Engineering Commons^™

Point Cloud Registration Method Based On Improved Grey Wolf Algorithm And Adaptive Splitting Kd-Tree, Yuanhao Du, Xiuli Geng, Chengzhi Xu, Yinhua Liu

Journal of System Simulation

Abstract: Traditional GWO algorithms suffer from limitations such as insufficient search efficiency and susceptibility to local optima. A novel method for the registration of point clouds of complex industrial components is proposed based on an improved GWO algorithm and ICP. To address the problem of uneven population distribution caused by random initialization in GWO, chaotic mapping is employed to initialize the gray wolf population, ensuring a more uniform distribution of individuals within the search space. A non-linear control parameter strategy is introduced to strike a balance between the algorithm's local search and global search capabilities. Elite reverse learning is integrated …

Gaussian Chaotic Fire Hawk Optimization Algorithm For Solving Dynamic Optimization Problems, Yongzhang Chen, Yuanbin Mo

Journal of System Simulation

Abstract: There are many important chemical processes in the chemical industry rely on dynamic optimization with factors such as nonlinearity and discontinuity. In order to find a more efficient solution algorithm, Gaussian Chaotic fire hawk optimization algorithm is proposed based on the fire hawk optimization algorithm, which is used to solve such problems after parameterizing the control variables. The original way of initializing the populations is replaced using tent chaotic mapping in order to make more sense of the initial distribution of the algorithm; a more targeted update method has been proposed in the analysis of fire hawk location updates …

Coordinated And Optimal Dispatching For Wind-Photovoltaic-Storage Systems Based On Multi-Strategy Multi-Objective Differential Evolution Algorithm, Xuyang Ren, Xuhui Bu, Yanling Yin, Jinghua Liu

Journal of System Simulation

Abstract: The introduction of new energy generation units makes the power system structure more and more complex, and the existing economic dispatching methods face many challenges. A coordinated and optimal dispatching for wind-photovoltaic-storage systems is constructed and a constraint handling method is given, a competitive mechanism-based multi-strategy multi-objective differential evolutionary (CMMODE) algorithm is proposed. The CMMODE algorithm utilizes a competitive mechanism to partition the population and constructs multiple differential variance operators based on the partitioning results, thus generating a multi-strategy scheme, employs an elite self-exploration mechanism to make the population have the ability to jump out of the local optimum …

Research On Rule-Based Energy Management Strategy Of Hybrid Mining Dump Truck, Jiangong Liu, Yuanhui Zhang, Fei Wei, Yiying Wang, Xiaoling Li, Peiqing Liu, Fengmiao Si

Journal of System Simulation

Abstract: A distributed hybrid powertrain system structure and a rule-based energy management strategy are proposed to address the problems of insufficient power and poor fuel economy in conventional dieselpowered mining dump trucks. By analyzing the operational characteristics of mining dump trucks, a distributed hybrid powertrain system structure and vehicle driving conditions are established, relevant mode-switching rules are formulated. The results demonstrate that the proposed distributed hybrid powertrain system structure enhances the climbing capability of the vehicle by 27% when using the third gear for uphill driving. In addition, the adoption of the rule-based energy management strategy results in an 19% …

Construction Of A Digital Twin-Based Ship Manufacturing Workshop Monitoring System, Tianxiang Hu, Hui Ye, Xiaofei Yang

Journal of System Simulation

Abstract: In order to address issues of opacity in production information and difficulties in collecting equipment data in shipbuilding workshops, a digital twin ship manufacturing workshop monitoring system is designed based on the Unity physics platform. The essential steps in building a virtual reality platform are outlined, encompassing the creation of a virtual ship workshop, the development of data transmission methods for multi-source heterogeneous data acquisition, implementation of data-driven methods for achieving virtual-real synchronization, and enhancement of data visualization capabilities. By practically designing a real-time monitoring system for the welding assembly line production process in shipbuilding, the 3D scene reproduction …

Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave

Journal of System Simulation

Abstract: In order to improve the existing small target detection methods, which suffer from low detection accuracy, high false detection rate and high leakage rate, the FSD-YOLOv5 algorithm is proposed, which has three improvements based on the YOLOv5 algorithm. The Focal EIoU is used instead of the original CIoU to improve the model convergence speed and regression accuracy. To cope with the deficiencies in CNN architecture, we adopt a new CNN building block called SPD-Conv is adopted. To address the problem of the reduced or lost information of small objects in feature maps caused by downsampling in convolutional neural networks, …

Leveraging Network Science For Customer Segmentation And Product Recommendation, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

The rapid growth in e-commerce has forced the development and implementation of enhanced customer segmentation and recommendation systems, improving business results and improving customer experience. Traditional approaches, such as RFM analysis and clustering algorithms like K-means, are very helpful in many situations but usually fail to catch complex interdependencies among customers and products. This paper proposes a new approach using network science methodologies, a bipartite graph model, toward the advancement of customer segmentation and product recommendation. It implements a bipartite graph of customers and products using the "Online Retail II" dataset and proceeds with community detection, segmenting customers into unique …

Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo

Al-Bahir

Forecasting volatility in financial time series remains challenging due to their asymmetric nature and excess kurtosis. This study evaluates and compares the performance of four variant of GARCH models incorporating skewed non-Gaussian error innovation distribution. The performances of these GARCH family of models under the skewed error innovation distributions were evaluated for three different unique data sets to have a more robust assessment of the performance of these skewed error innovation distributions. This study leverage on daily closing prices of Bitcoin, Naira to Dollar Exchange rates and daily Nigeria All Share Index between January 1, 2015 and January 26, 2024. …

Retracted: Deep Learning-Based Beamforming Optimization For Reconfigurable Intelligent Surface-Assisted Wireless Communication Systems, Mohammed Firas Jassim, Alhamzah Taher Mohammed, Osamah Abdullah

Iraqi Journal for Computer Science and Mathematics

This research investigates how deep learning might be used to optimize beamforming in wireless communication systems that are helped by Reconfigurable Intelligent Surfaces (RIS). Our goal is to increase the possible data rates by dynamically forecasting the best phase shifts for RIS elements by utilizing Convolutional Neural Networks (CNN) and hybrid CNN-Long Short-Term Memory (CNN-LSTM) models. We assess the performance of these deep learning models against conventional genie-aided techniques by simulating real-world wireless settings using the DeepMIMO dataset. The findings demonstrate that beamforming based on deep learning can reach near-optimal performance, greatly lowering the overhead associated with channel estimation while …

The Permutation Annihilator Ideals In Commutative Permutation Bck–Algebras With Their Applications, Shuker Khalil, Ali Abbas Asmae

Iraqi Journal for Computer Science and Mathematics

This paper introduces new concepts such as permutation BCK--algebra, permutation involutory ideal, commutative permutation BCK--algebra, and prime permutation ideal. Additionally, their attributes are examined. This paper elucidates a method for determining a relationship between the chemical structure of atoms for the chemical element Cadmium, and some of our suggestions are given here. In this work, the structure of the sets 𝒜 and λ_n^β∗𝒜 are defined. Next, we show that if 𝒜 is a permutation ideal, then λ_n^β∗𝒜 is a permutation ideal that contains 𝒜. Also, in any commutative permutation BCK--algebra the …

Integrating Fuzzy Set Theory With Association Rule Mining For Advanced E-Commerce Recommendations, Hind Raad Ibraheem, Murtadha Mohammed Hamad

Iraqi Journal for Computer Science and Mathematics

The dynamic nature of e-commerce necessitates the adoption of cutting-edge technologies to improve the online shopping experience. Our research introduces a groundbreaking methodology called Fuzzy Association Rule Mining (FARM), combining fuzzy set theory with traditional Association Rule Mining (ARM). Unlike conventional ARM, which focuses solely on the frequency of jointly purchased items, FARM also considers the sold quantities, leveraging the Apriori algorithm to discern customer preferences from historical sales data across the UCI Online Retail II, Market Basket, and Movielens datasets. This hybrid of fuzzy set theory with ARM enables a better understanding of complicated consumer behaviors and associations between …

Liu-Type Estimator In Inverse Gaussian Regression Model Based On (R-(K-D)) Class Estimator, Zeina Ameer Hadied, Oday Esam Al-Saqal, Zakariya Yahya Algamal

Iraqi Journal for Computer Science and Mathematics

When multicollinearity arises in the inverse Gaussian regression (IGR), there is a substantially unstable variance in the maximum likelihood estimator. Based on the (r-(k-d)) class estimation method, we present a novel Liu-type estimator in the IGR model in this study. The study examines the e ectiveness of the suggested estimator and draws comparisons with alternative estimators. Based on simulation and real data results, the suggested estimate performs better than the other estimators in terms of mean squared error.

The Efficacy Of Utilizing Artificial Intelligence Techniques In Developing Critical Thinking In Mathematics Among Secondary School Students And Their Attitudes Toward It, Mohammad A. Tashtoush, Aida B. Qasimi, Nawal H. Shirawia, Lubna A. Hussein

Iraqi Journal for Computer Science and Mathematics

The aim of this study is to investigate the efficacy of Artificial Intelligence (AI) techniques and programs in developing Critical Thinking Skills (CTSs) in mathematics among secondary school students, as well as their attitudes towards it. This study employed an experimental methodology, which was applied to a sample of 91 students. A critical thinking test and a scale to measure students' Attitudes Towards Mathematics (ATM) were also utilized. This study revealed significant improvements in the mean scores of critical thinking skills among secondary students who were exposed to Artificial Intelligence Techniques (AITs), particularly in deduction, interpretation, inference, and evaluation. Additionally, …

Integrating Neural Networks For Predictive Torque Control And Obstacle Avoidance In Autonomous Robot, Viswanath Kodali, Harsha Vardhan Borra, Kiran P

Northeast Journal of Complex Systems (NEJCS)

In the field of robotics, precise motion control and accurate computation of joint forces are critical for ensuring optimal performance. Traditional methods, such as using the Jacobian matrix for joint angle determination and Euler-Lagrange equations for torque computation, are reliable but computationally intensive, making them less suitable for real-time applications. This paper presents an advanced approach to improving the productivity and efficiency of a 3-Degree of Freedom (DOF) robotic arm by utilizing Artificial Neural Network (ANN). The proposed system dynamically predicts joint angles and torque, enabling faster and more efficient motion control.

To address the challenge of obstacle avoidance in …

Grnn-Fa Hybrid Model For Predicting The Useful Life Of Dump Truck Tyres, Festus Kunkyin-Saadaari, Alfred Kesseh, Victor Kwaku Agadzie

Journal of Sustainable Mining

The useful life of dump truck tyres is crucial for optimising economic efficiency and safety in mining operations. This study employs advanced hybrid models, including a generalised regression neural network (GRNN) combined with an artificial bee colony (ABC), ant colony optimisation (ACO), and firefly algorithm (FA), to predict tyre life at Perseus Mining Ghana Limited to enhance prediction accuracy. Sensitivity analysis using simple linear regression (SLR) identified tread depth as the most influential factor, with a correlation coefficient of 0.9638. Among the models, GRNN-FA demonstrated superior performance, achieving the highest correlation coefficient (r = 0.9586) and lowest mean squared error …

Email Spam Classification Based On Deep Learning Methods: A Review, Ekramul Haque Tusher, Mohd Arfian Ismail, Anis Farihan Mat Raffei

Iraqi Journal for Computer Science and Mathematics

Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. This review aims to identify the various deep learning techniques used for email spam, their effectiveness, and areas for future research. By synthesizing the outcomes …

Research Of Horse Oil Based Shampoo For Fine Hair Involving Local Oils And Enzyms Transesterification, Sherzod Y. Rakhmanov, Madina O. Khaydarova, Bonu G. Аrislonboyeva, Nilufar A. Khaydarova, Dilshod P. Rakhimov

CHEMISTRY AND CHEMICAL ENGINEERING

Currently, there are many shampoos, balms and various hair masks. Shampoo-tonics have also been introduced into production, providing temporary coloring without damaging the hair structure. In this research work, we set ourselves the task of conducting a study of a shampoo for soft hair that provides durability, granularity and shine to hair by transesterifying horse oil with the enzyme lipase and the surfactant sodium lauryl sulfate. Depending on the type of shampoo, we conducted a scientific study using the following experimental method. To add horse oil to the shampoo formula, we re-esterified mixtures of horse oil and sunflower oil in …

Effect Of Desorption On Photocatalytic Decomposition Of Methylene Blue Using Materials From Solid Wastes Of Production Of Molybdenum Oxides (Vi) And Titanium Dioxide, Dilshoda R. Tursunova, Shahlo Sh. Daminova, Rafael A. Nusretov, Ayipbergen Shiknazarov, Zuhra Ch. Kadirova

CHEMISTRY AND CHEMICAL ENGINEERING

The aim of the work is to obtain and characterize a composite photocatalyst based on the spent catalyst of the Shurtan Mining and Chemical Combine based on titanium dioxide and molybdenum-containing waste of the Almalyk Mining and Metallurgical Combine and to identify factors influencing the process of photocatalytic decomposition of methylene blue in solution under the action of UV light. In this work, we studied the kinetics of photocatalytic decomposition of methylene blue on the surface of materials obtained from technogenic solid waste, which were thermally activated at a temperature of 600 ° C. It was found that desorption plays …

X-Ray Photoelectron Spectroscopy Investigation Of Surface Changes In Chalcocite And Enargite Minerals Following Oxidation Treatment, Berdakh T. Daniyarov, Miki Hajime, Baxtigul Y. Ruzieva, Shahlo Sh. Daminova

CHEMISTRY AND CHEMICAL ENGINEERING

Copper sulfide minerals, such as chalcocite (Cu₂S) and enargite (Cu₃AsS₄), are important sources of copper, which has wide applications in electronics, energy, and other industries. These minerals are traditionally processed using flotation methods, which are one of the most effective ways to extract copper from sulfide ores. However, the success of flotation of copper sulfides, such as chalcocite and enargite, strongly depends on changes in their surface properties, such as hydrophobicity or hydrophilicity, which can be modified by various chemical reagents. To further understand the impact of these chemical reagents on chalcocite and enargite minerals, X-ray photoelectron spectroscopy (XPS) was …

Synthesis And Study Of Complex Compounds With 1,3,4-Oxadiazole Derivatives Based On Ammonium Vanadate, Mehribon A. Pirimova, Shaxnoza A. Kadirova, Abduhakim A. Ziyayev

CHEMISTRY AND CHEMICAL ENGINEERING

This research work examines the synthesis, structure and properties of ammonium vanadate complex compounds based on 1,3,4-oxadiazole derivatives. Competing donor centers in coordination, electronic and geometric structures of the ligand molecule were studied based on quantum chemical calculations using the Gaussian09 LanL2DZ software package. Among the ligands, 2-carboxymethylthio-5-phenyl-1,3,4-oxadiazole ligand has been shown to have more competitive donor atoms than other ligands.

Structural Features And Morphology Of Biodegradable Composites Based On Polylactide And Corn Starch, Eygeniy N. Poddenezhny, Andrei A. Boiko, Ekaterina E. Trusova, Viktor M. Shapovalov

CHEMISTRY AND CHEMICAL ENGINEERING

The aim of the work was to study the morphology and structural features of biodegradable composites based on polylactide, filled with corn starch formed by extrusion method. The characteristics of the obtained materials were investigated by scanning electron microscopy, X-ray diffraction, IR spectroscopy. It was established that the presence of polyethylene glycol PEG–4000 as a plasticizer and surfactant – glycerin monostearate in the initial mixture leads to the formation of a nonporous heterogeneous system, in which starch particles are statistically distributed in the matrix. The starch concentration in the composite varied from 20 to 55 wt. %. When the starch …

Influence Of Thermal Cycling On The Resistance Of Bismuth Cuprates Synthesized Using Solar Energy, Dilbara Dj. Gulamova, Sirojiddin Z. Mirzaev, Sirojiddin Kh. Bobokulov, Elyor B. Eshonkulov, Grigor I. Mamniashvili

CHEMISTRY AND CHEMICAL ENGINEERING

A bulk superconducting ceramic synthesized using solar technology exhibits a sharp increase in resistance from zero to approximately 160Ω at 250 K. Four thermal cycling tests in the range of 79-360 K revealed a tendency for the temperature transition interval to narrow and a comparatively sharp jump at 290 K, suggesting a superconducting transition. The effect of stress concentration at grain boundaries during four cycles leads to an increase in the superconducting transition temperature due to the cumulative rise in stress and pinning force. The assumption that these effects are caused by superconducting homologous phases is based on the manifestation …

The Effect Of B2o3 On The Structure And Properties Of The Glasses Of The Na2o–Cao–Mgo–Sio2–P2o5 System, Mihail V. Dyadenko, Ivan A. Levitskiy, Irina I. Kurilo, Alexander S. Glinskii

CHEMISTRY AND CHEMICAL ENGINEERING

The purpose of this work was to study the effect of boron oxide on the physico-chemical and technological properties of glasses of the Na₂O–CaO–MgO–SiO₂–P₂O₅ system. The study of crystallization ability, density, the temperature of the onset of softening, as well as the chemical stability of experimental glasses modified with boron oxide, made it possible to indirectly assess their ability to dissolve in aqueous solutions and show bioactive properties. The article presents the results of the influence of B₂O₃ on the viscosity of the studied glasses and the value of their …

Research Of The Decomposition Process Of Unenriched Phosphate Raw Materials Of Central Kyzylkum With Nitric And Sulfuric Acids, Husan A. Zikirov, Ruslan Ch. Yorbobaev, Kholtura Ch. Mirzakulov

CHEMISTRY AND CHEMICAL ENGINEERING

The aim of the research is to establish the optimal technological parameters of the process of decomposition of unenriched phosphate raw materials of the Central Kyzylkum nitric and sulfuric acid for processing complex nitrogen-phosphorus fertilizers, to study the chemical composition, rheological properties. The coefficient of decomposition of unenriched phosphate raw materials, pH of acid pulp depending on various ratios and the total rate of nitric-sulfuric acid, as well as S:L of the environment are determined. The chemical and mineralogical composition of nitrosulphophosphate fertilizers formed after drying the ammoniated pulp are established.

Strength And Durability Characteristics Of Mortar Containing Fine Glass Powders As Partial Substitute Of Cement, Deepa Paul, Bindhu K.R, G. M. Sadiqul Islam, Bindhu K. R.

ASEAN Journal on Science and Technology for Development

A recent trend in construction involves the application of high-strength mortar which consumes a high quantity of cement. The present study aims at producing a sustainable mortar utilising waste glass powders (GP) as a partial substitute for cement in mortar. GP grains having different particle sizes in equal proportions were carried out in the mortar mix for improved packing. After realising the cementing properties of GP particles from the microanalyses like micron-size, silica-rich, reactive, and thermal resistance, mechanical and durability aspects of the mortar composite with manufactured sand as a fine aggregate were examined. The mechanical properties of the mortar …

Internet Of Things Devices Users’ Privacy Adherence: A Case Of Digital Ignorance, Akrasia Or Exhaustion?, Philip Bazanye, Walter F. Uys, Wallace Chigona

The African Journal of Information Systems

Internet of Things devices, such as those used in home automation, commercial and retail business, and smart cities, are vulnerable to attacks that affect all aspects of daily life. The upsurge in the use of IoT devices has increased the likelihood of cyber-attacks on end users. This research investigates the factors that influence IoT device users to adhere to privacy standards. This interpretivist exploratory research was guided by a three-phased approach. The interview questions were derived from the conceptual model and the constructs of Activity Theory, and themes were analyzed using deductive thematic analysis. The findings were elaborated with reference …

Retracted: A Review Of Breast Cancer Histological Image Classification: Challenges And Limitations, Israa Faisal Jassam, Abdulrahman Abbas Mukhlif, Ahmed Adil Nafea, Mustafa Adnan Tharthar, Ahmed Isam Khudhair

Iraqi Journal for Computer Science and Mathematics

This paper comprehensively reviews the classification of breast cancer histological images. The paper discusses the research objectives, methodologies used, and conclusions drawn, as well as suggestions for the future. The study is based on the ICIAR 2018 database, which is considered one of the largest databases available to support this research. The paper also addresses major challenges such as lack of data, variation in tissue preparation, class imbalance, and computational requirements. Advanced techniques such as deep learning (DL), transfer learning and data augmentation are explored, along with innovative models such as convolutional neural networks (CNNs) and generative adversarial networks (GANs). …

Evolution Of Lyrics Of Egyptian Songs In The 20th Century, Omar Abdelrafe

The Undergraduate Research Journal

Despite the extensive research by western countries on the song lyrics, almost nothing is known about the evolution of Egyptian song lyrics. The previous studies in the U.S. and U.K. revealed that lyrics were more pessimistic as time passed. In this study, 1891 Egyptian songs from 1920 to 2022 were analyzed using a sentiment analysis tool while searching for offensive words and retrieving their popularity scores from Spotify. The results aligned with those of the other regions in which the negativity of songs and the percentage of songs containing offensive words increased. However, there is a substantial increase in neutral …

A Review On Exploring Artificial Intelligence Applications, Advancements, Issues, And Future Challenges, Sajid Naeem, Novman Nabeel, Waseem Beg, Shujaat Ali, Rajiv N. Kanojiya, Satish S. Mandawade, Chetan R. Yewale, Sc Kulkarni, Vt Salunke, Av Patil

Polytechnic Journal

Artificial intelligence (AI) is a transformative technology with diverse applications that is transforming several industries. AI is the use of systems and technology to replicate human intelligence and solve common real-world issues. Machine learning (ML) and deep learning are AI technologies that use algorithms to more accurately predict occurrences without the need for human intervention. Explainable Artificial Intelligence (XAI) refers to AI that can explain decisions or forecasts to human users. XAI seeks to improve AI systems' transparency, trustworthiness, and accountability, particularly when utilized in high-risk applications such as healthcare, finance, or security. This review article provides a thorough overview …

Building Services Engineering January/February 2025

Building Services Engineering

No abstract provided.