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With the spread of inverters, the attention of designers naturally turned to 5-phase motors, due to their advantageous properties. In this regard, perhaps the most important issue in the design of such machines is the selection of the correct rotor slot number. Many articles have been published on multiphase machines, however, only few of them…

Applying black-box ML models in high-stakes fields like criminology, healthcare and real-time operating systems might create issues because of poor interpretability and complexity. Also, model building methods that include interpretability is now one of the growing research topics due to the absence of interpretability metrics that are both model-agnostic and quantitative. This paper introduces model…

The development of Machine Learning methods and approaches offers enormous growth opportunities in the Healthcare field. One of the most exciting challenges in this field is the automation of clinical treatment selection for patient state optimization. Using necessary medical data and the application of Machine Learning methods (like the Genetic Algorithm and the Analytic Hierarchy…

Research focused on training and testing of dataset after Optimizing Software Component with the help of deep neural network mechanism. Optimized components are selected for training and testing to improve the accuracy at the time of software selection. Selected components are required to be attuned and accommodating as per requirement. Soft computing mechanism such as…

Coordinated MultiPoint (CoMP) has been introduced for LTE-Advanced system to overcome the inter-cell interference problems and enhance the signal quality of cell-edge UEs (User Equipments). With such concept, the overall system performance should be improved considerably to support the significantly increasing amount of demand on data transmission via mobile communication that happens nowadays. Dynamic Point…

With the rising number of web services created to build complex business processes, selecting the appropriate web service from a large number of web services respond to the same client request with the same functionality are developed independently but with different quality of service (QoS) attributes. From this point, there are many approaches to web…

Quality of service is a significant part of formulating a composing of web services to satisfy the user’s request, especially when several services exist and have been implemented in the same field and functionality. The selection process of web services among many options can be taken based on the quality of service considerations, fitness parameters,…

Despite the significant progress made in data mining technologies in recent years, breast cancer risk prediction and diagnosis at an early stage using DNA microarray technology still a real challenging task. This challenge comes especially from the high-dimensionality in gene expression data, i.e., an enormous number of genes versus a few tens of subjects (samples).…

Feature selection method applied on an intrusion dataset is used to classify the intrusion data as normal or intrusive. We have made an attempt to detect and classify the intrusion data using rank-based feature selection classifiers. A set of redundant features having null rank value are eliminated then the performance evaluation using various feature selection…

A distribution company in Mexico covers the travel expenses for 21 sales representatives. Currently, the routes they follow are not established clearly, which can lead to high costs in this subject. A reduction of such cost is sought after, by optimizing the routes for each one of them. The following research finds an improvement on…

As an emergent technology in Internet of Things (IoT), the ultimate target of fog computing is to provide a widely distributed computational resources and data repository closer to the network edge providing heterogeneous systems both in terms of software and hardware. The fog system must have the capability to deal with huge number of resources…

Due to the recent development of information and communication technology, such as sensor technology, IoT technology, and smart technology, interest in maker education is increasing. Maker education offers students experience-based education that allows them to make their own results, giving them various interests and motivations. Recently, various research results on maker education have been under…

The task of fuzzy mathematical modeling of the composition of a polymer composition is singled out and formulated, as one of the types of chemical-technological systems for creating the theoretical foundations for managing the physicochemical properties of the material produced from this composition. Fuzzy data on the technical functions and concentration of individual ingredients that…

In the last years, industrial company began to understand the central role that plays sustainable supplier selection (SSS) process for obtaining a sustainable supply chain (SSC). This paper proposes a new multi-criterion decision-making (MCDM) model for managers, which makes it possible to select the best suppliers who respect the sustainable development (SD) concept for a…

Music genre classification is an important multimedia research domain, including aspects of music piece representation, distances between genres, and categorization of music databases. The objective of this study was to develop a model for automatic classification of musical genres from audio data by using features from low-level time and frequency domains. These features can highlight…

There are high expectations for commercial cloud services as an economical computation resource when executing scientific computing workflows, for which the computation is increasing on a daily basis. However, no method has been developed for determining whether a scientific computing workflow can be executed at a low usage cost, and thus scientists have difficulty in…

Cloud Computing is considered nowadays an attractive solution to serve the Big Data storage, processing, and analytics needs. Given the high complexity of Big Data workflows and their contingent requirements, a single cloud provider might not be able alone to satisfy these needs. A multitude of cloud providers that offer myriad of cloud services and…

Recently, the number of industrial accidents of chemical plants has been increasing in Japan. The fault detection system is required to keep chemical plant safely. In this study, a fault detection system for a chemical plant using agent framework and negative selection algorithm was proposed. The negative selection algorithm is one of artificial immune systems.…

The increased motivation (by service providers) to offer user-centric and seamless communication services – that satisfies users’ quality of experience (QoE), has manifested a myriad of challenges in the field of wireless communication; and given the increased traffic capacity and sudden explosion of cellular devices, communication systems are constantly threatened by performance related issues –…

In futures markets, a single asset is generally represented by several contracts with different maturities. The selection of specific contracts is an inevitable task that also creates new opportunities, especially in terms of speculative trading. Evaluating immediate and upcoming trading costs for all considered contracts might lead to a significantly improved performance. Among that, even…

Application-oriented Wireless Sensor Networks (WSNs) promises to be one of the most useful technologies of this century. However, secure communication between nodes in WSNs is still an unresolved issue. In this context, we propose two protocols (i.e. Optimal Secure Path (OSP) and Sub-optimal Secure Path (SSP)) to minimize the outage probability of secrecy capacity in…

Investment decision-making plays a pivotal role in shaping both individual and institutional economic outcomes. Given the increasing complexity and uncertainty in global markets, optimizing investment decisions has become essential for maximizing returns while managing risks. This work explores modern optimization approaches in investment decision-making, focusing on mathematical modeling techniques such as linear programming (LP), mixed-integer…

While prior research has focused on siloed approaches to equipment replacement, this study introduces an integrated decision-making framework that synergizes predictive maintenance (IoT/M), dynamic multi-criteria analysis (MCDM), and sustainability-driven material selection. By validating this model through cross-sector case studies and strategic operational planning across various industrial sectors. We demonstrate a 30% improvement in replacement timing…

The integration of machine learning techniques in industrial production has the potential to revolutionize traditional manufacturing processes. In this study, we examine the efficacy of gradient-boosting machine learning models, specifically focusing on feature engineering techniques, applied to a novel dataset with 3D product models pertaining to work moan-hours in metal sheet stamping projects, framed as…

The proliferation of internet economies has given the corporate world manifold advantages to businesses, as they can now incorporate the latest innovations into their operations, thereby enhancing ease of doing business. For instance, financial institutions have leveraged credit card usage on the aforesaid proliferation. However, this exposes clients to cybercrime, as fraudsters always find ways…