Chittagong University of Engineering & Technology

About: Chittagong University of Engineering & Technology is a education organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Computer science & Renewable energy. The organization has 1200 authors who have published 1444 publications receiving 10418 citations. The organization is also known as: Engineering College, Chittagong & Bangladesh Institute of Technology, Chittagong.

Optimal PID tuning for controlling the temperature of electric furnace by genetic algorithm

Abstract: Temperature is one of the exigent parameters that needs to be controlled in today’s industries. Importantly this temperature control should be precise and fast. As the conventional controllers are not optimally tuned, the controller used for controlling the temperature of the electric furnace does not exhibit better performance. Its rise time and settling time is too large as well as it has a sizable amount of overshoot. This paper presents a Genetic Algorithm based PID controller to overcome the low precision, long rise time and settling time of the controller. In this algorithm, Integral of Absolute Error is taken as the object function for minimizing the error. Using this function, the algorithm engenders the optimum value of the gain parameters (Kp, Ki, Kd) for the PID controller. It shows better control over the conventional controllers. As the overshoot, settling time, and rise time are substantially improved, it provides sharp and prompt control over the temperature. This precise and instant control of temperature has a great impact on the food and medicine industries. As the temperature could be controlled precisely and instantly, we can avoid the change/degradation of the physical properties of the materials that are under process.

Sentiment Analysis of Bengali Texts on Online Restaurant Reviews Using Multinomial Naïve Bayes

Abstract: Recently, determining the customer impression is considered one of the prominent factors on the success of the restaurant businesses. Due to the rapid growth of digital contents related to restaurant or foods in the web, people are more inclined on reviews before going to any restaurant so the significance of customer review is inevitable. In order to selects a restaurant customer needs to check thousands of feedback’s to understand the restaurant quality or services. Therefore, classification of a significant amount of reviews into a sentimental category is required to attain meaningful insights so that the customer can choose restaurants based on their preferences. This classification can be done by sentiment analysis. This paper proposes a system that can classify customer reviews into positive and negative classes based on their sentimental feedback. We have tested the proposed system with 1000 restaurant reviews text written in Bengali. The experimental result shows that the proposed the system can classify restaurant reviews with 80.48% accuracy using multinomial Naive Bayes.

Shoreline change assessment using geospatial tools: a study on the Ganges deltaic coast of Bangladesh

Abstract: The Ganges deltaic coast of Bangladesh experiences an incessant movement over the time. Understanding the shoreline movement of this alluvial delta and a suitable method to calculate the rate of change poses a challenge for this highly dynamic coast having erosion and accretion. Using GIS and multi temporal LANDSAT images, the study investigated the positional change of the Ganges deltaic shoreline for the period of 1977–2017. LANDSAT images were radiometrically corrected and a spectral index i.e., normalized difference water index (NDWI) was applied to differentiate water and land features. A histogram based Otsu’s Binary thresholding method along with image based visual interpretation was used to extract the shorelines. Net changes of shoreline position were statistically calculated using three different techniques, namely; End Point Rate (EPR), Linear Regression Rate (LRR) and Weighted Linear Regression (WLR). A comparison between the techniques was also made to choose and evaluate the suitable statistical technique to estimate the rate of shoreline change for this alluvial delta. Analyses showed that LRR technique had less positional uncertainty in compare to EPR and WLR, although at a particular transect the techniques were closely correlated. The EPR, WLR and LRR technique showed that the shoreline is experiencing landward movement (erosion) with an average rate of 0.62 m/yr, 0.96 m/yr and 0.27 m/yr respectively. Moreover, a high erosion rate of 5 m/yr at the mangrove forest area of the GDC is a great concern for the existence of the mangrove forest. During 1977–2017, an overall 6.29 sq. km land area has been lost although significant land depositions were observed at the river estuaries. This study revealed the spatiotemporal trend of shoreline position of the Ganges deltaic coast and that would be beneficial for the coastal management and planning of the region.

Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions

Abstract: The rapid advancement of information and communication technology has brought a revolution in the domain of public transport (PT) planning alongside other areas of transport planning and operations. Of particular significance are the passively generated big data sources (e.g., smart cards, detailed vehicle location data, mobile phone traces, social media) which have started replacing the traditional surveys conducted onboard, at the stops/stations and/or at the household level for gathering insights about the behavior of the PT users. This paper presents a systematic review of the contemporary research papers related to the use of novel data sources in PT planning with particular focus on (1) assessing the usability and potential strengths and weaknesses of different emerging big data sources, (2) identifying the challenges and highlighting research gaps. Reviewed articles were categorized based on qualitative pattern matching (similarities/dissimilarities) and multiple sources of evidence analysis under three categories—use of big data in (1) travel pattern analysis, (2) PT modelling, and (3) PT performance assessment. The review revealed research gaps ranging from methodological and applied research on fusing different forms of big data as well as big data and traditional survey data; further work to validate the models and assumptions; lack of progress on developing more dynamic planning models. Findings of this study could inform transport planners and researchers about the opportunities/challenges big data bring for PT planning. Harnessing the full potential of the big data sources for PT planning can be extremely useful for cities in the developing world, where the PT landscape is changing more rapidly, but traditional forms of data are expensive to collect.