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Search Results: 1 - 10 of 6416 matches for " Md. Rabiul Islam "
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Association between Socio-Demographic Factors and Blood Sugar Levels in Type 2 Diabetes Mellitus Patients in Bangladesh  [PDF]
Md. Rabiul Islam
Journal of Diabetes Mellitus (JDM) , 2017, DOI: 10.4236/jdm.2017.73012
Abstract:
Background: The aim of the current study was to evaluate the anthropometric and demographic factors and their correlation with type 2 diabetes mellitus (T2DM) in Bangladesh. Methods: One hundred fourteen patients (70 males and 44 females) between 30 and 75 years of age from various areas of Bangladesh were screened for T2DM. Fasting blood sugar (FBS) was analyzed by using laboratory kits and spectrophotometric technique. Anthropometric and socio-demographic data were collected using a structured questionnaire. Body mass index (BMI) was calculated from weight (kg) and height (m) of the individual respondents. Physical activity was categorized based on activity during daily work. Economic condition is defined by respective family income and education level is categorized into 3 levels: illiterate, 0 - 12 years of education and graduate or above. Results: According to the current study results, half of the patients were from the middle-class family with low physical activity and their age was within the range of 30 - 45 years. The male and female ratio of the study population was 60:40. Most of the patients were found to be obese and educated. Urban populations were more prone to have DM than the rural population. Age, education, the area of residence (urban and rural), physical activity and co-morbid diseases were significantly correlated with T2DM in Bangladesh (P < 0.05). Conclusion: Our study shows that different socio-demographic factors have a significant correlation with T2DM in Bangladesh. Diabetes awareness, early diagnosis, patient education and life-style modification can be initiated to manage T2DM efficiently.
Profiling of Serum Immunoglobulins in Bangladeshi Major Depressive Disorder Patients  [PDF]
Waheeda Nasreen, Mohammad Fahim Kadir, James Regun Karmoker, Md. Reazul Islam, Md. Rabiul Islam
Health (Health) , 2018, DOI: 10.4236/health.2018.109090
Abstract: Background: Major Depressive Disorder (MDD) is a mental disorder characterized by a pervasive and persistent low mood which is accompanied by low self-esteem and loss of interest or pleasure in day to day activities that adversely affects a person’s family, work, and personal life. There is no sufficient laboratory test for the diagnosis of MDD and it is expected that this investigation may be helpful for better diagnosis and management of MDD. We aimed to measure serum immunoglobulin levels in MDD patients and control subjects to meet the above demand. Methods: For this purpose, we recruited 88 MDD patients from the department of psychiatry, Bangabandhu Sheikh Mujib Medical University, Dhaka and 89 healthy volunteers from Dhaka city matched with age, sex and socioeconomic status to the patient group. Turbidimetry method was applied to measure serum levels of immunoglobulin A, G, and M where immunoglobulin kit was utilized. Results: The current study revealed that mean serum concentrations of immunoglobulin A, G, and M in patients were found to be 209.07 ± 104.93, 791.50 ± 235.67 and 107.92 ± 47.53 mg/dL while those were 195.34 ± 92.16, 763.81 ± 175.89 and 99.17 ± 48.78 mg/dL in control subjects, respectively. Conclusion: Our result indicates that serum concentrations of immunoglobulin A, G and M were not significant between the groups and further studies are required to establish these findings.
Synthesis of isatin, 5-chloroisatin and their 2-1,3,4 oxadiazoline derivatives for comparative cytotoxicity study on brine shrimp
Md. Rabiul Islam and Mohammad Mohsin
Bangladesh Journal of Pharmacology , 2007,
Abstract: Isatin (3a), isatin 3-carbohydrazone (4a), 5-spiro (isatin) 2-(N-acetyl hydrazino) 4-(N-acetyl)- 2-1,3,4 oxadiazoline (5a), and 5-spiro (isatin) 2-hydrazino- 2-1,3,4 oxadiazoline (6a) have been synthesized from unsubstituted oximinoacetanilide (2a). 4-Chlorooximinoacetanilide (2b), 5-chloroisatin (3b), 5-chloroisatin 3-carbohydrazone (4b) and 5-spiro (5 -chloroisatin) 2-(N-acetyl hydrazino) 4-N-acetyl 2-1,3,4 oxadiazoline (5b) compounds have been synthesized from p-chloroaniline. The structures of the products have been characterized from spectral analysis and comparative cytotoxicity study of them was studied.
Smooth maps of a foliated manifold in a symplectic manifold
Mahuya Datta,Md. Rabiul Islam
Mathematics , 2007,
Abstract: The immersions of a smooth manifold $M$ in a symplectic manifold $(N,\sigma)$ inducing a given closed form $\omega$ on $M$ satisfy the $C^0$-dense $h$-principle in the space of all continuous maps which pull back the deRham cohomology class of $\sigma$ onto that of $\omega$. In this paper we prove a foliated version of this result due to Gromov.
Prescribing Practice of Antidepressant Drugs at Outpatient Department of a Tertiary Care Teaching Hospital in Bangladesh  [PDF]
Md. Rabiul Islam, Ayeshi Shafique
Open Journal of Depression (OJD) , 2017, DOI: 10.4236/ojd.2017.61002
Abstract: Objectives: In Bangladesh 16.05% of adult population suffer from psychiatric illness of which 28.7% suffer from Major Depressive Disorder (MDD). Although antidepressants are the recommended first-line pharmacological treatments for MDD, their prescribing patterns have not been studied in Bangladesh. This study investigates antidepressant prescription patterns at the outpatient psychiatry department of Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh. Material and methods: A retrospective review of the case notes of psychiatry outpatients at BSMMU was carried out between April 2014 and December 2015. A total of 281 MDD patients (aged 18 to 60 years) were randomly recruited. Relevant information was obtained by collection of prescription details from the patients or their relatives by face to face interview. Results: The average number of drugs prescribed per prescription was 2.4. Antidepressants were prescribed in 83.6% (235) encounters that constituted 76.5% (235) of the total number of prescribed drugs. About 82.5% (232) antidepressants were prescribed in combination with psychotherapy. Nearly 50% (141) of prescribed antidepressants were selective serotonin reuptake inhibitors (SSRIs). Among all antidepressant classes, escitalopram (22.1%), mirtazapine (21.4%), and sertraline (16.4%) were the leading drug prescribed. Lithium was prescribed to 4.6% (13) of patients. Conclusion: Novel antidepressant (SSRIs and SNRIs) drugs were prescribed more compared to traditional drugs (TCAs and TeCAs). In many cases, antidepressants were prescribed in combination with psychotherapy which is good practice to treat depression. It is expected that this investigation will be helpful to treat MDD patients with more precision in drug assortment and benefit to the patients.
Improvement of Text Dependent Speaker Identification System Using Neuro-Genetic Hybrid Algorithm in Office Environmental Conditions
Md. Rabiul Islam,Md. Fayzur Rahman
International Journal of Computer Science Issues , 2009,
Abstract: In this paper, an improved strategy for automated text dependent speaker identification system has been proposed in noisy environment. The identification process incorporates the Neuro-Genetic hybrid algorithm with cepstral based features. To remove the background noise from the source utterance, wiener filter has been used. Different speech pre-processing techniques such as start-end point detection algorithm, pre-emphasis filtering, frame blocking and windowing have been used to process the speech utterances. RCC, MFCC, ^MFCC, ^^MFCC, LPC and LPCC have been used to extract the features. After feature extraction of the speech, Neuro-Genetic hybrid algorithm has been used in the learning and identification purposes. Features are extracted by using different techniques to optimize the performance of the identification. According to the VALID speech database, the highest speaker identification rate of 100.000% for studio environment and 82.33% for office environmental conditions have been achieved in the close set text dependent speaker identification system.
Cytotoxicity study of some indophenines and isatin derivatives
Md. Mahbubul Hoque,Md. Rabiul Islam
Bangladesh Journal of Pharmacology , 2008,
Abstract: Eight indophenines were synthesized for the interest of studying biological activity especially for cytotoxicity. The cytotoxicity of some indophenines and some isatin derivatives was studied by the brine shrimp lethality bioassay. It was observed that all the indophenines from thiophene, thiazol and isatin derivatives showed potential cytotoxicity against brine shrimp nauplii and the Structure Activity Relationships (SAR) of these compounds have been reported.
Feature Fusion Based Audio-Visual Speaker Identification Using Hidden Markov Model under Different Lighting Variations
Md. Rabiul Islam,Md. Abdus Sobhan
Applied Computational Intelligence and Soft Computing , 2014, DOI: 10.1155/2014/831830
Abstract: The aim of the paper is to propose a feature fusion based Audio-Visual Speaker Identification (AVSI) system with varied conditions of illumination environments. Among the different fusion strategies, feature level fusion has been used for the proposed AVSI system where Hidden Markov Model (HMM) is used for learning and classification. Since the feature set contains richer information about the raw biometric data than any other levels, integration at feature level is expected to provide better authentication results. In this paper, both Mel Frequency Cepstral Coefficients (MFCCs) and Linear Prediction Cepstral Coefficients (LPCCs) are combined to get the audio feature vectors and Active Shape Model (ASM) based appearance and shape facial features are concatenated to take the visual feature vectors. These combined audio and visual features are used for the feature-fusion. To reduce the dimension of the audio and visual feature vectors, Principal Component Analysis (PCA) method is used. The VALID audio-visual database is used to measure the performance of the proposed system where four different illumination levels of lighting conditions are considered. Experimental results focus on the significance of the proposed audio-visual speaker identification system with various combinations of audio and visual features. 1. Introduction Human speaker identification is bimodal in nature [1, 2]. In a face-to-face conversation, we listen to what others say and at the same time observe their lip movements, facial expressions, and gestures. Especially, if we have a problem in listening due to environmental noise, the visual information plays an important role for speech understanding [3]. Even in the clean environment, speech recognition performance is improved when the talking face is visible [4]. Generally, it is true that audio-only speaker identification system is not sufficiently adequate to meet the variety of user requirements for person identification. The AVSI system promises to alleviate some of the drawbacks encountered by audio-only identification. Visual speech information can play an important role in the improvement of natural and robust human-computer interaction [5, 6]. Indeed, various important human-computer components, such as speaker identification, verification [7], localization [8], speech event detection [9], speech signal separation [10], coding [11], video indexing and retrieval [12], and text-to-speech [13], have been shown to benefit from the visual channel [14]. Audio-visual identification system can significantly improve the performance of
BPN Based Likelihood Ratio Score Fusion for Audio-Visual Speaker Identification in Response to Noise
Md. Rabiul Islam,Md. Abdus Sobhan
ISRN Artificial Intelligence , 2014, DOI: 10.1155/2014/737814
Abstract: This paper deals with a new and improved approach of Back-propagation learning neural network based likelihood ratio score fusion technique for audio-visual speaker Identification in various noisy environments. Different signal preprocessing and noise removing techniques have been used to process the speech utterance and LPC, LPCC, RCC, MFCC, ΔMFCC and ΔΔMFCC methods have been applied to extract the features from the audio signal. Active Shape Model has been used to extract the appearance and shape based facial features. To enhance the performance of the proposed system, appearance and shape based facial features are concatenated and Principal Component Analysis method has been used to reduce the dimension of the facial feature vector. The audio and visual feature vectors are then fed to Hidden Markov Model separately to find out the log-likelihood of each modality. The reliability of each modality has been calculated using reliability measurement method. Finally, these integrated likelihood ratios are fed to Back-propagation learning neural network algorithm to discover the final speaker identification result. For measuring the performance of the proposed system, three different databases, that is, NOIZEUS speech database, ORL face database and VALID audio-visual multimodal database have been used for audio-only, visual-only, and audio-visual speaker identification. To identify the accuracy of the proposed system with existing techniques under various noisy environment, different types of artificial noise have been added at various rates with audio and visual signal and performance being compared with different variations of audio and visual features. 1. Introduction Biometric authentication [1] has grown in popularity as a way to provide personal identification. Person’s identification is crucially significant in many applications and the hike in credit card fraud and identity thefts in recent years indicate that this is an issue of major concern in wider society. Individual passwords, pin identification, or even token based arrangement all have deficiencies that restrict their applicability in a widely networked society. Biometrics is used to identify the identity of an input sample when compared to a template, used in cases to identify specific people by certain characteristics. No single biometrics is expected to effectively satisfy the needs of all identification applications. A number of biometrics have been proposed, researched and evaluated for authentication applications. Each biometrics has its strengths and limitations, and accordingly, each
Codebook Design Method for Noise Robust Speaker Identification based on Genetic Algorithm
Md. Rabiul Islam,Md. Fayzur Rahman
Computer Science , 2009,
Abstract: In this paper, a novel method of designing a codebook for noise robust speaker identification purpose utilizing Genetic Algorithm has been proposed. Wiener filter has been used to remove the background noises from the source speech utterances. Speech features have been extracted using standard speech parameterization method such as LPC, LPCC, RCC, MFCC, (delta)MFCC and (delta)(delta) MFCC. For each of these techniques, the performance of the proposed system has been compared. In this codebook design method, Genetic Algorithm has the capability of getting global optimal result and hence improves the quality of the codebook. Comparing with the NOIZEOUS speech database, the experimental result shows that 79.62 percent accuracy has been achieved.
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