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Marketing literature states that it is more costly to engage a new customer than to retain an existing loyal customer. Churn prediction models are developed by academics and practitioners to effectively manage and control customer churn in…
Accurate estimation of Network Performance is crucial for several tasks in telecom networks. Telecom networks regularly serve a vast number of radio nodes. Each radio node provides services to end-users in the associated coverage areas. The…
The multitude of data generated by sensors available on users' mobile devices, combined with advances in machine learning techniques, support context-aware services in recognizing the current situation of a user (i.e., physical context) and…
Passenger waiting time prediction plays a critical role in enhancing both ridesharing user experience and platform efficiency. While most existing research focuses on post-request waiting time prediction with knowing the matched driver…
In the era of rapid technological advancement, social media platforms such as Twitter (X) have emerged as indispensable tools for gathering consumer insights, capturing diverse opinions, and understanding public attitudes. This research…
Given that disturbances to the stable and normal operation of power systems have grown phenomenally, particularly in terms of unauthorized access to confidential and critical data, injection of malicious software, and exploitation of…
We present a novel efficient adaptive sensing and monitoring solution for a system of mobile sensing devices that support traffic monitoring applications. We make a key observation that much of the variance in commute times arises at a few…
Churn prediction, or the task of identifying customers who are likely to discontinue use of a service, is an important and lucrative concern of firms in many different industries. As these firms collect an increasing amount of large-scale,…
This study evaluates three probabilistic forecasting strategies using LightGBM: global pooling, cluster-level pooling, and station-level modeling across a range of scenarios, from fully homogeneous simulated data to highly heterogeneous…
Data inconsistencies are present in the data collected over a large wireless sensor network (WSN), usually deployed for any kind of monitoring applications. Before passing this data to some WSN applications for decision making, it is…
In this paper, we introduce an intelligent prediction system for mobile source localization in industrial Internet of things. The position and velocity of mobile source are jointly predicted by using Time Delay (TD) measurements in the…
Various implementations of wireless sensor networks (i.e. personal area-, wireless body area- networks) are prone to node and network failures by such characteristics as limited node energy resources and hardware damage incurred from their…
Cities across the United States are implementing information communication technologies in an effort to improve government services. One such innovation in e-government is the creation of 311 systems, offering a centralized platform where…
IEEE 802.11 Wireless Networks are getting more and more popular at university campuses, enterprises, shopping centers, airports and in so many other public places, providing Internet access to a large crowd openly and quickly. The wireless…
The adoption of machine learning techniques in next-generation networks has increasingly attracted the attention of the research community. This is to provide adaptive learning and decision-making approaches to meet the requirements of…
In the diverse landscape of 6G networks, where wireless connectivity demands surge and spectrum resources remain limited, flexible spectrum access becomes paramount. The success of crafting such schemes hinges on our ability to accurately…
The idea of modern urban systems and smart cities requires monitoring and careful analysis of different signals. Such signals can originate from different sources and one of the most promising is the BTS, i.e. base transceiver station, an…
Telecommunications operators (telcos) traditional sources of income, voice and SMS, are shrinking due to customers using over-the-top (OTT) applications such as WhatsApp or Viber. In this challenging environment it is critical for telcos to…
State-of-the-art space science missions increasingly rely on automation due to spacecraft complexity and the costs of human oversight. The high volume of data, including scientific and telemetry data, makes manual inspection challenging.…
Most current recommender systems used the historical behaviour data of user to predict user' preference. However, it is difficult to recommend items to new users accurately. To alleviate this problem, existing user cold start methods either…