Volume 20, Issue-1, June 2023

Permanent URI for this collectionhttp://dspace.iiuc.ac.bd/handle/123456789/8286

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    MOOCs for professional development in Bangladesh: Difficulties and conveniences
    (International Islamic University Chittagong, 2023-07) Ullah, Md. Mohib
    The Massive Open Online Courses (MOOCs) that aim at developing teachers' efficiency have been gaining popularity worldwide. Besides enhancing teachers' knowledge and skills, MOOCs bring a qualitative change in learning and teaching in the educational arena. This qualitative study investigated the difficulties teachers faced in taking MOOCs, the convenience of taking MOOCs by attending camps, and the notable changes in teaching after taking MOOCs. Out of thirty-nine EFL Teachers who in 2018 attended two MOOC camps sponsored by the U.S. Department of State, seventeen participated in this research. The findings reported that teachers' challenges were primarily technical, technological, procedural, and time constraints. However, taking MOOCs by attending camps was convenient for mutual support, motivation, and best learning practices. The results showed that MOOCs helped teachers raise learners' intercultural awareness, develop content knowledge, facilitate C.T. skills, and interact more in the EFL classroom. The findings will help policymakers and teacher educators to use MOOCs more effectively for teachers' continuous professional development.
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    In vitro drug-drug interaction study between Ranitidine Hydrochloride and Bisoprolol fumarate
    (International Islamic University Chittagong, 2023-07) Chowdhury, Kazi Ashfak Ahmed
    The current study's objective is to assess the pharmacological interactions between Bisoprolol fumarate and Ranitidine hydrochloride using in vitro model. Using the Job's approach and Ardon's method, a spectral observation research, and the thin layer chromatography method, interactions between bisoprolol fumarate and ranitidine hydrochloride were assessed. UV-VIS spectrophotometers were used for spectral observation in both acidic and basic pH conditions. Different spectra from the individuals and 1:1, 1:2, and 2:1 complexes were obtained in the UV-VIS spectrophotometer. The drug complexes produced a distinct spectrum than its pure component. When Ranitidine hydrochloride is combined with Bisoprolol fumarate at a 1:1 ratio, the spectra suddenly alters as a result of interaction. The stability constant values at various levels of pH (1.2, 2.0, 3.0, 5.5, and 6.4) determined by the Ardon's plots are 0.896, 1.612, 1.200, 1.36, and 0.294. According to the stability constant values, Bisoprolol fumarate and Ranitidine hydrochloride interact in a moderately stable manner. Because of this, the complex displayed fluctuating activity during the test.
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    A geometrical feature-based framework for pedestrian crossing recognition
    (International Islamic University Chittagong, 2023-07) Md. Khaliluzzaman
    In this work, a framework for the recognition of pedestrian crossing (PC) regions based on geometrical features is proposed. A distinctive feature of a pedestrian crossing (PC) is that each end point of the horizontal strip edges at pedestrian crossings intersects with a vertical stripe width edge, which comprises two connected points (2CP). Another unique feature of PC is that the PC stripe's edges are formed in ascending parallel order. These two features are utilized to identify the PC candidate region in the PC image. Where the 2CP and parallel edge segment in sorted order is used to validate and justify the PC region. Finally, classifier support vector machine (SVM) confirms the potential PC region. Here, the features of the candidate area are extracted using the uniform rotationally invariant Local Binary Pattern (LBP). The proposed framework is tested with our own dataset, and the results reveal significant improvement over previous work.
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    A study of in-vivo antidepressant, antidiarrheal and ex-vivo thrombolytic activities of methanol extract of Mikania micrantha leaves
    (International Islamic University Chittagong, 2023-07) Ali, Md. Hazrat
    Mikania micrantha (Asteraceae) has useful properties in the field of medicine. This study is aimed to elucidate the therapeutic potential of crude methanol extract of Mikania micrantha (MEMM) leave, on Swiss mice. The tests for antidepression potential were carried out using the model of both in-vivo forced swimming test (FST) and tail suspension test (TST). Again, the anti-diarrheal efficiency was carried out through the castor oil-induced diarrheal model; the clot-lytic property was investigated by thrombus dissolution property. The test samples showed dose¬dependent (200 mg/kg BW, 400 mg/kg BW) potentiality in antidepressant, anti-diarrheal and thrombolytic activities. MEMM demonstrated a significant increase in swimming tone and mobility in FST and TST. MEMM 400 (mg/kg; b.w.; p.o.) exhibited a significant reduction of diarrhoea over 4 hours. Besides, MEMM produced promising (400 (mg/kg; b.w.; p.o) 43.76 %) clot lysis activity. The observed results of this scientific investigation revealed the possibility of the suitable use of this plant and whether this plant is useful as a source of alternative medicine and new therapeutics.
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    Edible vegetable Roktoshirinchi (Achyranthes ferruginea Roxb.) ameliorates pain and inflammation in experimental animal model
    (International Islamic University Chittagong, 2023-07) Reza, A. S. M. Ali
    Achyranthes ferruginea, a plant commonly used in Bangladeshi traditional medicine, was investigated in this study to uncover new therapeutic applications. The research focused on assessing it’s in vitro anti-inflammatory properties and in vivo analgesic effects using a methanol extract. In vitro, the methanol extract of Achyranthes ferruginea was examined for its anti-inflammatory effects through membrane stabilization and protein denaturation tests using Human Red Blood Cells (HRBCs). The results indicated a moderate dose-dependent anti-inflammatory effect, with maximum inhibitions of 34.5% (protein denaturation) and 53.68% (membrane stability) at a concentration of 1000 μg/ml For in vivo assessments, Swiss albino mice were utilized, with Diclofenac Sodium as a positive control. The extract demonstrated significant dose-dependent analgesic effects in both chemically induced paw licking and writhing tests. Furthermore, molecular docking studies revealed a higher binding affinity of N-trans-feruloyl-4'-O-methyldopamine with COX-1 and COX-2 enzymes. Overall, Achyranthes ferruginea methanol extract exhibited moderate anti-inflammatory activity and robust analgesic properties, highlighting its potential therapeutic applications.
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    Path loss and group delay investigation for in-human body to on-human body transmission using dipole and loop antenna
    (International Islamic University Chittagong, 2023-07) Haque, Md. Ismail
    The most critical aspects for a successful transceiver design for wireless body area communication system are path loss and group delay investigation of the human body. In this research, we used a 150 mm length dipole and 40 mm diameter loop antenna to analyze path loss and group delay at 10-60 MHz HBC band for implant communication. An anatomical human body model in the near field constituency was used with FDTD simulations to build the path loss model. For a small dipole antenna, the path loss increases by an exponent of 6.62 with distance, especially along the height direction of the body, and the average group delay is in the order of 1ns. On the other hand, the average group delay is less than 1 ns and the path loss grows by an exponent of 4.65 for a loop antenna. Finally, it is demonstrated that both antennas have good accuracy and have no effect on data speeds below 20 Mbps but the loop antenna has a better overall performance in this investigation.
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    An effective and efficient protocol for propagating large files in Peer-to-Peer systems
    (International Islamic University Chittagong, 2023-12) Hoque, MD Jiabul
    Distributed Hash Tables (DHTs) are integral components in peer-to-peer systems, providing storage and lookup services for key-value pairs. While they have proven highly successful in managing and locating replicas of small files (typically under 1 MB), their efficiency in handling larger files diminishes. Factors like sluggish data senders and slow receivers further exacerbate the inefficiencies in peer-to-peer systems, causing delays in the file propagation process. To address these challenges, peer-to-peer systems require more efficient protocols and resources to expedite the handling of relatively large data files. This study introduces a novel, efficient, and effective mechanism to propagate substantial files within DHTs while balancing load and minimizing system overhead. To assess the proposed protocol's effectiveness, we evaluated using the PeerSim simulator. We analyzed two crucial metrics linked to our proposed system: overhead and propagation time. The outcomes of this research demonstrate a significant reduction in propagation time while system overhead remains minimal. Consequently, the proposed protocol can ensure seamless operation in real-world streaming applications.
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    A comparative study on machine learning algorithms for improved prediction measures for COVID-19
    (International Islamic University Chittagong, 2022-02) Rahman, Md. Ziaur
    The Corona-virus (COVID-19) is an emerging disease responsible for infecting millions of people since the first notification until nowadays. Corona virus causes respiratory ailment like influenza with symptoms for example, cold, coughs, fatigue, fever and gradually increases the breathing problem. The disease and symptoms are changing frequently thus due to time constraints it is literally impossible to test. Analysis of Covid-19 data using machine learning paradigm is becoming a major interest of the researchers in this situation. The aim of this study is to develop a better predicting model for Covid-19 patients. Patients feature can be assessed statistically and traditionally. But with this day and age of advanced machine learning approaches Covid-19 can be predicted using machine learning techniques with better accuracy. In this work four well known machine learning approaches was used for better prediction in Covid-19. However, this study focuses on optimizing machine learning approaches. Two optimization approaches employed for Grid Search and Random Search are used for fine tune in prediction.