International Journal of Engineering and Manufacturing @ijem
Journal articles - International Journal of Engineering and Manufacturing
All articles: 623
Scientific article
EDM is a non-contact machining process widely used for shaping electro-conductive materials regardless of their hardness. In EDM material removal takes place by a series of recurring electrical sparks between the tool electrode and workpiece. In this study the effect of variation of discharge current on various machining parameters including Metal removal rate (MRR), Tool removal rate (TRR) and Surface roughness has been considered. A total of 32 experiments were conducted on four different workpieces i.e. Die Steel-D3, En-8, En-19 and Stainless steel (SS-AISI-440C) with the help of Copper and Aluminium electrodes. In this study Die-Sinking EDM has been employed and the results are shown with the help of graphs.
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Scientific article
The most important equipment utilized by power systems are transformers, which are passive electrical devices suitable for the transfer of electrical energy from one circuit to another which is associated with Electromagnetic (EM) induction. These equipment are important to help maintain network stability and reliability but despite these advantages, they still exhibit problems due to numerous factors such as overloading, poor dielectric strength, bad insulation, thermal degradation which in turn cause abrupt power outages or results in a major electrical system failure. Unfortunately, transformer users are having difficulty keeping an eye on how distribution transformers (DT) are performing when they are being used which contributes to outages. This paper focused on the performance analysis of a DT and the approach which helps to mitigate the difficulties of identifying load imbalance or overloaded DT to provide long-lasting and trouble-free services for power consumers, using Mansard place 1000 KVA, 11/0.415 KV Distribution Transformer (DT) as a case study to obtain the on-load parameters. The (Fluke 435 series II) Power Quality and Energy Analyzer (PQEA) was the equipment utilized to ascertain the reliability measurements of the DT and the experimental method was carried out on the second terminal connection as regards to IS 1180 standard.
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Analysis on Financial Policy of Enterprise and Sustainable Growth
Scientific article
Excessive growth will constrain enterprise resources, including intelligence, material, and money and so on. The slow growth rate will waste the precious financial resources of enterprise. The average rate of profit will be lower than that of social resources. When the actual sales growth rate is inconsistent with the sustainable growth rate, enterprise should lay emphasis on growth management and adopt appropriate financial policies to keep them consistent. This article analyzes the sales growth from financial perspective and uses financial index to estimate so as to avoid the problems caused by unfavorable growth and eventually to achieve the goal of sustainable growth.
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Analysis on Image Enhancement Techniques
Scientific article
Image Enhancement is crucial phase of particular application. These enhancement techniques become essential when there is every possibility of image degradation due to uncontrolled variations. These variations are categorized into light, emotion, noise, pose, blur and corruption. The enhanced images provide better images from which feature extraction is performed more effectively. Therefore the two major objectives of the proposed work are aligned in two phases. First phase of this paper discuss about Image Enhancement Techniques (IET) for improving image intensity. Second phase provide detailed elaboration of various Full Reference Based Image Quality Measures (FRBIQM). FRBIQM is further categorized into Pixel Difference Based Image Quality Measures (PDBIQM), Edge Based Image Quality Measures (EBIQM) and Corner Based Image Quality Measures (CBIQM). First image quality measure employs different techniques to evaluate performance between original and distorted image. Second image quality measure deploy edge detection techniques, which are essential for increasing the robustness (in feature extraction) and third image quality measure discuss corner based detection techniques, which are essential for enhancing robustness (in feature extraction). All these techniques are discussed with their examples. This paper provide brief survey of IET and FRBIQM. The significance and the value of the proposed work is to select the best image enhancement techniques and image quality measures among all (described ones) for features extraction. The one which gives the best results will be used for feature extraction.
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Anchor-Free Yolov8 for Robust Underwater Debris Detection and Classification
Scientific article
Deep-sea debris poses a significant threat to marine life and human health. Traditional methods for underwater debris detection and classification are labour-intensive and inefficient. The major challenge for using vision robots or autonomous underwater vehicles(AUVs) to remove deep sea debris is to exactly identify the marine debris. Marine debris gets deformed, eroded, and blocked due to seawater. Marine debris changes its shape, size, and texture in sea environment. Sea environment is challenging for the task of debris detection because of weak light. Uncertainty about the task of debris detection is due to marine life, rocks, marine flora, fauna, algae, etc. This study aims to develop a robust deep learning model for underwater debris detection and classification using YOLOV8. We evaluate the performance of YOLOV8 against YOLOV3 and YOLOV5 on the JAMSTEC TrashCan dataset. By employing an anchor-free detection head, YOLOV8 demonstrates improved accuracy in detecting underwater debris of varying shapes, sizes, and textures. Here, we show that YOLOV8 achieves a mean Average Precision (mAP) of 0.5095, outperforming YOLOV3 (mAP: 0.31879) and YOLOV5 (mAP: 0.43608). Our findings underscore the potential of anchor-free YOLOV8 in addressing the challenges of underwater debris detection, which is crucial for marine conservation efforts.
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Angle measurement on a flat surface using high frequency ultrasonic pulse
Scientific article
Ultrasonic waves are most commonly used to measure the presence of an object and its distance from the source using time of flight concept. These are pulses of sound waves that have frequency range higher than the human hearing range. In this paper, we will discuss the measurement of the tilt angle of a robot with respect to a flat base using ultrasonic waves and time of flight concept [2]. An Arduino platform was used with Atmel328P as the processing microcontroller chipset which will then compute the angle of tilt using the distance calculated from an ultrasonic sound transmitter and a receiver using coordinate geometry and trigonometric functions. A combination of gyroscope and accelerometer is also used to find the true tilt angle of the apparatus and then it is compared with the angle readings obtained from the ultrasonic sensor system. A high response time and low delay is necessary for instantaneous angle measurement. Hence, gyroscope-based angles have been used as a reference to adjust filter parameters to decrease error and noise at every iteration.
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Animation of magnetically levitated shoes and its optical flow with computer vision
Scientific article
The article presents a concept of computer-aided design and three-dimensional (3D) computer animation of a newly proposed magnetically levitation based shoes where the users can move in the air. The aerial movement would be in the direction of a magnetic track which is laid down below the trajectory and the users have to wear the maglev shoes. They can move from ground floor to upper floors as in the case of an elevator. The users have been provided adequate control over the speed of movement and they can stop and run the system by themselves at any instant of time by self-controlling of the motion generated by them. The maglev shoes are proposed to be built with superconducting materials to levitate above the magnetic tracks. Computer vision features are efficiently utilized to detect various features of the animated image frame of maglev shoes and the motion study of the proposed system. Statistical methods with existing functions are used to analyze various features like speed, angles and finding the optical flow in both horizontal and vertical direction of maglev shoe wearers.
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Anomaly Detection in Crowd Video Using Different Versions of YOLOv8
Scientific article
This paper focuses on real-time anomaly detection in surveillance video using YOLOv8, the latest in the YOLO object detection series, integrated with spatio-temporal analysis. The system aims to detect abnormal behavior in crowded environments by combining spatial object detection with temporal activity analysis. YOLOv8 is used to detect and track individuals in video frames, while a 3D Convolutional Neural Network (3D CNN) processes sequences of frames to identify behavioral anomalies based on movement patterns. Three variants of YOLOv8—Nano (n), Small (s), and Medium (m)—are evaluated for performance trade-offs in accuracy, processing speed (FPS), and latency. Results show YOLOv8n offers the best real-time performance, while YOLOv8m provides higher accuracy at the cost of increased latency. The system uses the UCF-Crime dataset for training and testing, and metrics such as accuracy, FPS, and latency are used for evaluation. The modular pipeline supports scalability and real-time deployment, with visual outputs aiding interpretation. By integrating object detection with spatio-temporal modelling, the system effectively identifies anomalies such as loitering or sudden movements. Future work includes refining detection accuracy using labelled anomalies and exploring advanced models like Transformers for improved temporal understanding. The significance of this research lies in its ability to combine lightweight real-time object detection with effective temporal behavior modeling within a scalable and modular architecture. The proposed framework contributes to the advancement of intelligent surveillance systems by improving anomaly detection reliability while maintaining computational efficiency suitable for deployment in smart cities, public safety monitoring, and edge-based surveillance applications.
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Any touch: design and implementation of a touch interface for bluetooth enabled personal devices
Scientific article
Human Computer Interactions has been a matter of great consideration for engineers, researchers, designers and industrial experts from decades. Every device, be it a smart phone, personal computer, ATM machines, etc. comes with a user interface for a layman to understand and to use the device. With the advancing technology, different modes of user interface are proposed. The most common of all is a touch interface. Most of the interactive devices now come with a touch interface. This paper presents an approach to provide a similar external touch interface for laptops and computers that further can modify for much smaller devices such as mobile phones.
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Application of AC Algorithm Based on RS in Stock Index Prediction
Scientific article
The AC Algorithm may easily get a lower pattern similarity when performing the AC under the situation of encountering multi-dimensional data, so this will affect the selection of similar patterns. Combining the Rough Set theory, the author makes the data dimension reduction processing. The experiment shows that the AC algorithm based on RS is practical and its performance efficiency and prediction accuracy are much higher than the AC algorithm.
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Scientific article
Soil mechanics problems deal with various types of soil that exhibit erratic behaviour in the real world, one such soil being the expansive soil where it takes a lot of laboratory test procedures to ascertain the physical properties of this soil. Modeling the behaviour of the expansive soil is complex and sometimes beyond the aptitude of most traditional procedures of physically-based engineering approaches. Artificial neural networks (ANN) are the ones used for predicting the complex nature of the soil since it has shown superior predictive potential as compared to the conventional approaches. This review aims to deliver and discuss the numerous applications of artificial neural network technique accomplished by various researchers in the field of geotechnical engineering to predict several properties of the expansive soil such as free swell index, unconfined compressive strength, shear strength of the soil, swelling pressure and swell percent, compaction characteristics, and plasticity index. This paper will assist practising engineers in determining the best modelling approaches and formulating the necessary data for using the ANN technique to solve soil mechanics problems.
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Application of Fuzzy Logic in Automated Lighting System in a University: A Case Study
Scientific article
Applications based on Fuzzy logic use mathematical reasoning to find the solution to the minutest possible fuzzy set that can range anywhere between 0 and 1. In this study, the practical implementation of a fuzzy logic controller for automated lighting was presented as a real case of an Indian university to detect the occupancy in the classroom and maintain the luminance level by sensing the daylight in the room. The result of the experiment indicates that the fuzzy logic control method could reduce wasted hours of lighting in unoccupied classrooms.
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Scientific article
The particle swarm optimization (PSO) algorithm is a stochastic global optimization technique based on swarm intelligence. It possesses advantages such as being a simple principle, few parameters and easy to be realized. In this paper, an optimization model is established to solve the difficulty in selecting parameters and improve the simulation accuracy of the biodegradable medical polymer degradation model. When modeling, the particle swarm optimization (PSO) algorithm is proposed to solve the model and calculate undetermined parameters of the biodegradable medical polymer degradation equations. A comparative analysis of the calculation results is progressed. It shows that parameters determined by optimization model make the simulation results of degradation model more close to the experiment results. Using this method to solve the model is more accurate and efficiency than determining parameters artificially. It also shows that the particle swarm optimization algorithm used to optimize parameters have practical significance and application value.
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Application of Python in Evaluating the Volume of 3D Shapes Using Monte Carlo Simulation
Scientific article
Volume estimation of three-dimensional (3D) objects is fundamental in various scientific and engineering fields. While analytical expressions exist for the simple geometric shapes, they become impractical for complex or irregular structures. Monte Carlo simulation is a statistical method which is based on the random sampling, which offers an efficient numerical alternative. This research explores the application of Monte Carlo integration method for the estimation of the volumes of three different 3D objects viz. sphere, cylinder, and cone. The paper elaborates on the mathematical background of the simulation by presenting detailed Python implementations, and analyzes the accuracy, convergence rates, and computational efficiency of the method. The study concludes that the simulation, despite their probabilistic nature, provide an effective and scalable technique for volume estimation, particularly for the shapes without closed-form volume expressions.
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Applying Motion Capture in Computer Animation Education
Scientific article
This paper introduces the motion capture technology and its use in computer animation education. Motion capture is a powerful aid in the course of computer animation and a supplement to the traditional key-frame animation. We use professional cameras to record the motion of the actor and then manipulate the data in software to eliminate some occlusion and confusion errors. For data that is still not satisfying, using data filter to smooth the motion to cut some awry frames. Then we import the captured data into Motionbuilder to adjust the motion and preview the real-time animation. At last in Maya we combine the motion data and character model, let the character perform the captured data and add the scene model and music to export the whole animation. In the course of computer animation, we use this method to design the animation of military boxing, basketball playing and folk dancing.
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Artifacts Removal of EEG Signals By the Application of ICA and Double Density DWT Algorithm
Scientific article
Independent Component Analysis is used for the automation and detection of brain artifacts. The Independent Component Analysis (ICA) here is used for the segmentation of artifact peaks in the signal. Then the Discrete Wavelet Transform is applied for multi-level transfer of signal data until the reception of significant result. We have extended our search and applied the Double Density Algorithm for the multi-level transfer. The results obtained were analyzed from the data set of EEG signals taken with a outsource reference. Since the method is parameter free implementations in clinical settings are imaginable.
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Scientific article
This study proposes an optimized Multi-Histogram Equalization (OMHE) technique for contrast enhancement while preserving the brightness of an input image. The objective of this study is to improve the visual interpretability or perception of information among color images. In this technique, input image histogram is partitioned into multiple sub-histograms and then classical histogram equalization process is applied to each one. Values of t threshold points for dividing the image histogram into t+1 sub-histograms are optimized using Artificial Bee Colony, a swarm intelligence-based optimization algorithm. A new fitness function for evaluating the contrast of enhanced image is proposed here that will guide the Artificial Bee colony algorithm into finding the optimal threshold values. AMBE (Absolute Mean Brightness Error), PSNR (Peak signal to noise ratio), SSIM (Structural Similarity Index) and Entropy are computed for quantitative analysis of the performance of the proposed method with existing methods. Comparisons show that proposed method performs better than other present approaches by enhancing the contrast well while preserving the brightness of the input image.
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Artificial neural networks based approach for predicting LVDT output characteristics
Scientific article
This paper presents a novel approach for training and output prediction of data of a Linear variable differential transformer (LVDT). LVDT is a commonly used device used in laboratories for measuring linear displacements in specific situations. This article considers application of Artificial Neural Networks (ANNs) for learning and output estimation of LVDT. Real-time experiments were conducted and results were collected for training of ANNs. The Regression results and outputs verified the learning and prediction capability of ANNs.
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Scientific article
To improve surveillance, the proposed patrolling security system employs autonomous mobile robots outfitted with low-cost night vision cameras. Regular patrols, which are essential for discouraging criminal behavior, are typically conducted by security or law enforcement officers with the use of pricey CCTV equipment. The goal of using autonomous robots is to save expenses while enhancing the quality of patrols in particular regions. Using a night vision camera, the late-night guarding robot detects human movement within its assigned zone while following a random path. Its obstacle-detecting sensors help to prevent crashes and guarantee secure navigation. The robot records incidences, takes pictures with its mounted camera, and carefully scans regions for probable incursions. It then sends the data to the user as quickly as it can. This project's primary goal is to draw attention to suspicious activity in hidden areas.
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Scientific article
The determination of strength properties i.e compressive strength, flexural strength and splitting tensile strength is essential to estimate the load at which the concrete members may crack especially in aggressive environment. The paper reports an experimental investigation on deterioration of used engine oil (UEO) soaked flyash concrete with respect to its strength properties and effective automation of classification of data sets returned by the SEM test on the same set of samples. In the former part, concrete cube ,beam and cylinder specimens with fly ash admixture as partial replacement of cement by 0%, 5%, 10%, 15%, 20%, 25%, 30%, 35% and 40% were subjected to water curing and then to UEO soaking. Gradual decrease in the strength properties of concrete specimens with respect to time was observed. An attempt has been made to study the permeation properties like soroptivity with the addition of fly ash in concrete. The SEM analysis of test results was in good agreement to this. An attempt was made to automate this analysis phase using correlation coefficient and Support Vector Machines (SVM). It was found that the latter achieved better results in terms of performance.
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