Traditionally, mathematical models developed for the design of pit limits had been tailored to suit single ore deposits. The case where there are more than one type of ore (complex deposit) had been grossly neglected. This apparent neglect was caused by the difficulty of developing mathematical models that can take care of variations in values, cost of mining and processing that are inherent in complex ore deposits. In this paper, we introduce two new concepts: the complex stripping ratio and the compound unit of ores. These two concepts help to simplify the development of mathematical models for pit limit estimation [...]

Corona Virus pandemic has significant changes the way of doing work in the early year of 2020. A flexible work schedule allows employees to work virtually from home as this pattern of job continuity during the crisis, virtual working environment is implemented by organizations and gets benefits from a new concept of virtual work environment that increases productivity, efficiency & quality, but on other hand, the virtual work environment can cause humans severe health issues that affect the productivity as well. The major goal of this research is to look at how WFH affects employee productivity & health while working [...]

In this paper, a novel multi-view image compression model is proposed, which leverages block-based Compressive Sensing (BCS) as the encoder and TV-AL3 with view synthesis for decoding. The proposed model encodes a total of N images, out of which two are reference views denoted as VR, and the rest are non-reference views denoted as VNR. The encoding of the reference and non-reference views is performed independently using BCS. However, the sub-rate used for encoding the nonreference views is always lower than the sub-rate used for encoding the reference views. The objective of the proposed model is to improve the reconstruction [...]

Artificial intelligence (AI) is becoming increasingly common nowadays. The utilization of Machine Learning (ML) algorithm bring the significant consequences and outcomes. In this paper, we used Microsoft Azure Machine Learning Studio alone with supervised learning, classification, and regression. In this regard, the UCI dataset named auto-mobile have been used. We illustrate the experimental findings that demonstrate that our model approach is better to traditional approaches. The classification and regression challenges, can be solved efficiently and effectively. [...]

Data centers (DC) play a very important role in higher educational institutions (HEIs) all over the world, particularly in Pakistan for the provision of expedited and reliable services, especially during the Covid-19 pandemic. Due to that educational and financial businesses have been shifted online, which increasing the mandate of virtual data center framework with the support of Learning Management Systems (LMS), and Enterprise Resource Planning (ERP) for HEIs. The main reasons preventing this adoption are the cost, complexity, and security. This paper proposed a cost-effective approach for traditional DC. This method-imposed VMware ESXI Hypervisor, which utilizes a single server machine [...]

The rise of Web 2.0 has made it easier for people to share their opinions online. A significant application of Web 2.0 is micro-blogging. The proliferation of social media and related services, such as Twitter, has made it easier than ever to voice one's opinion on a wide range of topics. As a result, micro-blogging platforms are rich in data for use in Sentiment Analysis and opinion mining. Due to Twitter's character constraint of 140 characters, simple text-based analysis in this area typically proven unproductive because tweets do not consist of consistent and syntactically valid terms. In this [...]

This study aimed to find the optimal price for an airline ticket while ensuring that the customer does not cancel their booking. A dataset provided by an online airline reservation company in Pakistan named SASTAticket was used, which consisted of approximately 1 million records with 12 features. The independent variables included the booking date, booking time, departure date, departure time, refundable ticket, baggage weight, and baggage pieces, while the output variable was the target price to be predicted. Correlation analysis revealed a weak but significant relationship between the target variable and the baggage weight, baggage pieces, and booking month. Three [...]