Low Profile MIMO Diversity Antenna with Multiple Feed

ABSTRACT A Compact low profile MIMO Diversity antenna system with multiple feeds with a size of 105mm*61.5mm is proposed. Multiple feeds are used to provide maximum power to antenna elements so that signal can propagate a long distance. The proposed antenna is achieving multiple frequencies, i.e. 2.5 GHz, 3.21 GHz, 4.22GHz, 4.68GHz, 6.5GHz, 6.74 GHz, 7 GHz and 8.35 GHz. Measured S-parameters show the isolation is -23.715 db. The maximum achievable bandwidth is 1.32 GHz (1320 MHz). This antenna can be applicable at Wimax, WLAN, LTE and Satellite Bands

A Feature-Based Approach for Sentiment Quantification Using Machine Learning

Sentiment analysis has been one of the most active research areas in the past decade due to its vast applications. Sentiment quantification, a new research problem in this field, extends sentiment analysis from individual documents to an aggregated collection of documents. Sentiment analysis has been widely researched, but sentiment quantification has drawn less attention despite offering a greater potential to enhance current business intelligence systems. In this research, to perform sentiment quantification, a framework based on feature engineering is proposed to exploit diverse feature sets such as sentiment, content, and part of speech, as well as deep features including word2vec and GloVe. Different machine learning algorithms, including conventional, ensemble learners, and deep learning approaches, have been investigated on standard datasets of SemEval2016, SemEval2017, STS-Gold, and Sanders. The empirical-based results reveal the effectiveness of the proposed feature sets in the process of sentiment quantification when applied to machine learning algorithms. The results also reveal that the ensemble-based algorithm AdaBoost outperforms other conventional machine learning algorithms using a combination of proposed feature sets. The deep learning algorithm RNN, on the other hand, shows optimal results using word embedding-based features. This research has the potential to help diverse applications of sentiment quantification, including polling, trend analysis, automatic summarization, and rumor or fake news detection

Software Quality Assurance in Software Projects: A Study of Pakistan

Abstract: Software quality is specific property which tells what kind of standard software should have. In a software project, quality is the key factor of success and decline of software related organization. Many researches have been done regarding software quality. Software related organization follows standards introduced by Capability Maturity Model Integration (CMMI) to achieve good quality software. Quality is divided into three main layers which are Software Quality Assurance (SQA), Software Quality Plan (SQP) and Software Quality Control (SQC). So In this study, we are discussing the quality standards and principles of software projects in Pakistan software Industry and how these implemented quality standards are measured and managed. In this study, we will see how many software firms are following the rules of CMMI to create software. How many are reaching international standards and how many firms are measuring the quality of their projects. The results show some of the companies are using software quality assurance techniques in Pakstan