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.

Optical wireless data transmission with enhanced substitution Caesar Cipher WHEEL encryption

Abstract: The paper describes a microcontroller based secured optical wireless communication system using laser and phototransistor. These days the usage of Wi-Fi has reached to every nook and corner of the world. There are some downsides belong to the usage of Wi-Fi such as those concerning to the speed, limited bandwidth, security and range of its usage. In order to overcome these hitches we can use the advanced version of Li-Fi which is efficient, high speed, and fully networked wireless communication. If light contains encrypted message then both privacy and prevention from unwanted access along with high data rate can be achievable from Li-Fi. A new encryption technique based on substitution of ASCII value of characters implemented and reliable data transmission carried out. The proposed encryption algorithm primarily follows Caesar Cipher WHEEL substitution, acts similarly with Caesar wheel device by rotating circularly and changes the ASCII value of original message according to predefined values and length of repetition. Encryption of data, transmission, reception and conversion to original message are implemented successfully using laser, phototransistor, microcontroller and associated devices. Microcontroller performs as overall controlling and processing unit.

A framework for detecting arsenic disease

Abstract: Humans are exposed to arsenic (As) primarily from air, food and water. Anyone can develop arsenic toxicity as a result of arsenic exposure. Most of the reports of chronic as well as toxicity in human focus attention on skin manifestations because of its diagnostic specificity. A dermal manifestation such as hyperpigmentation is diagnostic of chronic arsenicosis. This paper focuses on designing and modelling a system that will collate Pigmented Skin Lesion (PSL), their analysis, corresponding observations and conclusions by medical experts using prototyping methodology. The system uses computational intelligence technique to analyse, process, and classify the image library data based on texture and morphological features of the images. A user in a remote location can use mobile data acquisition devices (such as smartphone) to generate images of PSL, supply such images as input to the proposed system, which in turns should intelligently be able to specify the arsenic poisoned hyperpigmentation status of the imaged PSL. The system has been evaluated with a set of images and found that the system can almost accurately detect arsenic.

A New Approach to Solve Job Sequencing Problem Using Dynamic Programming with Reduced Time Complexity

Abstract: The classical algorithm which is dedicated to resolve job sequencing problem with a deadline (JSD) needs exponential time O(\( n^{2} \)), where sorting algorithm [O(\( nlog\left( n \right) \))-(Merge Sort)] must have to use to sort all the jobs in decreasing order of their profit and it is a greedy technique. To reduce the complexity of this classical algorithm, we nullify the sorting algorithm using dynamic programming approach in the proposed algorithm. The time complexity after using this approach reduces to O(\( mn \)), where no sorting algorithm [O(\( nlog\left( n \right) \))-(Merge Sort)] needed, which has been shown by proper explanation. Here, we were also given a novel approach to resolve the job sequencing problem using Dynamic Programming and it is a unique approach that always finds an optimal solution. By using this approach, a proper algorithm has been developed in this paper. Besides, finding maximum profit and the sequence of the job to obtain maximum profit, this algorithm gives the sequence of jobs for a specific profit or near a specific profit.

Early detection of Sepsis in critical patients using Random Forest Classifier

Abstract: Time plays a pivotal rule in successful control of sepsis-associated infections and mortality in ICU patients. Accurate and confident prediction of sepsis ahead of time is a challenging task owing to the complex nature of the underlying pathophysiological mechanisms. Missing data in the laboratory values which have been reported by medical findings to be important for forecasting sepsis makes the problem worse. To address the problem of missing data, last observation carried forward (LOCF) method has been adopted in this paper. This has been proved to be a simple yet effective idea. The remaining missing features were substituted with zero, which is one type of constant imputation. Out of the 40 available features, 19 were selected by performing the analysis of variance (ANOVA) test. The class imbalance problem was addressed via cost-sensitive learning which gave more weight to the minority class data points based on their proportion. Finally, a random forest classifier was trained upon the data. The model obtained a utility score of approximately 57% and 22% respectively on the two datasets which were taken from Physionet/Computing in Cardiology (CinC) challenge, 2019.

Development of control strategy for load sharing in grid-connected PV power system

Abstract: In a power system of conventional parallel connected generators, share of real power and reactive var of an incoming generator are controlled by adjusting shaft power input and field excitation The scenario of load sharing by a grid connected PV system is however different since no prime mover or excitation source are present Due to serious power crisis, there are needs for evacuation of PV power to grid systems However, this needs intensive analysis on the load sharing phenomena In this paper, aspects of load sharing of a grid connected PV system are analyzed, and a strategy is proposed where the load sharing task can be undertaken controlling both modulation index and phase angle of the inverter It is seen that both real power and reactive var are affected upon change in index of modulation and phase angle of the PV inverter Analysis and simulation results are presented to demonstrate effectiveness of the proposed control technique