENTHROUGH MOBILE LEARNING 通过移动学习提高学习障碍儿童的学习效果
Pub Date : 1900-01-01 DOI: 10.26634/jmt.8.2.15191
Joan D. R. Robert
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引用次数: 0
COMPARATIVE STUDY OF AGILE METHODOLOGIES IN MOBILE APPLICATION DEVELOPMENT 移动应用开发中敏捷方法的比较研究
Pub Date : 1900-01-01 DOI: 10.26634/jmt.6.2.15485
S. Akanksha, G. Vijay
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引用次数: 0
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i-manager's Journal on Mobile Applications and Technologies
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