List of Articles
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Open Access Article
1 - A Threshold-based Brain Tumour Segmentation from MR Images using Multi-Objective Particle Swarm Optimization
Katkoori Arun Kumar Ravi BodaThe Pareto optimal solution is unique in single objective Particle Swarm Optimization (SO-PSO) problems as the emphasis is on the variable space of the decision. A multi-objective-based optimization technique called Multi-Objective Particle Swarm Optimization (MO-PSO) i MoreThe Pareto optimal solution is unique in single objective Particle Swarm Optimization (SO-PSO) problems as the emphasis is on the variable space of the decision. A multi-objective-based optimization technique called Multi-Objective Particle Swarm Optimization (MO-PSO) is introduced in this paper for image segmentation. The multi-objective Particle Swarm Optimization (MO-PSO) technique extends the principle of optimization by facilitating simultaneous optimization of single objectives. It is used in solving various image processing problems like image segmentation, image enhancement, etc. This technique is used to detect the tumour of the human brain on MR images. To get the threshold, the suggested algorithm uses two fitness(objective) functions- Image entropy and Image variance. These two objective functions are distinct from each other and are simultaneously optimized to create a sequence of pareto-optimal solutions. The global best (Gbest) obtained from MO-PSO is treated as threshold. The MO-PSO technique tested on various MRI images provides its efficiency with experimental findings. In terms of “best, worst, mean, median, standard deviation” parameters, the MO-PSO technique is also contrasted with the existing Single-objective PSO (SO-PSO) technique. Experimental results show that Multi Objective-PSO is 28% advanced than SO-PSO for ‘best’ parameter with reference to image entropy function and 92% accuracy than Single Objective-PSO with reference to image variance function. Manuscript profile -
Open Access Article
2 - Predicting Student Performance for Early Intervention using Classification Algorithms in Machine Learning
Kalaivani K Ulagapriya K Saritha A Ashutosh KumarPredicting Student’s Performance System is to find students who may require early intervention before they fail to graduate. It is generally meant for the teaching faculty members to analyze Student's Performance and Results. It stores Student Details in a database and MorePredicting Student’s Performance System is to find students who may require early intervention before they fail to graduate. It is generally meant for the teaching faculty members to analyze Student's Performance and Results. It stores Student Details in a database and uses Machine Learning Model using i. Python Data Analysis tools like Pandas and ii. Data Visualization tools like Seaborn to analyze the overall Performance of the Class. The proposed system suggests student performance prediction through Machine Learning Algorithms and Data Mining Techniques. The Data Mining technique used here is classification, which classifies the students based on student’s attributes. The Front end of the application is made using React JS Library with Data Visualization Charts and connected to a backend Database where all student’s records are stored in MongoDB and the Machine Learning model is trained and deployed through Flask. In this process, the machine learning algorithm is trained using a dataset to create a model and predict the output on the basis of that model. Three different types of data used in Machine Learning are continuous, categorical and binary. In this study, a brief description and comparative analysis of various classification techniques is done using student performance dataset. The six different machine learning Classification algorithms, which have been compared, are Logistic Regression, Decision Tree, K-Nearest Neighbor, Naïve Bayes, Support Vector Machine and Random Forest. The results of Naïve Bayes classifier are comparatively higher than other techniques in terms of metrics such as precision, recall and F1 score. The values of precision, recall and F1 score are 0.93, 0.92 and 0.92 respectively. Manuscript profile -
Open Access Article
3 - Evaluating the Cultural Anthropology of Artefacts of Computer Mediated Communication: A Case of Law Enforcement Agencies
Chukwunonso Henry Nwokoye Njideka N. Mbeledogu Chikwe UmeugojiThe renowned orientations of cultural models proposed by Hall and Hofstede has been the subject of criticisms. This is due to the weak, inflexible and old-fashioned nature of some designs resulting from them. In addition, is the ever-changing, formless and undefined nat MoreThe renowned orientations of cultural models proposed by Hall and Hofstede has been the subject of criticisms. This is due to the weak, inflexible and old-fashioned nature of some designs resulting from them. In addition, is the ever-changing, formless and undefined nature of culture and globalization. Consequently, these vituperations have resulted in better clarifications when assessing the cultural anthropology of websites. Based on these later clarifications and other additions, we seek to evaluate the cultural heuristics of websites owned by agencies of the Nigerian government. Note that this is verily necessary because older models did not include Africa in their analyses. Specifically, we employed the online survey method by distributing questionnaires to different groups of experts drawn from the various regions of Nigeria. The experts employed methods such as manual inspection and use of automated tools to reach conclusions. Afterwards, the results were assembled and using the choice of a simple majority, we decided whether a design parameter is either high or low context. Findings show that websites developers tend to favor low context styles when choosing design parameters. The paper attempts to situate Africa in Hall’s continuum; therein, Nigeria (Africa) may fall within French Canadian and Scandinavian and/or within Latin and Scandinavian for the left hand and right hand side diagram respectively. In future, we would study the cultural anthropology of African websites employing the design parameters proposed by Alexander, et al. Manuscript profile -
Open Access Article
4 - Proposing Real-time Parking System for Smart Cities using Two Cameras
Phat Nguyen Huu Loc Hoang BaoToday, cars are becoming a popular means of life. This rapid development has resulted in an increasing demand for private parking. Therefore, finding a parking space in urban areas is extremely difficult for drivers. Another serious problem is that parking on the roadw MoreToday, cars are becoming a popular means of life. This rapid development has resulted in an increasing demand for private parking. Therefore, finding a parking space in urban areas is extremely difficult for drivers. Another serious problem is that parking on the roadway has serious consequences like traffic congestion. As a result, various solutions are proposed to solve basic functions such as detecting a space or determining the position of the parking to orient the driver. In this paper, we propose a system that not only detects the space but also identifies the vehicle's identity based on their respective license plate. Our proposal system includes two cameras with two independent functions, Skyeye and LPR cameras, respectively. Skyeye module has function to detect and track vehicles while automatic license plate recognition system (ALPR) module detects and identifies license plates. Therefore, the system not only helps drivers to find suitable parking space but also manages and controls vehicles effectively for street parking. Besides, it is possible to detect offending vehicles parking on the roadway based on its identity. We also collect a set of data that correctly distributes for the context in order to increase the system's performance. The accuracy of proposal system is 99.48% that shows the feasibility of applying into real environments. Manuscript profile -
Open Access Article
5 - Word Sense Induction in Persian and English: A Comparative Study
Masood GhayoomiWords in the natural language have forms and meanings, and there might not always be a one-to-one match between them. This property of the language causes words to have more than one meaning; as a result, a text processing system faces challenges to determine the precis MoreWords in the natural language have forms and meanings, and there might not always be a one-to-one match between them. This property of the language causes words to have more than one meaning; as a result, a text processing system faces challenges to determine the precise meaning of the target word in a sentence. Using lexical resources or lexical databases, such as WordNet, might be a help, but due to their manual development, they become outdated by passage of time and language change. Moreover, the lexical resources might be domain dependent which are unusable for open domain natural language processing tasks. These drawbacks are a strong motivation to use unsupervised machine learning approaches to induce word senses from the natural data. To reach the goal, the clustering approach can be utilized such that each cluster resembles a sense. In this paper, we study the performance of a word sense induction model by using three variables: a) the target language: in our experiments, we run the induction process on Persian and English; b) the type of the clustering algorithm: both parametric clustering algorithms, including hierarchical and partitioning, and non-parametric clustering algorithms, including probabilistic and density-based, are utilized to induce senses; c) the context of the target words to capture the information in vectors created for clustering: for the input of the clustering algorithms, the vectors are created either based on the whole sentence in which the target word is located; or based on the limited surrounding words of the target word. We evaluate the clustering performance externally. Moreover, we introduce a normalized, joint evaluation metric to compare the models. The experimental results for both Persian and English test data showed that the window-based partitioningK-means algorithm obtained the best performance. Manuscript profile -
Open Access Article
6 - Digital Transformation Model, Based on Grounded Theory
Abbas Khamseh Mohammad Ali Mirfallah Lialestani Reza RadfarGiven the emergence of Digital Transformation from Industry 4.0 and the rapid dissemination of technological innovations as well as their impact as a strong driving force in new businesses, efforts should be made to identify the dimensions of this core factor as rapidly MoreGiven the emergence of Digital Transformation from Industry 4.0 and the rapid dissemination of technological innovations as well as their impact as a strong driving force in new businesses, efforts should be made to identify the dimensions of this core factor as rapidly as possible. Providing a comprehensive overview of all aspects of the model. The purpose of this article is to provide insights into the state of the art of digital transformation in the last years and suggest ways for future research. This analysis is like a mapping of the subject literature into categories, so that with the help of a number of experts the evolutionary trends can be identified and further researched. In this way, with a deeper understanding of the subject, we have attempted to identify existing gaps. The findings suggest that organizations of all sizes must adapt their business strategy to the realities of digital transformation. This will largely lead to changing business processes as well as managing operations in a new and more intelligent tool-based way. Based on this research, organizations will evolve not just on their own, but on the whole value chain, and this will clearly change the way they produce and deliver value. Organizations can develop their digital ecosystem by creating and developing innovation centers and using open innovation strategy, and as a result, link their digital business to a value chain. Also in this article, we have identified the main categories and subcategories by examining the sources and using the grounded theory approach, as well as determining the relationship between them. Finally, we completed the work by identifying the digital transformation model as the central phenomenon of research. Manuscript profile -
Open Access Article
7 - An Automatic Thresholding Approach to Gravitation-Based Edge Detection in Grey-Scale Images
Hamed Agahi Kimia RezaeiThis paper presents an optimal auto-thresholding approach for the gravitational edge detection method in grey-scale images. The goal of this approach is to enhance the performance measures of the edge detector in clean and noisy conditions. To this aim, an optimal thres MoreThis paper presents an optimal auto-thresholding approach for the gravitational edge detection method in grey-scale images. The goal of this approach is to enhance the performance measures of the edge detector in clean and noisy conditions. To this aim, an optimal threshold is automatically found, according to which the proposed method dichotomizes the pixels to the edges and non-edges. First, some pre-processing operations are applied to the image. Then, the vector sum of the gravitational forces applied to each pixel by its neighbors is computed according to the universal law of gravitation. Afterwards, the force magnitude is mapped to a new characteristic called the force feature. Following this, the histogram representation of this feature is determined, for which an optimal threshold is aimed to be discovered. Three thresholding techniques are proposed, two of which contain iterative processes. The parameters of the formulation used in these techniques are adjusted by means of the metaheuristic grasshopper optimization algorithm. To evaluate the proposed system, two standard databases were used and multiple qualitative and quantitative measures were utilized. The results confirmed that the methodology of our work outperformed some conventional and recent detectors, achieving the average precision of 0.894 on the BSDS500 dataset. Moreover, the outputs had high similarity to the ideal edge maps. Manuscript profile