AIUB Journal of Science and Engineering (AJSE)

A Medical Cyber-Physical System utilizing the Bayes algorithm for post-diagnosis patient supervision

Fri, 30 Aug 2024 00:00:00 +0600

Among several basic human needs, medical treatment is one of the most prominent. However, since there need to be more doctors, nurses, and other medical facilities in many places, medical cyber-physical systems are quickly becoming a competitive alternative. One important use of these systems is for observation after a diagnosis. Instead of active observation by a caregiver, this can be easily done using various monitoring systems. However, most of the existing systems for this application are inflexible and need to consider the current challenges. On the other hand, these problems can be solved by intelligent and adaptive systems, which is now possible thanks to the growth of relevant technology, especially healthcare 4.0. Therefore, this article proposes an adaptive system based on the Bayes algorithm for performing medical interventions on patients, leading to a reduction in the dependence on caregivers, particularly in the post-diagnosis scenario.

Design and Performance Analysis of Robust Adaptive Neuro-Fuzzy Inference System-Based Modified P&O Algorithm of MPPT Controller for a Solar PV System

Arnob Chandra Dafader, Md. Rifat Hazari, Shameem Ahmad, Mohammad Abdul Mannan — Fri, 30 Aug 2024 00:00:00 +0600

Perturb and observe (P&O) is a well-known maximum power point tracking (MPPT) algorithm that is used in solar photovoltaic (PV) systems to increase its efficiency. However, as the PV system uses solar irradiance and temperature for making electric power, the fast change of these two affects the performance of P&O and the efficiency of the PV system. Thus, the P&O algorithm fails to detect maximum power point (MPP) if temperature and irradiance change quickly. Therefore, this paper presents an adaptive neuro-fuzzy inference system (ANFIS) based P&O algorithm of MPPT controller for a solar PV system to solve the issues mentioned earlier. The utilization of the proposed ANFIS in the P&O algorithm can track the fast changes in solar irradiance and temperature to extract the maximum power from the solar PV panel. Comparative analysis has been done on MATLAB/Simulink software for both the traditional P&O and the proposed ANFIS-based P&O algorithm to show the effectiveness of the proposed MPPT controller.

The Impact of COVID-19 Outbreak on the Power Sector in Bangladesh: A Strategic Adoption for Any Pandemic Condition

Fri, 30 Aug 2024 00:00:00 +0600

In this research all the data sets were gathered during the COVID-19 outbreak. The study presented, however, is applicable to any pandemic scenario in Bangladesh or elsewhere. The lockdown has significantly reduced the demand for power worldwide and altered the makeup of the load and the daily load profile. This is because many offices have switched to home office strategy, which has shortened the operating schedule of many businesses. Considering this, many countries' adoption of lockdown measures to halt the spread of COVID-19 abruptly changed socioeconomic operations, including the power generation industries. To better understand the pandemic's impact on Bangladesh's fossil-fuel based power sector, this study examines renewable energy technologies' roles in creating climate resilient, sustainable energy routes. Research was done for the pandemic lockdown in 2020. Due to the lockdown situation, the power sector witnessed increased overcapacity, and revenue losses. This study looked at the implications on energy demand, load profiles, generation, consumption, generating mix, and expansion of renewable electricity generation. In addition, a suitable generation mix for Bangladesh has been suggested. This sector's resilience has also been assessed to overcome the pandemic crisis and any future pandemic-like emergency. In this research, a well-organized examination of the existing power sector overall plan has also been proposed, focusing on clean energy led power sector development.

Thermoexergetic analysis and multi-objective optimization of steam power plant performances

Mohamed Walid Azizi, Moumtez Bensouici, Fatima Zohra Bensouici — Fri, 30 Aug 2024 00:00:00 +0600

This study investigated the steam power plant performances using a response surface methodology (RSM). The thermodynamic simulations are conducted by the Engineering Equation Solver (EES) program for distinct parameters such as inlet temperature (350≤T3≤600°C), boiler pressure (5000≤P₃≤15000kPa), and condenser pressure (5≤T₁≤15 kPa). A centered composite design (CCD) with process parameters was used for statistical analysis. A second-order regression model was developed to correlate the process parameters with thermal efficiency (η_I), exergetic efficiency (η_II), vapor quality (x), and specific fuel consumption (SFC). A better determination coefficient (R²) was attained with the quadratic model, which showed 99.88%, 99.85%, 99.44%, and 99.80% for η_I, η_II, x, and SFC, respectively. Hence, numerical and graphical optimization was conducted operating the desirability function approach to get the suitable input variables to deliver the highest thermal and exergetic efficiencies with maximum vapor quality and minimal specific fuel consumption rate.

Design and Feasibility Analysis of a LoRa Based Communication System for Disaster Management

Fri, 30 Aug 2024 00:00:00 +0600

In the context of earthquake and flood disasters, effective communication remains a pivotal concern due to the vulnerability of conventional networks. This study presents a comparative analysis of off-grid communication technologies—namely WiFi and LoRa—with the aim of ascertaining their efficacy in addressing this challenge and proposes a LoRa rescue model. Critical parameters such as communication range, SNR (Signal to noise ratio), RSSI (Received Signal Strength Indicator) rate, data transmission speed, bandwidth, frequency, and reliability are evaluated. The outcomes of this investigation highlight the importance of alternative communication solutions when centralized networks falter. Particularly, the intrinsic attributes of LoRa exhibit potential for sustaining connectivity amidst network disruptions. These findings not only enrich the discourse on disaster management strategies but also offer insights into crafting adaptive and resilient communication systems. Informed decision-making regarding communication technology deployment in emergency contexts in order to make the rescue process convenient and reliable is the direct implication of this research.

Empirical Analysis of the SAC-OCDMA-WDM System by Leveraging the AND Subtraction Technique

Fahmidul Islam, Mohammad Nasir Uddin — Fri, 30 Aug 2024 00:00:00 +0600

This study used C-band carrier frequency to assess Spectral Amplitude Coding Optical Code Division Multiple Access or SAC-OCDMA systems using Fiber Bragg Gratings (FBG) as encoders and decoders by implementing the AND subtraction detection technique. The optical transmission distance, optical power, channel bandwidth, data rate, and number of channels are only a few of the many factors that affect how well a system performs. Numerous simulations have been conducted to analyze the influence of the above-mentioned parameters on the system’s performance. The proposed SAC-OCDMA system has been integrated with the Wavelength Division Multiplexing or WDM system to increase the active channel's quantity. The network has been designed and analyzed using commercially available Optisystem software. The proposed SAC-OCDMA system architecture with two channels stays within operational limit up to unrepeated transmission over 336 km at a data rate of 1.6 Gbit/s. These results were attained with the pre-FEC threshold. Further, the SAC-OCDMA system has been simulated up to a maximum of ten channels considering the pre-FEC bit error rate threshold. The obtained results have been compared with recently reported technical articles and found superior in terms of the number of channels and transmission distance. The proposed model obtained a superior data rate of 6.4 Gbps, and a maximum transmission distance of 24 km for 10-channel architecture.

A Numerical Analysis of Comparing Several Practical Approaches for Pricing both American and European Put Options

Afroza Akter, Salma Parvin — Fri, 30 Aug 2024 00:00:00 +0600

The present paper focuses on pricing with European or American put option that has yet to be studied. In solving option pricing problems, numerical methods form an essential part. Five numerical methods: Black-Scholes-Merton, Monte Carlo, Binomial, Trinomial, and Finite Difference have been implemented in the present work. Here Computer Algebra System (CAS) Python is used for the simulation. A comparison of these methods for both European and American put options has been shown by a graphical representation. Results show that Crank Nicolson Finite Difference Methods (FDM) gives us more accurate results than the other methods.

Machine Learning-based ECG Classification using Wavelet Scattered Features

Sree Janani K K, Sabeenian R.S — Fri, 30 Aug 2024 00:00:00 +0600

Cardiac abnormalities are one of the leading causes of mortality and morbidity among the population. Changes in the morphology and rhythm of the cardiac signals associated with cardiac abnormalities need to be identified and classified. Advances in artificial intelligence paves the way for precise classification. the preprocessed ECG signal segments undergo wavelet scattering to extract the low variance features with reduced dimension are rearranged and the key features are selected using Minimum Redundancy and Maximum Relevance (MRMR) feature selection algorithm chosen by comparatively analyzing different feature selection algorithms and the selected features are fed to the machine learning models. Classification of ECG signals is comparatively analyzed using different Machine Learning models such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision tree, and Artificial Neural Network (ANN) models with 10-fold cross-validation. the performance is improved by optimizing each model by tuning the hyperparameters. Among the twenty models, the cubic SVM model achieves the highest accuracy of 99.84 percent.

Datalogger prototyping for NH3 ground concentrations measures and comparison with NH3-IASI generated datamaps

Noureddine Benabadji, Farid Rahal, Imane Nadjah Menakh — Fri, 30 Aug 2024 00:00:00 +0600

Ammonia (NH₃) gas is dangerous as it is highly toxic and irritating and so, causes severe burning of the eyes and respiratory problems (throat and lung damages) when inhaled in high concentrations. It is a colorless gas, with a strong suffocating odor. It is also a flammable gas (and may form an explosive mixture with air, when heated), and can dissolve in water to form ammonium hydroxide solution, a highly corrosive agent for any metallic based structures like bridges, boats, water tanks, etc… It can also react with other atmospheric pollutants, primarily SO₂ and NOx, generating fine particulate matter which can pass through the lungs in blood. In the other hand, it is considered as an industrial useful hydrogen carrier of energy, and an additive to coal-fired power plants, and is slowly shifting from its natural use as fertilizer for agricultural industry to a “green and clean” fuel source. In this article, we describe in detail the use of an electrochemical sensor driven by a microcontroller. The principle of the measurement system is a chemical oxidation of catalyst metals, where conductivity varies with the target gas concentration. Mathematical calculations are also provided to convert the 10-bit numerical counts to meaningful NH₃ concentrations in ppm, taking into account the temperature dependency correction.

Impact of Si and GaAs as Semiconductor Materials: Designing to Application-Level Comparison

Syeda Fahima Nazreen, M Tanseer Ali — Fri, 30 Aug 2024 00:00:00 +0600

The semiconductor industry has been making life easier by providing loads of electronic devices. With the advancement of technology, electronic devices need to be updated. This gradual upgradation has led the industry towards nanotechnology. The study is to provide an analytical comparison of the impact of Si and GaAs as semiconductor materials in designing 3D density gradient nanowire MOSFETS. The model has been designed and evaluated on the basis of the characteristics curve and transconductance range. The drain current in the I_d-V_gand I_d-V_d curve for GaAs used model is higher than the Si used model by about 10 times which is useful for analog applications. The threshold voltage for both models is 0.7V. Besides that, the electron concentration forming a potential well of the depth of about 10⁴ for GaAs used material than the model made using Si as material. In the case of AC analysis, the transconductance range for the model using GaAs is almost double of the model designed using Si. Later on, the extracted data from the curves have been utilized to generate model and library files. Finally, an inverter circuit and biasing circuit have been designed with models where the output of the inverter circuit perfectly works. The frequency response curve generated using the biasing circuit showed the cut-off frequency of the GaAs used model is 10MegaHz whereas it is 1MegaHz for Si used model.