Статьи журнала - International Journal of Engineering and Manufacturing
Все статьи: 484
Статья научная
In the modern era agriculture development is the highly contribute field of food security. Data Science is one of the top analysis experimental methods for forecasting and mapping synchronize. In our study, we experiment with three major parameters (Rainfall, Relative Humidity and Temperature) that can be affected crop production rate as well as area-based mapping. To complete the procedure, the cluster groping and prediction system has created a machine learning BOT combined analysis system. Bangladesh and its 13 areas with 46 years of data have visualized with proper analysis and build up a 2D map of each separate production area. Multi Linear Regression (MLR) and KMean Clustering is the main key point algorithm for the production analysis. Experiment analyzing, we can see that some elements of our environment are closely associated with the productivity of the crop. An untactful environmental change on parameters (Rainfall, Humidity, and Temperature) reduces agricultural productivity by 32-38%. Developed model accuracy 91.25% forecasting methodological analysis for production mapping and prediction. Extreme population food security has ensured ICT and Agriculture combine BOT & EVPM method is essential for the scientific world. This study will allow farmers to choose the proper crop in the right environmental condition, which will play a key role in strengthening the economy of the country.
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Cystic Region Detection Using Hybrid Fuzzy-based Multi-Region Normalization
Статья научная
One of the main purposes of this approach is to automatically extract the cystic border. Several of the semi-automatic segmentation strategies that have already been used may result in incomplete categorization, which is likely to fail as well as causes solitary pixel in noise dentistry x-rays images due to sampling artifact. As such, cyst boundaries are not removed appropriately. It focuses on the elimination of solitary pixels caused by artefacts. This suggested technique uses both the fuzzy memberships function of every pixel as well as localized spatially information of the neighbor pixels to accomplish the maximum feasible levels of automated processes for computers-aided diagnostics or identification of illnesses. That fuzzy-based multi-region normalization is implemented in five phases. To begin, FCM techniques are used to determine the numbers of centroids. This fuzzified function is constructed as well as provides memberships degree numbers to any and every pixel within every class based on the number of cluster centers as well as the shape of the histogram. It generates an intermediary segmentation output by fuzzy memberships degrees at about this step. This fuzzy localized aggregating of the neighborhood pixels will be the fourth phase, with the greatest responsiveness of the memberships degree generating pixels being kept in mind only for ultimate cystic area retrieved outputs.
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DataViz Model: A Novel Approach towards Big Data Analytics and Visualization
Статья научная
Big Data is the collection of large data sets which contains large amount of data. There are different areas which are generating huge data, this data may be present in the form of semi-structured or unstructured and to get useful information from such raw data there is need of data analysis. Due to Big Data’s excessive volume, variety, and velocity it is very difficult to store and process huge data. The process of extracting the information from such raw data is called Big Data Analytics. Big data Analytics processes data gives result in the form of structured data. Again this data is huge size and very difficult to understand since it is present in the form of CSV or excel or simple text files. So for effective decision making and to understand the information quickly the data need to be visualized as human mind understands images and graphs better and faster than text data. In this paper a model called Data Visualization (Viz) is designed which integrates big data analytics and the data visualization. This model first takes the data from various sources and then processes it and converts it into structured form, if want this data can be stored to RDBMS. Finally the text result can be visualized with the help of Visualization module of the DataViz. Here text result is represented in the form of charts and graphs.
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Database Design of a General Data Analysis System of Commodity Sales Information
Статья научная
A data analysis system for the general commodity sales information is researched on and further designed. The key problems of designing this system are that, it should enable the system to adjust to user-data with different structures, enable users to define or change data structures as well as retrieval methods. Through the research on the general structure and retrieval method of the commodity sales data, the system realizes users' customization of the database, thus is applicable to sales data with different structures. This paper focuses on the structure of the database, the creation method and process of the database by the user, the structure of the data dictionary and data exchange between database and software, with case examples in the final illustration.
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DbDMAD: a Database of DNA Methylation in Human Age-related Disease
Статья научная
DNA methylation plays a variety of crucial roles in cell division, proliferation, development of aging life, development of genetic diseases related to uniparental disomy, and carcinogenesis. DNA methylation can be probed by HPLC and gene chip which is very helpful to the high-through methylation test. In recent years many published articles reported that DNA methylation may be linked with human aged disease. Mining and integration of DNA methylation in human aged disease can be beneficial to novel biological discoveries. There has not been DNA methylation database repository which is exclusive for human aged disease. Therefore, we developed dbDMAD: a database of DNA methylation in human aged diseases, there are two purposes of it, one is to store DNA methylation in human aged disease datasets which were obtained from laboratory experiments, another is to find the relationship of different aged diseases. This is the first release of dbDMAD in which users can find 12 kinds of human aged diseases and relevant DNA methylation information. It can be searched by disease name and gene ID. This database also includes a visualization tool named ChainMap, by which the map of methylation pathway can be shown.
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Deep Convolution Neural Networks for Cross-Dataset Facial Expression Recognition System
Статья научная
Facial Expressions are a true and obvious way to represent emotions in human beings. Understanding facial expression recognition (FER) is essential, and it is also useful in the area of Artificial Intelligence, Computing, Medical, Video games, e-Education, and many more. In the past, much research was conducted in the domain of FER using different approaches such as analysis through different sensor data, using machine learning and deep learning framework with static images and dynamic sequence. Researchers used machine learning-based techniques such as the Multi-layer Perceptron Model, k- Nearest Neighbors, and Support Vector Machines were used by researchers in solving the FER. These methods have extracted features such as Local Binary Patterns, Eigenfaces, Face-landmark features, and Texture features. Recently use of deep learning algorithms in FER has been considerable. State-of-the-art results show deep learning-based approaches are more potent than conventional FER approaches. This paper focuses on implementing three different Custom CNN Architecture training them on FER13 Dataset and testing them on CK+ and JAFFE Dataset including FER13 after fine-tuning. The three pre-trained models' on FER2013 after fine-tuning have significantly improved the accuracy of the resulting CNN on the target test sets between 65.12 % to 79.07% on the JAFFE dataset and 50.96% to 68.81% on the CK+ dataset.
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