International Journal of Engineering and Manufacturing @ijem
Journal articles - International Journal of Engineering and Manufacturing
All articles: 623
The Development of GSM Mobile Phone MMI Software
Scientific article
This article discusses the design and implementation of MMI software of GSM mobile phone. In this design, object-oriented programming techniques are used. The way to design the interface between chip and MMI hardware of GSM is introduced too. These skills make the software has clear program structure, high code efficiency and good reusable modules. In this article the development of GSM mobile phone MMI software modules organization, window management techniques, and shortcuts are talked about.
Free
Scientific article
In this life, every person is always faced with various options and each choice will certainly bring different consequences. Pharmacy Company as an organization which managed by the human resources are also faced with various options in order to determine a quality officer. The hardest thing in making a choice is an effort to eliminate the subjectivity factor of the procurement team so that every choice made is objective. Based on the analysis of the above requirements, the company need a computer application that can support decision making using the Analytic Network Process. The application is not a key decision makers who will replace the role of men but only as decision support. Applications are made to assist the Personnel Manager of the company in selecting prospective employees and new employee selection. In addition, the application also help in a structured data collection so that support a balanced and objective assessment.
Free
The Emerging Role of Academia in Sqa
Scientific article
Now that every company and every consumer prioritize quality over quantity of work, the career of Software quality assurance is also taking a leap, especially in the field of academia. Thus, this report gives an overview of what a future with the usage of software quality control and testing would look like, and why it’s needed for the development of the caliber of software used all around the globe. It further marks out why adding courses related to software quality assurance in the curriculum is important and how this addition can widen the dynamics of software control, quality and testing industries. It also marks out how, even today, academia can and is playing an integral role in the developmental process of software quality assurance and testing in terms of the research that can be and is being made towards the whole developmental process of SQA. Universities and undergraduate programs can further play an important role towards the researching the horizons and fields software testing and assurance has to offer in the near future. Furthermore, this report questioned various practitioners belonging to some of the most prestigious IT companies about their opinion on the research questions involved in this report so as to verify the credibility of the data that has been gathered. At the end of the research, we have a foresight for as to how the industry of software quality assurance and software testing will grow.
Free
The Identification of Human Cassette Exons based on SVM
Scientific article
Alternative splicing is the main mechanism expanding transcript diversity. Cassette exon is an important alternative splicing form that is very similar to constitutive exon in sequence features. Previous studies which based on expressed sequence tags (ESTs) and evolutionary conservation information have identified many alternative splicing events. In this paper, we construct a classifier to identify the human cassette exons based on Support vector machine (SVM) which only make use of sequence information. It can achieve the accuracy of 68.12%. Especially, the classifier can achieve 76.54% when considering the splicing frequency. The results show that the sensitivity and specificity of this method are higher than those recently reported on the same dataset.
Free
Scientific article
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.
Free
The Impact of Organizational Slack on The Performance of Pharmaceutical and Chemical Firms
Scientific article
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.
Free
The Influence of Stage Structure and Prey Refuge on the Stability of the Predator-Prey Model
Scientific article
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.
Free
Scientific article
A Modified Group Method of Data Handling (MGMDH) is a component of a synthetic method of constructing multivariate polynomial regression given by a redundant representation. The MGMDH is used to construct multivariate linear regression given by a redundant representation in the case when a decomposition method, which is also a component of the synthetic method, allowed to estimate with a given accuracy the values of unknown coefficients for nonlinear terms of a multivariate polynomial regression. As statistical studies have shown, the MGMDH efficiently finds the correct structure of a multivariate linear regression when the realizations of a random factor in the tests are an order of magnitude smaller than the modules of the corresponding values of the regression to be determined. Only in this case, the use of the regularity criterion in the MGMDH almost always allows finding the correct structure of a multivariate linear regression given by a redundant representation. In this paper, the MGMDH is adapted for the case when during the tests the modules of the random factor implementations and the values of the regression to be determined take values of the same order, which significantly increases the efficiency of using the MGMDH for constructing multivariate linear regressions given by redundant representations. It is obvious that the adapted MGMDH for multivariate linear regressions given by redundant representations presented in this work is easily transformed using the standardization operation for the general problem of constructing multivariate regression given by a redundant representation in the case when the unknown coefficients are linear in the regression structure.
Free
The Multimedia Sentiment Model Based on Online Homestay Reviews
Scientific article
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.
Free
The Research of Automatic License Plate Location Algorithm Under Various Conditions
Scientific article
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.
Free
The Research of Using Irregular Triangulated Network to Achieve the Relevant Water Calculation
Scientific article
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.
Free
The Stability of Boolean Rules Memory Based on the Core Systems of Number-Processing
Scientific article
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.
Free
Scientific article
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.
Free
Scientific article
Humans use emotions to express their feelings and effectively interact with others. Humans express emotions through hands, voice, gestures, and, most importantly, facial expressions. Facial emotion recognition is widely used in human-computer interaction, security, and healthcare. Traditional facial emotion recognition using visible light is often affected by changing lighting conditions. Thermal images could be used as an alternative solution because it relies on physiological heat patterns that remain consistent regardless of illumination. However, the use of thermal images for emotion recognition has not been extensively explored, primarily due to the scarcity of thermal image datasets. The study utilized the recently published Thermal Emotion dataset, which contains 2,250 thermal images before augmentation. After generating a synthetic dataset using cGAN, the datasets expanded to 6,823 images. To prevent dataset leakage, the study used 80% of the data for training, 10% for validation, and 10% for testing. The study used a bilateral filter to reduce noise while keeping relevant edge information, used CLAHE to enhance local contrast in low-intensity regions, making subtle thermal gradients more distinguishable, used Gaussian smoothing to reduce high-frequency noise, resulting in more stable feature extraction, and used attention mechanisms, CBAM, to allow the model to focus on emotion-relevant facial regions through its channel and spatial attention components. The combination of these techniques improved inter-class separability and contributed to measurable gains in recognition accuracy. The study findings show that inclusions of the bilateral filter, CLAHE cGAN, EfficientNetB5, and the CBAM attention mechanism significantly improved accuracy from 97.04% to 98.81%. For each experiment, ResNet18 classifies human facial emotions into five expressions: Happy, Sad, Angry, Natural, and Surprise. These findings imply that synthetic data generation using a cGAN to overcome data scarcity and an attention mechanism provides robust, lightning-independent solutions for facial emotion recognition.
Free
Thermal Enhancement of Capsaicin on Target Tissue Involved in Hyperthermia
Scientific article
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.
Free
Scientific article
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.
Free
Scientific article
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.
Free
Towards Ambient Assisted Living (AAL): Design of an IoT-based Elderly Activity Monitoring System
Scientific article
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.
Free
Towards Automated Diagnosis of Heart Diseases: A Study of Machine Learning Techniques
Scientific article
The study applies machine learning algorithms to the diagnosis of heart disease. Data were collected from multiple sources in hospital and clinic records, along with time-based comparison other studies. The second part of the study, Clinical Decision Support, simulated the daily work of a physician and helped them make patient-centered medical decisions. The results revealed significant potential for machine learning to improve heart disease detection efficiency and accuracy, which could benefit future effective disease management and reduce patient burden. The study findings will enable future healthcare providers to harness new technology to achieve better prevention and superior care outcomes for heart disease screening. The study recommendations include optimal diagnostic skills and intervention-oriented preventive measures.
Free
Scientific article
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.
Free
