International Journal of Engineering and Manufacturing @ijem
Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 532
Статья научная
This paper measured the impact of the implementation of the five core Industry 4.0 technologies (artificial intelligence, big data analytics, cloud computing, cybersecurity, and Internet of Things (IoT)) on organizational behavior and corporate culture of businesses and organizations in Pakistan. Moreover, the influence of organizational behavior and corporate culture on organizational effectiveness was also analyzed in this paper. The retail industry of Pakistan was chosen as the subject of this study, and a quantitative approach, which included a questionnaire based on a five-point Likert scale ranging from “strongly agree” to “strongly disagree,” was employed to gather the responses from participants, including both superiors and subordinates possessing the technological know-how of Industry 4.0. The findings indicated that the implementation of Industry 4.0 in Pakistan’s retail sector helps positively transform organizational behavior and aids in building a great corporate culture. Moreover, it was found that both positive organizational behavior and great corporate culture help in improving the overall organizational effectiveness. This study took an unprecedented step to research Industry 4.0 from an organizational perspective. Furthermore, the carried-out study extended the theoretical body of knowledge by studying and examining the five crucial factors of Industry 4.0 that contribute to the service sector, particularly the retail industry, of the big emerging markets (BEM) economies, including Pakistan.
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The Impact of Organizational Slack on The Performance of Pharmaceutical and Chemical Firms
Статья научная
The purpose of this paper is to attempt to reconcile previous views of the relationship between organizational slack and performance through examining the impact of organizational slack on the performance of pharmaceutical and chemical firms by using empirical analysis based on the data get from 47 firms in Henan Province. The result shows that the relationship between organizational slack and the performance of pharmaceutical and chemical firms is inverse N-shaped. The results broadly demonstrate that relationships differ based on industry circumstances and organizational slack. Additionally, this study is the first to empirically identify an inverse N-shaped relationship between slack and performance, indicating that, in certain industry circumstances, little and much slack is bad for performance. Overall, results highlight the importance of additional research into intervening factors impacting the slack–performance relationship.
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The Influence of Stage Structure and Prey Refuge on the Stability of the Predator-Prey Model
Статья научная
This paper aims to study the prey refuge impact on the dynamic behaviour of a stage structure predator-prey model. The model consists of four ecological species: prey in the protected and unprotected area and immature and mature predators. It assumes the grown predator can feeds only on the prey in an unreserved area. The conditions that guarantee the existence of the possible fixed points are found. Further, the local stability around all of the equilibria is considered. Then, using the Lyapunov direct method, the essential conditions for the global stability of the equilibria are adopted. Numerical simulations are illustrated to confirm our results. It concluded that the protected area positively affects the system's co-existence.
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The Multimedia Sentiment Model Based on Online Homestay Reviews
Статья научная
Aiming at the fact that traditional sentiment analysis is based on text, without considering the factors such as special symbols and emoticon images, which can’t fully extract the user's emotions, this paper proposes a sentiment analysis method of online homestay reviews based on image-text fusion. For text datasets, first use Word2vec to build a topic clustering model, then find the corresponding topic attribute dictionary through the topic center words, use Bayesian classifier is used for sentiment analysis, compared with SVM and decision tree methods, to evaluate the effect; For the picture dataset, Convolutional Neural Network (CNN) model is initialized by parameter migration, and image sentiment classification model is obtained by fine-tuning training of CNN model after parameter migration; Finally, the fusion method is designed to calculate the emotional probability of image-text, then judge the emotional polarity and compare it with the user's score, The accuracy rate is 88.6%, which is higher than that of text sentiment analysis model or image sentiment analysis model. The experimental results show that the sentiment analysis of image-text fusion has better classification effect on image-text reviews and more effectively avoid the problem of inconsistency between user ratings and the emotion expressed in comments.
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The Research of Automatic License Plate Location Algorithm Under Various Conditions
Статья научная
The paper presents a method of automated license plate location, the first key step of the license plate recognition is to find and separate the license plate area from the image of license plate. In this article, the quality of the license plate image is improved though a series of digital image processing in the image pretreatment, and the quick and exact license plate location is realized based on the gray projection algorithm. Large numerous of plate license images are acquired and tested by the development platform of VC++6.0, and the result shows that the technology adopted in the article has good adaptability, especially it can quickly and reliably locate the license plate images shot under complex backgrounds.
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The Research of Using Irregular Triangulated Network to Achieve the Relevant Water Calculation
Статья научная
This article describes the method of using irregular triangulated network to establish DEM (digital elevation model).Based on the DEM model, the article established and gave the relevant models and methods on the water areas and storage capacity in real time simulation by computer for forecasting and controlling of storage capacity and other related terms.
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The Stability of Boolean Rules Memory Based on the Core Systems of Number-Processing
Статья научная
Activation of how and where arithmetic operations are displayed in the brain has been observed in various number-processing tasks. However, it remains poorly understood whether stabilized memory of Boolean rules are associated with background knowledge. The present study reviewed behavioral and imaging evidence demonstrating that Boolean problem-solving abilities depend on the core systems of number-processing. The core systems account for a mathematical cultural background, and serve as the foundation for sophisticated mathematical knowledge. The Ebbinghaus paradigm was used to investigate learning-induced changes by functional magnetic resonance imaging (fMRI) in a retrieval task of Boolean rules.
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Статья научная
It is an arduous task to detect the traces of heavy metals in real environmental samples. In this paper, the use of micro-organisms as bioreceptors and the merits of nanobeads’ (NBs) properties are combined to develop a novel electrochemical biosensor based on nanocomposite films. The whole Escherichia. coli cells were fixed onto a surface of indium-tin-oxide glass with and without NBs and/or polyelectrolyte multilayers. In addition, the electrochemical impedance spectroscopy technique, mercury was used to detect.
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Thermal Enhancement of Capsaicin on Target Tissue Involved in Hyperthermia
Статья научная
Local thermal enhancement in target tissue is of great interest in tumor hyperthermia. In this study, we proposed a brand-new thermal enhancement protocol for tumor hyperthermia using heat generated from thermogenesis of capsaicin, which can safely deliver a totally localized heating to target tissue. A healthy male volunteer was recruited, whose partial areas of opisthenar and forearm were smeared with 1% (w/w) capsaicin solution, to determine the increase of thermogenesis in local area of human body. In addition, animal experiments on several healthy Kunming (KM) mice (20-22g) were performed to test the feasibility of this capsaicin based thermal enhancement method. Preliminary experiments on the volunteer showed an effective temperature increase in the skin area smeared with capsaicin solution. Animal experiments indicated that distinct enhancement in heating effect presents in the target tissue of mice where capsaicin solution was introduced. The thermal enhancement ability of capsaicin, therefore, suggests that capsaicin can be used as a potential therapeutic adjuvant to locally enhance heating effects in target tissue during tumor hyperthermia.
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Статья научная
The inhibition of the corrosion of aluminium by benzaldehyde in 1.4 M HCl was investigated using weight loss method and characterized by FT-IR analysis. The results showed that the corrosion rate of aluminium in 1.4 M HCl decreases with increase in concentration of the inhibitor. The inhibition efficiency increases progressively as the concentration of the inhibitor increases. Effects of temperature on the inhibition efficiency of the inhibitor showed that inhibition efficiency decreases with increase in temperature. The value of activation energy (Ea) was found to be 20.55 Kjmol-1 for aluminium corrosion in 1.4 M HCl which was increased to 34.49 Kjmol-1 in the presence of 0.1 M inhibitor concentration. The calculated values for enthalpy of activation (ΔHa) were all positive indicating the endothermic nature of the aluminium dissolution process. The obtained values of Gibbs free energy (ΔGads) was in the range of -17.94 to -18.27 kJ mol-1. Kinetics of the reaction in the presence of the inhibitor revealed that it follows a first order reaction. The value of rate constant (k) was reduced from uninhibited acid to the inhibited acid solution, while the half-life values in the presence of the inhibitor were higher compared to the value in uninhibited acid solution suggesting that inhibition efficiency increases with increase in the concentration of the inhibitor.
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Статья научная
Virtual reality plays a major role in medicine in the aspect of diagnostics and treatment planning. From the diagnostics perspective, automated methods yields the segmented results into virtual environment which will helps the physician to take accurate decisions on time. Virtual reality of 3D brain tissue segmentation helps to diagnostic the brain related diseases like alzheimer's disease, brain malformations, brain tumors, cerebellar disorders and etc. The work proposed a fully automatic histogram-based self-initializing K-Means (HBSKM) algorithm is performed on compute unified device architecture (CUDA) enabled GPU (QudroK5000) machine to segmenting the human brain tissue. Number of clusters (K) and initial centroids (C) automatically calculated from the mid image from the volume through Gaussian smoothening technique. The experimental dataset was collected from internet brain segmentation repository (IBSR) in segmenting the three major tissues such as grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) to experiment the efficiency of the present parallel K-Means algorithm. Computation time is calculated between the homogenous and heterogeneous environment of CPU and GPU for HBSKM algorithm. This proposed work achieved 6× speedup folds while heterogeneous CPU and GPU implementation and 3.5× speedup folds achieved with homogenous GPU implementation. Finally, volume of segmented brain tissue results was presented in virtual 3D and also compared with ground truth results.
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Towards Ambient Assisted Living (AAL): Design of an IoT-based Elderly Activity Monitoring System
Статья научная
This paper presents a design and development of an IoT-based system to real-time track elders' physical activities using accelerometer sensor data. The objective behind conducting such research is to overcome the lack of ability to monitor physical activities. Especially with the development of the socio-economic sector, the number of elders who live in isolated areas such as elderly homes have increased rapidly. In such a case with declining cognitive abilities, the healthcare of these elderly personalities becomes vulnerable. This research project fulfilled the necessity of a system to capture the vital details about those people. The Internet of Things (IoT) and cloud-based applications have become a significant part of the Information and Technology sector. Realtime monitoring is a concept tightly coupled with IoT cloud cloud-native application for this application is an excellent example of that.Further, the requirement of a low-cost system was fulfilled by using hardware components such as NodeMCU and accelerometer sensors. The designed and developed system is composed of a cost-effective wrist-worn device capable of capturing hand movement on three different arises. Hence, the detected signals are transmitted to a master node to process and recognize the activity according to the detected signal. Another significant aspect of the project is using machine learning techniques to recognize the four different activities such as walking, sitting, sleeping, and standing. The use of supervised machine learning techniques is evaluated to overcome the barriers of real-time activity recognition. Further different supervised machine learning algorithms were used and evaluated, which were extracted from existing literature. The project was conducted while accomplishing the machine learning life cycle stages, and it has significantly benefitted from generating highly accurate final results for the overall system. Further different supervised machine learning algorithms were used and evaluated, which were extracted from existing literature. The supervised machine learning algorithm Decision Tree Classifier used for this study. Using the Decision Classifier Tree algorithm succeeded in gaining more than 80% of model accuracy. Since the research topic comes under a classification type-oriented problem, the testing process of the model has been done using the confusion matrix for the trained model.
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Статья научная
As one of the countries situated in the Pacific Ring of Fire, the Philippines suffers from an inexhaustible number of natural disasters every year. One of the most destructible ones is the occurrence of earthquakes. Because of the high damage that earthquakes incur, along with their inevitability and unpredictability, developing effective methods of earthquake damage mitigation as well as disaster preparedness is imperative to lessen the negative impacts it is capable of producing in communities. One efficient way of doing this is by implementing an earthquake early warning (EEW) system that is capable of sending message alerts to receivers to warn them in the event of a hazardous earthquake. With this objective, this study centers on creating an earthquake detector with SMS messaging to function as an EEW system with an added advantage of being low-cost to make it more accessible to the public. Using electronic components based on an Arduino Mega 2560 and a Global System for Mobile Communications (GSM) module, the earthquake detector and its alert message system were created. A series of tests in different locations across Butuan City was then performed to assess the device’s accuracy in measuring different Intensity levels when subjected to surface vibrations. Comparative analysis showed that its recorded values. Corresponded with the values obtained from accelerometer-based mobile applications. In conclusion, the study was deemed functional in its ability to detect low and high surface vibrations, which proves that it is successful in detecting earthquake tremors and vibrations in the event of an earthquake.
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Статья научная
The main focuses are to design controlling systems of good disturbance, stability rejection, and small error-tracking. Trajectory tracking of robot manipulators are controlled by several methodologies, but when robot manipulator works with uncertain dynamic models, some limitations of this technique appear. Concerning the control perspective, such uncertainty can be divided into two groups: the unstructured inputs (e.g. disturbance effect) and the structure dynamics (e.g. the changes of parameter). Within a small number of applications, some environments, could be unknown or unstructured, make use of robot manipulators, along with some tools of strong mechanics also can make use of new methods of control to design a controller of nonlinear robust with a reasonable performance. So in this paper we test the effect of disturbance in control the first DOF of PUMA 560 using non model based FO-Fuzzy-PID controller and compared its results with two model based controllers (CTC, ANN). Also we study the effect of change of inertias parameters in the 2 cases Model based control and non- Model based control and then discus which controller give the best results. The main objective of this paper is that the non model based FO-Fuzzy-PID is able to emulate the manipulator dynamic behaviour without the need to have a complex nonlinear mathematical model for the robot.
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Transabdominal and Laparoscopic Myomectomy Comparative Analysis of 566 Cases
Статья научная
The purpose of our study here is introducing curative effect by comparing and analyzing abdominal type myomectomy and laparoscopic myomectomy. We have compared and analyzed 301 cases of abdominal type myomectomy and 265 cases of laparoscopic myomectomy which were in our hospital from January 2003 to December 2008. The study shows that the time of abdominal type myomectomy is 87.18±36.80 minutes, and the time of laparoscopic myomectomy is 81.56±30.71 minutes. There isn’t obvious difference between these two kinds of surgeries. The hemorrhagic volume in abdominal type myomectomy is 106.86±32.65 ml and the hemorrhagic volume in laparoscopic myomectomy is 85.23±30.37 ml. The hemorrhagic volume difference in these two kinds of surgeries is very important from the point of view of statistics (P<0.01). The average days which used to restore in abdominal type myomectomy is 2.85±1.73, and the average days which used to restore in laparoscopic myomectomy is 5.81±1.47. And the difference is also very important (P<0.01). We have concluded that the laparoscopic myomectomy has such advantages as small hurt, rapid restoration and no incision. On the other hand, the hemorrhagic volume is very low and the restoration-days are very low.
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Transfer Characteristics of Three Kinds of Micro-groove Heat Pipes
Статья научная
In this paper, a simulation of three kinds of micro-groove plate heat pipes- rectangular; trapezoidal and triangular, is conducted by thermal analysis software ANSYS. Through comparing with the focal point temperature value of the surfaces of micro-groove plate heat pipes, respectively being 30W; 40W; 50W, the result is obtained that trapezoidal plate heat piper has more excellent performance.
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Transfer Learning based Breast Cancer Classification via Deep Convolutional Neural Network
Статья научная
Breast cancer is a leading cause of death among women, and the subjectivity of human visual perception and lack of automated detection methods can lead to misclassification of breast cancer images. In this study, a breast cancer classification model using a Convolutional Neural Network (CNN) deep learning algorithm was proposed. The model demonstrated high accuracy in classifying breast images as benign or malignant, with a classification accuracy of 97.1%. The model was also able to run on low computational resources. The study used a dataset of 2009 breast images labeled by two radiologists and included six scenarios based on different hyperparameters, augmentation values, pretrained models, and models built from scratch. While the performance of the proposed model was promising, further improvement may be achieved by using a larger breast image dataset and a machine with more powerful GPU hardware.
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Transfer Learning with EfficientNetV2 for Diabetic Retinopathy Detection
Статья научная
This paper investigates the application of EfficientNetV2, an advanced variant of EfficientNet, in diabetic retinopathy (DR) detection, a critical area in medical image analysis. Despite the extensive use of deep learning models in this domain, EfficientNetV2’s potential remains largely unexplored. The study conducts comprehensive experiments, comparing EfficientNetV2 with established models like AlexNet, GoogleNet, and various ResNet architectures. A dataset of 3662 images was used to train the models. Results indicate that EfficientNetV2 achieves competitive performance, particularly excelling in sensitivity, a crucial metric in medical image classification. With a high area under the curve (AUC) value of 98.16%, EfficientNetV2 demonstrates robust discriminatory ability. These findings underscore its potential as an effective tool for DR diagnosis, suggesting broader applicability in medical image analysis. Moreover, EfficientNetV2 contains more layers than AlexNet, GoogleNet, and ResNet architecture, which makes EfficientNetV2 the superior deep learning model for DR detection. Future research could focus on optimizing the model for specific clinical contexts and validating its real-world effectiveness through large-scale clinical trials.
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Статья научная
When we are translating SQL into relational algebra, we need a simple but flexible form to represent the data structure involved. As an interim result of the calculation, relational algebra tree combined with object-oriented model can gives us simple, intuitive notation allowing the query to be efficiently expressed and implemented at amazing ease.
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Статья научная
Comparative study of cryptography and steganography techniques shows that they have some strong and weak points when they used alone. But as we know from soft computing techniques (neural, genetic, and fuzzy computing), that when combining (hybridizing), more than one techniques, by the suitable way to do a job, the outcome will be a better technique with more strong points and less weak points. Work of this paper represents an attempt to prove that combining cryptography with steganography techniques will result in hard transmitting system to break and thus enforcing security issues of secret text data transmitting over public channels. Matlab programs are written to encrypt plain text secret information following AES encrypt/decrypt algorithm with a key of 128 bits long and then hide/extract the text according to LSB insertion method with a key of 128 bits long too. System tests show that both techniques enforce each other and private data transmitting become more secure.
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