In this letter, we derive the probability density function (PDF) and cumulative distribution function (CDF) of the minimum of two non-central Chi-square random variables with two degrees of freedom in terms of power series. With the help of the derived PDF and CDF, we obtain the exact ergodic capacity of the following adaptive protocols in a decode-and-forward (DF) cooperative system over dissimilar Rician fading channels: (i) constant power with optimal rate adaptation; (ii) optimal simultaneous power and rate adaptation; (iii) channel inversion with fixed rate. By using the analytical expressions of the capacity, it is observed that the optimal power and rate adaptation provides better capacity than the optimal rate adaptation with constant power from low to moderate signal-to-noise ratio values over dissimilar Rician fading channels. Despite low complexity, the channel inversion based adaptive transmission is shown to suffer from significant loss in capacity as compared to the other adaptive transmission based techniques over DF Rician channels.

On the Capacity of Decode-and-Forward Relaying over Rician Fading Channels

Nowadays, customers have become more interested in the quality of service (QoS) that organizations can provide them. Services provided by different vendors are not highly distinguished which increases competition between organizations to maintain and increase their QoS. Customer Relationship Management systems are used to enable organizations to acquire new customers, establish a continuous relationship with them and increase customer retention for more profitability. CRM systems use machine-learning models to analyze customers’ personal and behavioral data to give organization a competitive advantage by increasing customer retention rate. Those models can predict customers who are expected to churn and reasons of churn. Predictions are used to design targeted marketing plans and service offers. This paper tries to compare and analyze the performance of different machine-learning techniques that are used for churn prediction problem. Ten analytical techniques that belong to different categories of learning are chosen for this study. The chosen techniques include Discriminant Analysis, Decision Trees (CART), instance-based learning (k-nearest neighbors), Support Vector Machines, Logistic Regression, ensemble–based learning techniques (Random Forest, Ada Boosting trees and Stochastic Gradient Boosting), Naive Bayesian, and Multi-layer perceptron. Models were applied on a dataset of telecommunication that contains 3333 records. Results show that both random forest and ADA boost outperform all other techniques with almost the same accuracy 96%. Both Multi-layer perceptron and Support vector machine can be recommended as well with 94% accuracy. Decision tree achieved 90%, naive Bayesian 88% and finally logistic regression and Linear Discriminant Analysis (LDA) with accuracy 86.7%.

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Machine-Learning Techniques for Customer Retention: A Comparative Study

This study was conducted in order to make a Market Basket Analysis by using Association Rules. The data used in the study are the sales data of any supermarket received from the Vancouver Island Un...

Market basket analysis with association rules

Recently, artificial intelligence (AI) technology receives extensive attention in the manufacturing field. As the core technology, it generates considerable interest among smart manufacturing and Industry 4.0 strategy. Product lifecycle management (PLM) copes with various kinds of engineering, business, and management activities concerning a product throughout its whole lifecycle—from the inception of an intangible concept through the recycling of a finished product. In the context of smart manufacturing, this paper reviews various theories, algorithms, and technologies of AI to different stages of PLM (i.e., product design, manufacturing, and service). A structured roadmap is presented to navigate the future research and application of AI in PLM. This paper also discusses the opportunities and challenges of applying AI for PLM.

Artificial intelligence in product lifecycle management

Code smells indicate software design problems that harm software quality. Data-intensive systems that frequently access databases often suffer from SQL code smells besides the traditional smells. While there have been extensive studies on traditional code smells, recently, there has been a growing interest in SQL code smells. In this paper, we conduct an empirical study to investigate the prevalence and evolution of SQL code smells in open-source, data-intensive systems. We collected 150 projects and examined both traditional and SQL code smells in these projects. Our investigation delivers several important findings. First, SQL code smells are indeed prevalent in data-intensive software systems. Second, SQL code smells have a weak co-occurrence with traditional code smells. Third, SQL code smells have a weaker association with bugs than that of traditional code smells. Fourth, SQL code smells are more likely to be introduced at the beginning of the project lifetime and likely to be left in the code without a fix, compared to traditional code smells. Overall, our results show that SQL code smells are indeed prevalent and persistent in the studied data-intensive software systems. Developers should be aware of these smells and consider detecting and refactoring SQL code smells and traditional code smells separately, using dedicated tools.

On the Prevalence, Impact, and Evolution of SQL Code Smells in Data-Intensive Systems

Market Basket Analysis: Identify the Changing Trends of Market Data Using Association Rule Mining

In this work, the performance of communication system inside the densely packed small cells or femtocells with maximum ratio combining (MRC) diversity is studied. The line of sight (LOS) a...

Performance analysis of Beaulieu‐Xie fading channel with MRC diversity reception

This paper analyzes the performance of decode-and-forward (DF)-based multi-hop relaying communication systems over α - κ - μ and α - κ - μ -Extreme fading channels Analytical formulas for the probability density function (PDF) and the cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) as well as its moment generating function (MGF) are derived Based on the derived PDFs, novel closed-form expressions for the outage probability (OP), bit error rate (BER) under coherent and non-coherent modulation schemes are derived Additionally, asymptotic analyses of BER based on Poincare series expansions of SNR PDFs are carried out and results show good approximations for low SNR regimes Simulations are performed to verify the accuracy and to show the tightness of the theoretical analysis

On the outage probability and BER of a DF-based multi-hop system over α-κ-μ and α-κ-μ-extreme fading channels

The three-term PID controllers are significantly used in most of the benchmarked systems as controllers. However, the benchmarked Single Input Multiple Output (SIMO) systems may require more than one PID controllers in the control loops, the way to design PID controllers is not an easy task. Although, the linear PID (L-PID) controllers are not yielded a satisfactory control results for a benchmarked system due to the presence of inherent nonlinearities. In order to improve performance, the linear PID controllers are modified by nonlinear characteristics. In this paper, the linear and nonlinear PID (NL-PID) controllers are implemented for the stabilization and control of Gantry Crane System as a test problem. The experimental results prove that the multi-loop NL-PID controllers exhibit more robustness to outer large with fast external disturbances. The L-PID and NL-PID controllers are compared to find out the best controller, which gives optimum responses and can also handle external disturbances.

Design of Multi-Loop L-PID and NL-PID Controllers: An Experimental Validation

In contrary to Shannon’s ergodic capacity, the delay-constrained effective rate is used to define the maximum data rate of the real-time applications in 5G and beyond networks. The effective capacity (EC) performance of the delay sensitive communication system over Fisher-Snedecor F fading channel with maximum ratio combining is studied. The closed-form mathematical expressions for the EC are derived in terms of Meijer G-function and the effect of different fading parameters on the effective throughput of the system is demonstrated. The simplified asymptotic expression for high signal-to-noise ratio (SNR) and low SNR regimes are provided to gain more insight into the system. The effect of different system parameters on the EC performance is also demonstrated. Simulation results are corroborated along with the numerical results to verify the correctness of the proposed formulations.

Manpreet Kaur

Papers

Market Basket Analysis: Identify the Changing Trends of Market Data Using Association Rule Mining

Performance analysis of Beaulieu‐Xie fading channel with MRC diversity reception

On the outage probability and BER of a DF-based multi-hop system over α-κ-μ and α-κ-μ-extreme fading channels

Design of Multi-Loop L-PID and NL-PID Controllers: An Experimental Validation

Effective Capacity Analysis Over Fisher-Snedecor F Fading Channels with MRC Reception