Advanced Computer Applications Research Articles

Application of machine learning technique for dynamic analysis of confined geomaterial subjected to vibratory load

Computer programming-based numerical programs are firmly established in geotechnical engineering, with rapid growth of finite element modeling and machine learning techniques gaining much attention both in practice and academia. This study is intended to expedite the dissemination of advanced computer applications in terms of finite element simulation and machine learning models by investigating the dynamic response of geomaterials subjected to vibratory loads. Several trial models were built to perform the experimental investigations with a vibratory shaker, signal generator, several accelerometers, a data collection system, and other ancillary devices. The implicit integration techniques in commercialized software were adopted for numerical simulations. After data collection from numerical simulation, models were chosen, trained, and assessed to produce predictions that were then used in this study. Several technologies, including the ensemble boosted tree, squared exponential Gaussian Process Regression (GPR), Matern 5/2 GPR, exponential GPR, and decision tree architectures (fine and medium), were used to forecast the displacement of confined geomaterial. The displacement-depth ratio was found rising to 80% in the frequency range of 5 to 25 Hz, suggesting a considerable change in the behavior of the geomaterial. The Matern 5/2 GPR model showed better accuracy with an R2 value of 0.99, indicating an outstanding predictive ability. The Matern 5/2 GPR and boosted tree models could help better understand the links between displacement and its distribution along the direction of load application. The outcomes of this study based on computer-aided finite element programs can be effectively implemented in machine learning to develop computer programs. In conclusion, the computational machine learning models adopted in this study offer a new insight for uncovering hidden intrinsic laws and creating new knowledge for geotechnical researchers and practitioners.

Comparative analysis of audio classification with MFCC and STFT features using machine learning techniques

In the era of automated and digitalized information, advanced computer applications deal with a major part of the data that comprises audio-related information. Advancements in technology have ushered in a new era where cutting-edge devices can deliver comprehensive insights into audio content, leveraging sophisticated algorithms such such as Mel Frequency Cepstral Coefficients (MFCCs) and Short-Time Fourier Transform (STFT) to extract and provide pertinent information. Our study helps in not only efficient audio file management and audio file retrievals but also plays a vital role in security, the robotics industry, and investigations. Beyond its industrial applications, our model exhibits remarkable versatility in the corporate sector, particularly in tasks like siren sound detection and more. Embracing this capability holds the promise of catalyzing the development of advanced automated systems, paving the way for increased efficiency and safety across various corporate domains. The primary aim of our experiment is to focus on creating highly efficient audio classification models that can be seamlessly automated and deployed within the industrial sector, addressing critical needs for enhanced productivity and performance. Despite the dynamic nature of environmental sounds and the presence of noises, our presented audio classification model comes out to be efficient and accurate. The novelty of our research work reclines to compare two different audio datasets having similar characteristics and revolves around classifying the audio signals into several categories using various machine learning techniques and extracting MFCCs and STFTs features from the audio signals. We have also tested the results after and before the noise removal for analyzing the effect of the noise on the results including the precision, recall, specificity, and F1-score. Our experiment shows that the ANN model outperforms the other six audio models with the accuracy of 91.41% and 91.27% on respective datasets.

Unveiling Advanced Computational Applications in Quantum Computing: A Comprehensive Review

The field of advanced computing applications could experience a significant impact from quantum computing, which is a rapidly developing field with the potential to revolutionize numerous areas of science and technology. In this review, we explore into the various ways in which complex computational problems could be tackled by utilizing quantum computers, including machine learning, optimization, and simulation. One potential application of quantum computers is in machine learning, where they could be used to improve the accuracy and efficiency of algorithms. Complex optimization problems, such as those encountered in logistics and finance, can be addressed using quantum computers as well. Furthermore, the utilization of quantum computers could enable the simulation of intricate systems, such as molecules and materials, leading to significant applications in fields like Physics and Material Technology. Although quantum computers are currently in the early stages of development, they possess the potential to propel numerous areas of science and technology forward in a significant manner. Further research and development are needed to fully realize the potential of quantum computing in the field of advanced computing applications.

Impact of Street Lighting Level on Floodlights

The article presents selected results of research related to the use of outdoor lighting, mainly street lighting, in the design of facility illumination. The indicated subject matter primarily concerns architectural structures that are located in urbanized city spaces and in the strict centers of old cities. It is in these areas that there is usually a significant saturation of historic secular and sacred buildings with significant tourist values. At the same time, the immediate surroundings of the structures are usually wrapped by a dense network of street lighting infrastructure. This illumination can be a major setback in the process of illumination planning. Therefore, it is necessary to take into account the extent of this impact on the planned illumination work, related to the selection, mounting, and direction of illumination equipment. This is related to the distance of the street luminaires from the facade, the height of their installation, the distance of the poles from each other, the power of the street luminaires, and the luminous flux distribution of the luminaires used. The purpose of the work undertaken was to analyze the extent to which outdoor lighting influences the planned illumination of an architectural structure and to explore the possibility of its potential use as a component of illumination. Analytical work was conducted at two levels of detail using advanced graphical computer applications. After general considerations and the derivation of conclusions, an example of illumination of a large sacral building was realized successfully using the element of street lighting as a component of illumination.

Drone usage for pavement damage identification

Abstract: The timely use of appropriate renovation measures can effectively extend the life of road surfaces. For this purpose, it is necessary to carry out a detailed identification of damage, and then on its basis to assess the condition of road surfaces. Due to the development of advanced measurement techniques and computer applications, damage to pavements can be monitored faster and more accurately. This article presents a method of identifying damage to the pavement of a large area of the square with the use of a drone. The applicated method allowed to visualize and differentiate various surface defects faster and more preciously. The method also enabled determine causes and genesis of damage more greatly. Keywords: Drone; Pavement damage; DJI SPARK, Damage Identification

Mathematical justification on the origin of the sigmoid in logistic regression

Logistic regression is a commonly used classification algorithm in machine learning. It allows categorizing data into discrete classes by learning the relationship from a given set of labeled data. It learns a linear relationship from the given data set and then introduces nonlinearity through an activation function to determine a hyperplane that separates the learning points into two subclasses. In the case of logistic regression, the sigmoid is the most used activation function to perform binary classification. The choice of sigmoid for binary classifications is justified by its ability to transform any real number into a probability between 0 and 1. This study provides, through two different approaches, a rigorous mathematical answer to the crucial question that torments us, namely where does this logistic function on which most neural network algorithms are based come from? References Stoltzfus, "Logistic regression: A brief primer," Academic Emergency Medicine, vol. 18, no. 10, pp. 1099-1104, 2011. Peng et al, "An introduction to logistic regression analysis and reporting," The Journal of Educational Research, vol. 96, no. 1, pp. . Costa et al, "A logistic regression model for consumer default risk," Journal of Applied Statistics, vol. 47, no. 13-15, pp. 2879-2894, 2020. Gatzert and M. Schubert, "Cyber risk management in the us banking and insurance industry: A textual and empirical analysis of determinants and value," Journal of Risk and Insurance, vol. 89, no. 3, pp. 725-763, 2022. Premsmith and H. Ketmaneechairat, "A predictive model for heart disease detection using data mining techniques," Journal of Advances in Information Technology, vol. 12, pp. 14-20, 2021. Almotiri et al, "Using api with logistic regression model to predict hotel reservation cancellation by detecting the cancellation factors," International Journal of Advanced Computer Science and Applications, vol. 12 , no. 6 , pp. . Kudupudi et al, "Spam message detection using logistic regression," International Journal of Advanced Computer Science and Applications, vol. 9, no. 9, pp. 815-818, 2021. Keren and . Cuiwei, "Housing price analysis using linear regression and logistic regression: A comprehensive explanation using melbourne real estate data," in 2021 IEEE International Conference on Computing (ICOCO), 2021, pp. 241-246. Dheeru and G. Casey, "UCI machine learning repository," 2017. [Online]. Available: http://archive.ics. uci.edu/ml Goldbloom, "Kaggle dataset," 2010. [Online]. Available: https: //www.kaggle.com/ Febrianti et al, "The parameter estimation of logistic regression with maximum likelihood method and score function modification," Journal of Physics: Conference Series, vol. 1725, no. 1, p. 012014, 2021. Lucena, "Loss functions for classification using structured entropy," 2022. [Online]. Available: https://arxiv.org/abs/2206.07122 Hikmat and A. Abdulazeez, "Comparison of optimization techniques based on gradient descent algorithm: a review," PalArch?s Journal of Archaeology of Egypt/Egyptology, vol. 18, no. 4, pp. 2715-2743, 2021.E. Norton et al, “Odds ratios-current best practice and use,” Journal of the American Medical Association, vol. 320, no. 1, pp. 84–85, 2018 Tong, Fundamental Properties and Sampling Distributions of the Multivariate Normal Distribution. Springer New York, 1990, pp. 23– 61.

Determining the optimal strategy for aggregate production planning (APP) during the Covid-19 crisis using an algorithm Harmony Search Algorithm

Determining the optimal strategy for aggregate production planning (APP) during the Covid-19 crisis using an algorithm Harmony Search Algorithm

Heterogeneity in biomarkers, mitogenome and genetic disorders of the Arab population with special emphasis on large-scale whole-exome sequencing.

More than 25 million DNA variations have been discovered as novel including major alleles from the Arab population. Exome studies on the Saudi genome discovered > 3000 novel nucleotide variants associated with > 1200 rare genetic disorders. Reclassification of many pathogenic variants in the Human Gene Mutation Database and ClinVar Database as benign through the Arab database facilitates building a detailed and comprehensive map of the human morbid genome. Intellectual disability comes first with the combined and observed carrier frequency of 0.06779 among Saudi Arabians; retinal dystrophy is the next highest. Genome studies have discovered interesting novel candidate disease marker variations in many genes from consanguineous families. More than 7 pathogenic variants in the C12orf57 gene are prominently associated with the etiology of developmental delay/intellectual impairment in Arab ancestries. Advances in large-scale genome studies open a new outlook on Mendelian genes and disorders. In the past half-dozen years, candidate genes of intellectual disability, neurogenetic disorders, blood and bleeding disorders and rare genetic diseases have been well documented through genomic medicine studies in combination with advanced computational biology applications. The Arab mitogenome exposed hundreds of variations in the mtDNA genome and ancestral sharing with Africa, the Near East and East Asia and its association with obesity. These recent discoveries in disease markers and molecular genetics of the Arab population will have a positive impact towards supporting genetic counsellors on reaching consanguineous families to manage stress linked to genetics and precision medicine. This narrative review summarizes the advances in molecular medical genetics and recent discoveries on pathogenic variants. Despite the fact that these initiatives are targeting the genetics and genomics of disorders prevalent in Arab populations, a lack of complete cooperation across the projects needed to be revisited to uncover the Arab population's prominent disease markers. This shows that further study is needed in genomics to fully comprehend the molecular abnormalities and associated pathogenesis that cause inherited disorders in Arab ancestries.

Advanced Mathematics and Computational Applications in Control Systems Engineering

Control-systems engineering is a multidisciplinary subject that applies automatic-control theory to design systems with desired behaviors in control environments [...]

Teachers’ Information and Communication Technology (ICT) Skills Assessment: Basis for a Comprehensive ICT Training Program

The study described the extent of knowledge in ICT skills of 180 teachers as a basis for a training plan in a selected schools division in Region 3. A descriptive survey method was utilized having a weighted mean and standard deviation to treat the data collected. It was concluded that the teachers displayed a proficient extent of knowledge in basic ICT skills. However, some of the skills enumerated have a low mean and were close to the adjacent group scale of the lower level of knowledge. Furthermore, they showed limited knowledge in some advanced computer applications which are necessary for the construction of instructional materials. The self-assessment revealed that they are knowledgeable in ICT skills, but they do not know how to use it in complex applications. The skills for development based on the training needs assessment reiterated a combination of skills which further clarified that not all skills under a certain application are known. It is then recommended that training needs assessment should always be conducted by school administrators to gather data on the actual needs of the teachers as a basis in planning a thorough training matrix to ensure that the development and training provided are based on the needs of the teachers.

Preface

6th Annual International Conference on Computer Science and Applications [CSA2020] has been held on September 25-27, 2020 (Virtual Conference). CSA2020 aims to bring researchers, engineers, and students to the areas of advanced computer science and applications. CSA2020 features unique mixed topics of software engineering, computer science, computer applications and computer network.We received a total of 158 submissions from various parts of the world. The Technical Program Committee worked very hard to have all papers reviewed before the review deadline. The final technical program consists of 72 papers. All the accepted papers have been submitted to strict peer-review by 2-4 expert referees, and selected based on originality, significance and clarity for the purpose of the conference. The conference program is extremely rich, profound and featuring high-impact presentations of selected papers and additional late-breaking contributions. We sincerely hope that the conference would not only show the participants a broad overview of the latest research results on related fields, but also provide them with a significant platform for academic connection and exchange. The keynote speaker is internationally recognized leading experts in his research fields, who has demonstrated outstanding proficiency and have achieved distinction in his profession. The proceedings would be published by IOP Conference Series: Journal of Physics: Conference Series (JPCS).We would like to express our sincere gratitude to all the members of Technical Program Committee and organizers for their enthusiasm, time, and expertise. Our deep thanks also go to many volunteers and staffs for the long hours and hard work they have generously given to CSA2020. The last but not least, we would like to thank all the authors, speakers and participants for their great contributions to the success of CSA2020.CSA2020 Organizing CommitteeList of Committee of CSA2020, Keynote speaker, Editors, Technical Program Committees are available in this pdf.

Teachers’ Information and Communication Technology Skills Assessment: Basis for a Comprehensive ICT Training Program

The study described the extent of knowledge in ICT skills of 180 teachers as a basis for a training plan in a selected schools division in Region 3. A descriptive survey method was utilized having a weighted mean and standard deviation to treat the data collected. It was concluded that the teachers displayed a proficient extent of knowledge in basic ICT skills. However, some of the skills enumerated have a low mean and were close to the adjacent group scale of the lower level of knowledge. Furthermore, they showed limited knowledge in some advanced computer applications which are necessary for the construction of instructional materials. The self-assessment revealed that they are knowledgeable in ICT skills, but they do not know how to use it in complex applications. The skills for development based on the training needs assessment reiterated a combination of skills which further clarified that not all skills under a certain application are known. It is then recommended that training needs assessment should always be conducted by school administrators to gather data on the actual needs of the teachers as a basis in planning a thorough training matrix to ensure that the development and training provided are based on the needs of the teachers.

Conceptual model of Life Cycle Assessment based generic computer tool towards Eco-Design in manufacturing sector

Abstract Even though life cycle assessments (LCA) provide a complete environmental performance analysis and guide to eco-designs, complexities have slowed down the distribution of LCA methodology in manufacturing sector. Even though bottom level advanced LCA computer applications like SimaPro and Gabi are available, it has not become popular in industry. A comprehensive research work is needed to develop life cycle inventory (LCI) under complexities such as data collection, scenario identification, allocation, aggregation and data quality measurements. During life cycle impact assessment (LCIA) with advanced LCA software, the linking of international databases makes severe challenges such as clear identification of secondary life cycles, selection of appropriate datasets and dataset modifications. An analytical interpretation of impact categories can be used to identify environmental hotspots and provide eco-design capabilities. This conceptual computer model is proposed to overcome the long barrier between raw data feeding and eco-design assistance. A strong LCA based, industry specific, Industrially Generic, eco-design guided, user friendly and real time DSS tool motivates industrialists to move towards sustainable manufacturing.

Advanced computer science and applications for soft computing of converged IT environments

Advanced computer science and applications for soft computing of converged IT environments

Boosting Advanced Computational Applications and Resources in Latin America through Collaboration and Sharing

Although computing research and facilities in Latin America have been developing steadily, a remarkable gap nevertheless remains in the availability of resources and specialized human resources compared to other regions. RICAP (Red Iberoamericana de Computacion de Altas Prestaciones, or Ibero-American Network for High-Performance Computing) aims to fill this gap by means of a strategic and advanced computational infrastructure that includes both high-performance and high-throughput computing platforms. This network will also develop software tools to facilitate this infrastructures accessibility and computational efficiency to encourage use by the Latin American computing community as well as focus on strengthening and training human resources in both parallel programming techniques and large-scale computing platform operations.

Wavelet/PSO-Based Segmentation and Marker-Less Tracking of the Gallbladder in Monocular Calibration-free Laparoscopic Cholecystectomy

This paper presents an automatic segmentation and monocular marker-less tracking method of the gallbladder in minimally invasive laparoscopic cholecystectomy intervention that can be used for the construction of an adaptive calibrationfree medical augmented reality system. In particular, the proposed method consists of three steps, namely, a segmentation of 2D laparoscopic images using a combination of photometric population-based statistical approach and edge detection techniques, a PSO-based detection of the targeted anatomical structure (the gallbladder) and, finally, the 3D model waveletbased multi-resolution analysis and adaptive 2D/3D registration. The proposed population-based statistical segmentation approach of 2D laparoscopic images differs from classical approaches (histogram thresholding), in that we consider anatomical structures and surgical instruments in terms of distributions of RGB color triples. This allows an efficient handling, superior robustness and to readily integrate current intervention information. The result of this step consists in a set of point clouds with a loosely gradient information that can cover various anatomical structures. In order to enhance both sensitivity and specificity, the detection of the targeted structure (the gallbladder) is based on a modified PSO (particles swarm optimization) scheme which maximizes both internal features density and the divergence with neighboring structures such as, the liver. Finally, a multi-particles based representation of the targeted structure is constructed, thanks to a proposed wavelet-based multi-resolution analysis of the 3D model of the targeted structure which is registered adaptively with the 2D particles generated during the previous step. Results are shown on both synthetic and real data. © 2018, (IJACSA) International Journal of Advanced Computer Science and Applications.

Integrating technological solutions to identify the potential locations for rainwater harvesting interventions in ICAR-IIHR farm at Hesaraghatta, Bengaluru

Water constitutes the prime requirement for existence and sustenance of all life forms. It is also the most vital component for enabling economic and social development. The quantum of rainfall and surface water availability have remained constant leading to overexploitation of ground water, declining water table levels and deterioration of water quality. ICAR-Indian Institute of Horticultural Research, Hesaraghatta, Bengaluru is wholly dependent on rains and borewell water for irrigation of experimental plots and laboratory needs apart from demand from other utilities and residential colony. There is water shortage because of reduced output from borewells, change in rainfall pattern, and, the dried up Aivarakhandapura lake. This resource scarcity has to be balanced critically with increasing water demand due to enhancement of cultivated land, more experimental activities, construction of new buildings and additional environment controlled polyhouses/ greenhouses. Devising practical solutions for management of scarce water resource is a big challenge. This paper focuses on Water Conservation and Water Balance in farm area of ICAR - IIHR (in Arkavathy basin near Hesaraghatta) with morphological and hydro-geological analyses to understand the in-situ percolation / infiltration and runoff characteristics taking into account the topographical features of the area. The study also covers the application of Penman-Monteith equation standardized by the Food and Agricultural Organization (FAO56-PM) simultaneously with crop coefficient approach (single crop coefficient) for estimation of values of reference evapotranspiration (ETo) and crop evapotranspiration under standard conditions (ETc). A series of systematic, logical and scientific steps are adopted to arrive at validated conclusions. This paper presents the data collected from various sources and tests which are compiled and collated using advanced computer applications like AutoCAD, Arc GIS, MS Excel and Adobe Photoshop. The results obtained from these applications are used to analyze and arrive at potential locations for engineering interventions in the farm area for effective and efficient harvesting of rainwater leading to conservation and ground water recharge.

Special Issue on Advanced Computational Methods, Systems, and Industrial Engineering Applications

Special Issue on Advanced Computational Methods, Systems, and Industrial Engineering Applications

Creating a database from "scratch"

The Smarter Solutions case study was written for an advanced computer applications course for students majoring in computer information systems and business administration. It involves developing a...

Advanced Computer Technologies and Applications in Grid and Cloud Computing

Advanced Computer Technologies and Applications in Grid and Cloud Computing