The k-means algorithm: A comprehensive survey and performance evaluation

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The k-means clustering algorithm is considered one of the most powerful and popular data mining algorithms in the research community. However, despite its popularity, the algorithm has certain limitations, including problems associated with random initialization of the centroids which leads to unexpected convergence. Additionally, such a clustering algorithm requires the number of clusters to be defined beforehand, which is responsible for different cluster shapes and outlier effects. A fundamental problem of the k-means algorithm is its inability to handle various data types. This paper provides a structured and synoptic overview of research conducted on the k-means algorithm to overcome such shortcomings. Variants of the k-means algorithms including their recent developments are discussed, where their effectiveness is investigated based on the experimental analysis of a variety of datasets. The detailed experimental analysis along with a thorough comparison among different k-means clustering algorithms differentiates our work compared to other existing survey papers. Furthermore, it outlines a clear and thorough understanding of the k-means algorithm along with its different research directions

MHD flow in a vertical channel under the effect of temperature dependent physical parameters

Mixed convective flow in a vertical channel filled with electrically conducting viscous fluid with isothermal wall conditions is investigated for variable properties. The combined effects of temperature dependent viscosity and temperature dependent thermal conductivity are analyzed. The solutions are obtained both analytically by perturbation method and numerically by Runge–Kutta method with shooting technique. The dimensionless governing parameters affecting velocity and temperature fields are variable viscosity parameter (−0.5 ≤ bν ≤ 0.5), variable thermal conductivity parameter (−0.5 ≤ bk ≤ 0.5), Hartmann number (1 ≤ M ≤ 3), applied electric field parameter (E0 = ±1, 0), wall temperature ratio parameter (−2 ≤ m ≤ 2) and buoyancy parameter (0 < N ≤ 1.5). For some limiting cases, the obtained results are validated by comparing with those available from the existing literature. Correlations for skin friction and Nusselt number in terms of governing parameters are developed

Brexit or Brand it? The effects of attitude towards Brexit and reshored brands on consumer purchase intention

Brexit has caused a seismic shift in the British socio-economic and political landscapes, creating widespread uncertainties, while simultaneously giving hope and national pride to millions. The decision by a number of organizations to reshore their production has opened a new era for business management that challenges the axiomatic assumption of the benefits of offshored production. Although reshoring predates Brexit, the link between the two in the British context is not just serendipitous and they are argued to have reasonable interlinkages. However, there is inadequate empirical evidence to suggest that British consumers’ attitude towards Brexit has any effect on their intention to purchase reshored brands. Through a mixed-methods study comprising a survey of 415 respondents and 20 in-depth interviews, this paper addresses this research gap. Findings suggest that corporate social responsibility (CSR) and consumer reshoring sentiment (CRS) have positive effects on consumers’ attitude towards reshored brands. Despite CRS's positive influence on attitude towards Brexit, the latter does not have any significant effects on the intention to purchase a reshored brand, which is positively influenced by the attitude towards the same brand. As such, companies should enhance the image of their brands and CSR in order to harness the benefits of reshoring

CPEC: Pakistan-China Cordial Ties - A Boost to Pakistan's Economy

This paper highlights the need of energy production in Pakistan and to determine the extent to which China Pakistan Economic Corridor (CPEC) and its energy projects will contribute to the economic growth and development of Pakistan. In this regard, a fair amount of literature has been reviewed. The literature review presented confirms that a positive relationship exists between the energy production, security and economic development.&nbsp; The long term friendship of Pakistan and China is discussed and how this tie has benefitted both the countries. Chinese cooperation and assistance with Pakistan is well evident from the substantial Chinese investment in Pakistan’s infrastructural expansion particularly development of Pakistan’s deep-water port at Gwadar. Under its One Belt One Road plan, China and Pakistan have collaboratively started a multibillion mega project, China Pakistan Economic Corridor. Under CPEC twenty-one energy projects being established, that is supposed to reduce the energy poverty generation in Pakistan. The study finds out that the sufficiency in energy sector will boost economy by energizing the industry and businesses as well as by creating thousands of direct and indirect employment opportunities

Location Based Power Reduction Cloud Integrated Social Sensor Network

It is great to hear about the advancements in wireless sensor networks and their applications, as well as the integration of cloud computing to enhance data analysis and storage capabilities. Indeed, these technologies have opened up numerous possibilities across various fields, including infrastructure tracking, environmental monitoring, healthcare, and more. The concept of a social sensor cloud, as you mentioned, brings an interesting dimension to this technology landscape by focusing on knowledge-sharing and connecting like-minded individuals or organizations. This could potentially lead to more collaborative and efficient solutions across a wide range of domains. Energy efficiency is a critical consideration in the design and operation of wireless sensor networks and the cloud infrastructure that supports them. The limited battery life of sensors necessitates careful management of energy consumption to ensure optimal functionality and longevity. Sleep scheduling methods are a common technique used to manage energy consumption in these networks. By coordinating when sensors are active and when they are in a low-power sleep mode, energy consumption can be significantly reduced without compromising the network's overall effectiveness. In the context of the Social Sensor Cloud, managing energy efficiency becomes even more crucial due to the shorter battery life of the sensors involved. This is particularly relevant given the growing concerns about environmental sustainability and the need to reduce energy consumption across technological systems. It's clear that your research paper addresses these challenges head-on, by exploring energy-efficient techniques for the Social Sensor Cloud. Sleep scheduling is just one of the many strategies that researchers and engineers are working on to strike a balance between functionality and energy consumption. Other methods might include optimizing data transfer protocols, developing energy-harvesting mechanisms, and enhancing sensor hardware efficiency. As technology continues to evolve, the integration of wireless sensor networks, cloud computing, and social networks will likely pave the way for innovative solutions and transformative applications. Addressing energy efficiency concerns will undoubtedly play a crucial role in ensuring the long-term viability and positive impact of these technologies