LIVIVO - Search results -

Search results

Result 1 - 10 of total 312

Search options

Article ; Online: A novel hybrid feature selection and ensemble-based machine learning approach for botnet detection.

Hossain, Md Alamgir / Islam, Md Saiful

2023 Volume 13, Issue 1, Page(s) 21207

Abstract: In the age of sophisticated cyber threats, botnet detection remains a crucial yet complex security challenge. Existing detection systems are continually outmaneuvered by the relentless advancement of botnet strategies, necessitating a more dynamic and ... ...

Abstract	In the age of sophisticated cyber threats, botnet detection remains a crucial yet complex security challenge. Existing detection systems are continually outmaneuvered by the relentless advancement of botnet strategies, necessitating a more dynamic and proactive approach. Our research introduces a ground-breaking solution to the persistent botnet problem through a strategic amalgamation of Hybrid Feature Selection methods-Categorical Analysis, Mutual Information, and Principal Component Analysis-and a robust ensemble of machine learning techniques. We uniquely combine these feature selection tools to refine the input space, enhancing the detection capabilities of the ensemble learners. Extra Trees, as the ensemble technique of choice, exhibits exemplary performance, culminating in a near-perfect 99.99% accuracy rate in botnet classification across varied datasets. Our model not only surpasses previous benchmarks but also demonstrates exceptional adaptability to new botnet phenomena, ensuring persistent accuracy in a landscape of evolving threats. Detailed comparative analyses manifest our model's superiority, consistently achieving over 99% True Positive Rates and an unprecedented False Positive Rate close to 0.00%, thereby setting a new precedent for reliability in botnet detection. This research signifies a transformative step in cybersecurity, offering unprecedented precision and resilience against botnet infiltrations, and providing an indispensable blueprint for the development of next-generation security frameworks.
Language	English
Publishing date	2023-12-01
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-48230-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article: Report of the 18th Asia-Oceania Congress of Medical Physics (AOCMP) in Conjunction with the 16th South-East Asia Congress of Medical Physics (SEACOMP).

Alamgir, Hossain Md

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics

2019 Volume 38, Issue 4, Page(s) 181

Language	English
Publishing date	2019-02-28
Publishing country	Japan
Document type	Journal Article
ISSN	1345-5354
ISSN	1345-5354
DOI	10.11323/jjmp.38.4_181
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Socio-economic status and pregnancy complications and their impact on antenatal care services provided at home and Upazila health complex.

Alamgir, Fariha / Hossain, Md Farhad / Ullah, Mohammad Safi / Hossain, Md Safayet / Hasan, Mahmud

Heliyon

2024 Volume 10, Issue 6, Page(s) e27716

Abstract: The stage of pregnancy is crucial for women of reproductive age and their families. However, in low- and middle-income countries like Bangladesh, antenatal and postnatal care are not widely practiced due to various socio-economic factors, such as low ... ...

Abstract	The stage of pregnancy is crucial for women of reproductive age and their families. However, in low- and middle-income countries like Bangladesh, antenatal and postnatal care are not widely practiced due to various socio-economic factors, such as low education levels, income, age, pregnancy knowledge, and limited healthcare facilities. The objective of this study was to examine the factors associated with antenatal care in two locations in Bangladesh based on the data collected from the Bangladesh Demographic and Health Survey (BDHS) 2017-2018. We explored different variables as explanatory variables related to ANC service. The results showed that most of the respondents were from rural areas, with 77.02% receiving antenatal care at home. Women with secondary education were more likely to receive care at home than those without education. The Chi-square test indicated a positive correlation between antenatal care at home with several variables, whereas, in the case of Upazila health complexes, only three variables showed a positive association. Logistic regression analysis further showed some specific variables such as geographical division, religion, iron intake during pregnancy, and reporting pregnancy complications had a significant impact on ANC at home. In contrast, covariates such as residence, division, and wealth index were significant for antenatal care at Upazila health complexes. The division was a significant covariate in both cases. Interestingly, we observed that mothers who had been informed about the signs of pregnancy complications were 92% more likely to receive antenatal care at home than those who had not experienced pregnancy complications. Conversely, the results revealed that mothers who were unaware of pregnancy complications were 32% more likely to receive antenatal care at home than those who had been informed about complications. This suggests that when women are educated about pregnancy complications, they are more likely to receive more antenatal care. However, Bangladesh's situation is quite different due to a lack of proper education and knowledge of antenatal care services.
Language	English
Publishing date	2024-03-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2024.e27716
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Social Media Stickiness in the Z Generation

Saiful Hoque / Md. Alamgir Hossain

Journal of Information Science Theory and Practice, Vol 11, Iss

A Study Based on the Uses and Gratifications Theory

2023 Volume 4

Abstract: The purpose of this study is to investigate how uses and gratifications motivations increase social media stickiness, with a special focus on media engagement as a key mediator. Data were gathered via a survey questionnaire from Bangladeshi Z Generation ... ...

Abstract	The purpose of this study is to investigate how uses and gratifications motivations increase social media stickiness, with a special focus on media engagement as a key mediator. Data were gathered via a survey questionnaire from Bangladeshi Z Generation social media users, which was quantitative in nature. For the analysis of 258 survey samples, structural equation modeling methodology was used. The results show that social media engagement and social media stickiness are positively impacted by uses and gratifications motivations such as social interaction, information, convenience, and entertainment. The study also found evidence of a relationship between uses and gratification motivations and social media stickiness, which is also mediated by emotional attachment. Understanding the motivations and gratifications sought by Z Generation users on social media platforms can help design strategies to enhance engagement and loyalty, ultimately leading to improved user retention and platform success. By identifying and addressing the specific needs and desires of the Z Generation, social media platforms can tailor their features, content, and user experiences to foster a stronger sense of connection and satisfaction, resulting in increased user engagement and prolonged usage.
Keywords	uses and gratifications motivations ; emotional attachment ; social presence ; social media stickiness ; Bibliography. Library science. Information resources ; Z
Subject code	360
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Korea Institute of Science and Technology Information
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: A Computational Approach for Identifying Potential Phytochemicals Against Non-structural Protein 1 (Nsp1) of SARS-CoV-2.

Hossain, Md Alamgir

Combinatorial chemistry & high throughput screening

2020 Volume 24, Issue 9, Page(s) 1482–1491

Abstract: Aim and objective: A recent study has revealed that non-structural protein 1 (Nsp1) of the SARS-CoV-2 is one of the novel targets for developing new antiviral drugs. To date, there is no significant exact medication available to treat Covid-19. As a ... ...

Abstract	Aim and objective: A recent study has revealed that non-structural protein 1 (Nsp1) of the SARS-CoV-2 is one of the novel targets for developing new antiviral drugs. To date, there is no significant exact medication available to treat Covid-19. As a result, both the death toll and the number of people affecting by this disease are increasing with each passing day. 35 phytochemicals having antiviral properties were taken to get the best compounds against Nsp1 Materials and Methods: As no PDB structure of this protein is available, homology modeling was done to predict the probable structure. After homology modeling, the best model was taken according to C-score and TM- score and then validated using different web servers. After validation, docking of these compounds was done using AutoDock vina, vega zz, and PyRx, and consensus docking score was considered to select molecules after docking. Finally, the orbitals energy calculation of these compounds was done to check their activity and the binding interactions of these molecules also analyzed. Results: Molecules having a consensus score of -8kcal/mol or more negative were kept for further study and it was seen that 16 molecules had the given criteria. Then, drug-likeness filtration was done according to Lipinski's rule of five and 11 molecules remained. Out of these 11 molecules, 5 molecules had satisfactory ADMET properties. Calculation of orbital energy revealed their activity. Conclusion: It is expected that this research might be helpful for the development of new antiviral drugs active against SARS-CoV-2 targeting Nsp1.
MeSH term(s)	Algorithms ; Antiviral Agents ; Binding Sites ; COVID-19/drug therapy ; Computational Biology ; Drug Development ; Drug Evaluation, Preclinical ; Humans ; Ligands ; Models, Theoretical ; Molecular Docking Simulation ; Phytotherapy/methods ; Plants, Medicinal/chemistry ; Predictive Value of Tests ; Reproducibility of Results
Chemical Substances	Antiviral Agents ; Ligands
Keywords	covid19
Language	English
Publishing date	2020-11-04
Publishing country	United Arab Emirates
Document type	Journal Article
ZDB-ID	2064785-2
ISSN	1875-5402 ; 1386-2073
ISSN (online)	1875-5402
ISSN	1386-2073
DOI	10.2174/1386207323999201103211106
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 5577: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A novel hybrid feature selection and ensemble-based machine learning approach for botnet detection

Md. Alamgir Hossain / Md. Saiful Islam

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 28

Abstract: Abstract In the age of sophisticated cyber threats, botnet detection remains a crucial yet complex security challenge. Existing detection systems are continually outmaneuvered by the relentless advancement of botnet strategies, necessitating a more ... ...

Abstract	Abstract In the age of sophisticated cyber threats, botnet detection remains a crucial yet complex security challenge. Existing detection systems are continually outmaneuvered by the relentless advancement of botnet strategies, necessitating a more dynamic and proactive approach. Our research introduces a ground-breaking solution to the persistent botnet problem through a strategic amalgamation of Hybrid Feature Selection methods—Categorical Analysis, Mutual Information, and Principal Component Analysis—and a robust ensemble of machine learning techniques. We uniquely combine these feature selection tools to refine the input space, enhancing the detection capabilities of the ensemble learners. Extra Trees, as the ensemble technique of choice, exhibits exemplary performance, culminating in a near-perfect 99.99% accuracy rate in botnet classification across varied datasets. Our model not only surpasses previous benchmarks but also demonstrates exceptional adaptability to new botnet phenomena, ensuring persistent accuracy in a landscape of evolving threats. Detailed comparative analyses manifest our model's superiority, consistently achieving over 99% True Positive Rates and an unprecedented False Positive Rate close to 0.00%, thereby setting a new precedent for reliability in botnet detection. This research signifies a transformative step in cybersecurity, offering unprecedented precision and resilience against botnet infiltrations, and providing an indispensable blueprint for the development of next-generation security frameworks.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Ensuring network security with a robust intrusion detection system using ensemble-based machine learning

Md. Alamgir Hossain / Md. Saiful Islam

Array, Vol 19, Iss , Pp 100306- (2023)

2023

Abstract: Intrusion detection is a critical aspect of network security to protect computer systems from unauthorized access and attacks. The capacity of traditional intrusion detection systems (IDS) to identify unknown sophisticated threats is constrained by their ...

Abstract	Intrusion detection is a critical aspect of network security to protect computer systems from unauthorized access and attacks. The capacity of traditional intrusion detection systems (IDS) to identify unknown sophisticated threats is constrained by their reliance on signature-based detection. Approaches based on machine learning have shown promising results in identifying unknown malicious attacks. No learning algorithm-based model, however, is able to accurately and consistently detect all different kinds of attacks. Besides that, the existing models are tested for a specific dataset. In this research, a novel ensemble-based machine-learning technique for intrusion detection is presented. Numerous public datasets and multiple ensemble strategies, including Random Forest, Gradient Boosting, Adaboost, Gradient XGBoost, Bagging, and Simple Stacking, will be employed to evaluate the performance of the proposed approach. The most relevant features for the detection of intrusion are selected using correlation analysis, mutual information, and principal component analysis. Our research using different ensemble methods demonstrates that the proposed approach using the Random Forest technique outperforms existing approaches in terms of accuracy and FPR, typically exceeding 99% with better evaluation metrics like Precision, Recall, F1-score, Balanced Accuracy, Cohen's Kappa, etc. This strategy may be a useful tool for strengthening the safety of computer systems and networks against emerging cyber threats.
Keywords	Intrusion detection system ; Feature extraction for IDS ; Ensemble-based approach ; Machine learning for IDS ; Computer network security ; Cyber attacks detection ; Computer engineering. Computer hardware ; TK7885-7895 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	006
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Urea- and Thiourea-Based Receptors for Anion Binding.

Kundu, Sanchita / Egboluche, Tochukwu Kevin / Hossain, Md Alamgir

Accounts of chemical research

2023 Volume 56, Issue 11, Page(s) 1320–1329

Abstract: ConspectusOver the past five decades, significant progress has been made in the field of anion recognition with a diverse variety of synthetic receptors because of the fundamental importance of anions in chemical, environmental, and biological processes. ...

Abstract	ConspectusOver the past five decades, significant progress has been made in the field of anion recognition with a diverse variety of synthetic receptors because of the fundamental importance of anions in chemical, environmental, and biological processes. In particular, urea- and thiourea-based molecules offering directional binding sites are attractive receptors for anions due to their ability to bind anions employing primarily hydrogen-bonding interactions under neutral conditions and have gained a recent paramount attention in the area of supramolecular chemistry. The presence of two imine (-NH) groups on each urea/thiourea functionality in these receptors gives them potential for excellent binding of an anion, mimicking the natural binding process in living cells. The increased acidity offered by thiocarbonyl groups (C═S) in a thiourea-functionalized receptor could enhance its anion binding ability as compared to its analogous urea-based receptor containing a carbonyl (C═O) group. During the last several years, our group has been involved in exploring a wide variety of synthetic receptors, and we have studied them with anions experimentally and computationally. In this Account, we will highlight the overall summary of our group's efforts focusing on anion coordination chemistry of urea- and thiourea-based receptors with varying linkers (rigid and flexible), dimensions (dipodal and tripodal), and functionalities (bifunctional, trifunctional, and hexafunctional). Depending on the linkers and attached groups, bifunctional-based dipodal receptors can bind anions forming 1:1 or 1:2 complexes. A dipodal receptor with flexible aliphatic or rigid
Language	English
Publishing date	2023-03-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	1483291-4
ISSN	1520-4898 ; 0001-4842
ISSN (online)	1520-4898
ISSN	0001-4842
DOI	10.1021/acs.accounts.2c00701
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: The Power of Live-Streaming in Consumers’ Purchasing Decision

Md. Alamgir Hossain / Abul Kalam / Md. Nuruzzaman / Minho Kim

SAGE Open, Vol

2023 Volume 13

Abstract: Livestreaming has gained popularity as a new e-commerce platform, communication tool, social network, and source of entertainment for millions of users. It is important to examine the nature and history of this developing area of e-commerce since it has ... ...

Abstract	Livestreaming has gained popularity as a new e-commerce platform, communication tool, social network, and source of entertainment for millions of users. It is important to examine the nature and history of this developing area of e-commerce since it has the potential to be exploited to overcome the COVID-19 pandemic’s challenges. Therefore, this study critically explores the consumer livestreaming purchasing behavior and proposes a model, which composed of stimulus, organism, and response as the extension of stimuli-organism-organism model. The structural equation modeling approach applies for analyzing 434 survey responses from a convenience sample. The results suggest that the stimulus variable (source credibility, response capability, platform interactivity) significantly affects the organism variables (customer engagement, swift guanxi), which in turn significantly contribute to creating responses (purchase intentions, actual purchase behavior). Customer engagement and swift guanxi also have potent mediating effects in the model. We offer novel insights into new consumer behaviors in livestream commerce that can underpin future research to promote businesses and services even under challenging conditions.
Keywords	History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	SAGE Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Functional Evaluation of Fermented Rice Bran and Extracted Rice Bran Oil Addressing for Human Health Benefit.

Alauddin, Md / Sultana, Afroza / Faruque, Md Omar / Islam, Fariha / Kabir, Md Alamgir / Shozib, Habibul Bari / Siddiquee, Muhammad Ali / Howlader, Md Zakir Hossain

Journal of oleo science

2024 Volume 73, Issue 4, Page(s) 467–477

Abstract: Rice bran (RB) and rice bran oil (RBO) are exploring as prominent food component worldwide and their compositional variation is being varied among the world due to regional and production process. In this study, Fermented Rice Bran (FRB) was produced by ... ...

Abstract	Rice bran (RB) and rice bran oil (RBO) are exploring as prominent food component worldwide and their compositional variation is being varied among the world due to regional and production process. In this study, Fermented Rice Bran (FRB) was produced by employing edible gram-positive bacteria (Lactobacillus acidophilus, Lactobacillus bulgaricus and Bifidobacterium bifidum) at 125×10
MeSH term(s)	Humans ; Rice Bran Oil/chemistry ; Fatty Acids, Unsaturated/analysis ; Antioxidants/analysis ; Vitamin E ; Phenols
Chemical Substances	Rice Bran Oil (LZO6K1506A) ; Fatty Acids, Unsaturated ; Antioxidants ; Vitamin E (1406-18-4) ; Phenols
Language	English
Publishing date	2024-04-01
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2218264-0
ISSN	1347-3352 ; 1345-8957
ISSN (online)	1347-3352
ISSN	1345-8957
DOI	10.5650/jos.ess23192
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito