SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning

The field of machine learning (ML) has witnessed significant advancements in recent years. However, many existing algorithms lack interpretability and struggle with high-dimensional and imbalanced data. This paper proposes SPINEX, a novel similarity-based interpretable neighbor exploration algorithm designed to address these limitations. This algorithm combines ensemble learning and feature interaction analysis to achieve accurate predictions and meaningful insights by quantifying each feature's contribution to predictions and identifying interactions between features, thereby enhancing the interpretability of the algorithm. To evaluate the performance of SPINEX, extensive experiments on 59 synthetic and real datasets were conducted for both regression and classification tasks. The results demonstrate that SPINEX achieves comparative performance and, in some scenarios, may outperform commonly adopted ML algorithms. The same findings demonstrate the effectiveness and competitiveness of SPINEX, making it a promising approach for various real-world applications

Simplifying Causality: A Brief Review of Philosophical Views and Definitions with Examples from Economics, Education, Medicine, Policy, Physics and Engineering

This short paper compiles the big ideas behind some philosophical views, definitions, and examples of causality. This collection spans the realms of the four commonly adopted approaches to causality: Humes regularity, counterfactual, manipulation, and mechanisms. This short review is motivated by presenting simplified views and definitions and then supplements them with examples from various fields, including economics, education, medicine, politics, physics, and engineering. It is the hope that this short review comes in handy for new and interested readers with little knowledge of causality and causal inference.Comment: Under revie

Causal Diagrams for Structural Engineers

Causal diagrams are logic and graphical tools that depict assumptions about presumed causal relations. Such diagrams have proven effective in tackling a variety of problems in social sciences and epidemiology research yet remain foreign to civil engineers. Unlike the traditional means of examining relationships via multivariable regression, causal diagrams can identify the presence of confounders, colliders, and mediators. Thus, this paper hopes to introduce the big ideas behind causal diagrams (specifically, directed acyclic graphs (DAGs)) and how to create and apply such diagrams to several civil engineering problems. Findings from the presented case studies indicate that civil engineers can successfully use causal diagrams to improve their understanding of complex causation relations, thereby accelerating research and practical efforts

Learning Computer Networks Using Intelligent Tutoring System

Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of the ITS was done by a group of students and teachers. The results were acceptable

Vestibular-balance rehabilitation in patients with whiplash-associated disorders

Background and objective: Whiplash associated syndrome is one of the neck disorders that is accompanied by several chronic symptoms. Balancing problems arising from common disorders and dizziness are considered as manifestations that are time-consuming to evaluate and treat. The present study aims to investigate the effect of vestibular-balance rehabilitation using a test that can be used for differential diagnosis of these lesions by comparing dizziness handicap inventory (DHI) and Smooth Pursuit Neck Torsion (SPNT) scores. Method: This was an analytical cross-sectional study with a two-stage design. Forty patients with whiplash-associated disorders were randomly divided into control and intervention groups. SPNT test and DHI evaluation were performed for both groups. For twenty people selected randomly in the intervention group, vestibular-balance rehabilitation was performed during 12 sessions. Finally, the SPNT and DHI tests were performed again to examine and compare the results. Results: The results of this study showed that there was a statistically significant difference between the scores of smooth pursuit neck torsion gain in the SPNT test, the total score of DHI, the functional components of this questionnaire between the control and intervention groups after the implementation of the rehabilitation, and the differences in the physical, functional, and emotional components of the questionnaires of the control and intervention groups after rehabilitation exercises. Conclusion: Vestibular-balance rehabilitation exercises can be an effective treatment for dizziness and improving the quality of life of a person suffering from whiplash-associated disorder, followed by the reduction in dizziness caused by disability. © 2019 International Tinnitus Journal. All rights reserved

Near Ultra-Violet Electroluminescence from a ZnO Nanorods/p-GaN Heterojunction Light Emitting Diode

The heterostructure of the n-ZnO nanorod (NRs) arrays grown on the p-GaN layer was formed using lowcost hydrothermal technique in order to fabricate a light emitting diode (LED) device. Morphological, structural and optica l properties of as-prepared sample are described. The LED exhibited room temperature current-voltage (1-V) characteristics confirming a rectifying diode behaviour. The device presents near ultra-violet (UV) color under reverse bias. The electroluminescence (EL) spectrum of color emitting LED composed of intense peaks centered at 378 nm and 367 nm. The electroluminescence mechanism of the heterojunction LED was discussed in terms of band diagram

Generalized temperature-dependent material models for compressive strength of masonry using fire tests, statistical methods and artificial intelligence

Masonry has superior fire resistance properties stemming from its inert characteristics, and slow degradation of mechanical properties. However, once exposed to fire conditions, masonry undergoes a series of physio-chemical changes. Such changes are often described via temperature-dependent material models. Despite calls for standardization of such models, there is a lack in such standardized models. As a result, available temperature-dependent material models vary across various fire codes and standards. In order to bridge this knowledge gap, this paper presents three methodologies, namely, regression-based, probabilistic-based, and the use of artificial neural (ANN) networks, to derive generalized temperature-dependent material models for masonry with a case study on the compressive strength property. Findings from this paper can be adopted to establish updated temperature-dependent material models of fire design and analysis of masonry structures

Growth of n-ZnOnanorods on p-GaN using an Aqueous Solution Method

Wide band gap semiconductors like GaN and ZnO have high electron mobility and wide band gap energy. Zinc oxide (ZnO)nanorod arrays are grown on a seed-layer ZnO/GaN l sapphire substrate using a wet chemical bath deposition method. Chemical solution deposition is a low-temperature and possibly the lowest-cost method of growing ZnOnanorods on a GaN substrate. Field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD) measurements were used to examine the morphology, phase growth orientation and the structure of the ZnOnanorods and the GaN thin film. Optical property of the as-grown ZnOnanorodsand the GaN thin film was analyzed by room temperature photoluminescence measurements. The synthesis of vertically well-aligned nZnOnanorods on p-GaN film with large aspect ratio, high optical quality, and high density can be very useful for fabricating nanoelectronic and nano-optical devices

Chromaticity Study Of La2O3-PVA Phosphor Nanofibers Prepared By Electrospinning Process For Uv Light Down Conversion For White Light Emitting Diode

Lanthanum oxide-polyvinyl alcohol (La2O3-PVA) phosphor nanofibers had been prepared using electrospinning process with four different thicknesses (2.0, 6.0, 13.0 and 59.0 μm) and each sample with the same thickness was investigated with different annealing temperatures (100, 200, 300 and 500 ℃). The phosphor was used for light downconversion of UV light (365 nm) for fabrication of white light emitting diode (WLED). The resulting phosphor nanofibers were observed and analyzed by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM) and ultraviolet-visible (UV-Vis) spectroscopy. The chromaticity coordinates (CIE) and correlated color temperature (CCT) of the WLED were measured with different thickness and temperature of phosphor nanofibers by using HPC-2 lightsource colorimeter with applied voltage and current of 8.4 V and 0.14 A respectively. The comparison showed that lanthanum oxide-polyvinyl alcohol (La2O3-PVA) phosphor nanofibers exhibited CIE values of 0.3575, 0.4308 and CCT of 4835 K. The annealing temperature and thickness of phosphor were confirmed to be major factors that control the intensity of white light emitted from the sample

pH Sensing Characteristics of CuS/ZnO Thin Film Implemented as EGFET

Copper sulphide (CuS) is one of the most important semiconductor materials used in many applications for its semiconducting characteristics. CuS nanoscale thin films were deposited on various substrates using various methods of deposition; recently CuS thin films were used as extended gate field effect transistor (EGFET) and implemented as a pH sensor. In this work, CuS thin film was deposited on ZnO layer using spray pyrolysis deposition (SPD). CuS solution (0.4 M) was prepared from copper(II) chloride and sodium thiosulfate dissolved in deionised water. the precursors used to prepare CuS solution were copper chloride and sodium thiosulfate with 0.4 M concentration, and these precursors were solved using deionized water. The structural characteristics of this thin film show two phases for CuS; covellite and chalcocite with grain size of 31.2 nm. Nanoplate structure with a lot of aggregations was achieved from this deposition and it is confirmed by morphological examination, which estimates the roughness of the film to be 0.145 μm. CuS/ZnO thin film was used as EGFET and applied as pH sensor; the sensitivity and hysteresis were measured for this sensor to be 23.3 mV/pH and 17.5 mV, respectively