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Mobile phone helps in communication and thus, lead to accessing information is gaining popularity in Bangladesh along with many developing countries.In the remote rural areas where mobile network is not up to the expectation yet and scarcity of information is a stark, rural farm women entrepreneur trying to seek information through mobile phone. The focus of the study was to determine the extent and types of information seeking through mobile phones by the rural farm women and explore the contribution of selected characteristics of the rural farm women on the extent of information seeking through mobile phones. The study was conducted in two geographic locations, in the Northern part of Bangladesh Doholpara, and Dakkhinkharibari village under DimlaUpazila, and in the Southern part Borokupot village of ShyamnagarUpazila. A multi-stage sampling technique was followed in conducting the study. The present study was conducted on 150 sampled rural farm women which comprised of 50 from each farm enterprise's crop, fisheries, and livestock. Data were collected by a pre-tested interview schedule that was prepared with simple and direct questions with different appropriate scales from September to December 2020. Along with descriptive statistics, correlation and multiple regression analysis were also performed. The major findings revealed that the majority of the rural farm women of each three farm enterprises (crop, fisheries, and livestock) in the study area were found in a category of those who seek agricultural information through mobile phone at a medium to a higher level. Findings also revealed that in all three agricultural farm enterprises, rural farm women mostly seek market information i.e. calling market centers, traders, and dealers for checking market price followed by collecting weather forecast and contact with experts during an emergency like information regarding diseases of fish, selection fish fries and contact with the veterinary surgeon or quack doctor regarding domestics animal. Among profile characteristics, family size, experience in managing the farm, attitude towards the mobile phone, and organizational participation were identified as the important contributing factors of the rural farm women in seeking information through mobile phone.

A novel compartmental model is proposed to project the COVID-19 dynamics in Bangladesh. The exposed population is divided into two classes: tested and not tested. Model parameters are estimated by fitting the output with empirical COVID-19 data of Bangladesh from 7 April 2020 to 15 June 2020. It is found that even if 90% of exposed individuals are tested, number of unidentified cases (recovered or dead) is 3 to 4 times than that of identified cases. As of 15 June 2020, Bangladesh is using the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) based test to detect the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The impact of false negative rate of this test on unidentified infection is analyzed. It is found that the year-end total recoveries (deaths) surges 700 (800) times if the false negative rate is doubled. Periodic lockdown and relaxation intervals are incorporated by defining the effective contact rate (β) as a periodic function of time. Impact of lockdown is perspicuous from the periodic fluctuation of the basic reproduction number ( ). It is observed that a 90-day-lockdwon reduces the final outcome by 3% while a 30-day-lockdwon increases it by 2%. On other hand, casualties are 10 to 100 times worse in case of no lockdown even with less than half effective contact rate. Analysis of strictness of isolation reveals that a 12.5% increase in the strictness coefficient reduces the exposed population 2.5 times whereas a 37.5% decrease in it intensifies the outcome nearly 9 times. Projections up to 6 April 2021 suggests that the epidemic will reach its peak in Bangladesh in August 2020.

The main purpose of this study was to determine the use and role of mobile phone for information services in agricultural activities as well as to explore the relationship between the socio-economic characteristics of women farmers and their use of mobile phone in agricultural activities. Data were collected using pre-tested interview schedule from a sample of 85 women farmers during the month of August 2018. Besides descriptive statistics, Pearson’s Product Moment Correlation Coefficient (r) was used to explore the significant influencing factors. Ten (10) different android mobile phone apps were identified which are most frequently used by the women farmers in the study area. Among the mobile apps, ‘vutta or maize app’ was found as the top used mobile app for information services in agricultural activities. This might be because of rapidly spreading of maize cultivation as a highly benefited cereal crops against the climatic change situation in the study area. Findings indicated that among the women farmers, majority (64.7 percent) of the women farmers used mobile phone moderately for information services in agricultural activities followed by 23.5 percent high and only 11.8 percent low used of mobile phone. Among ten socio-economic characteristics of the women farmers, education, annual income, organizational participation, training received and ICT self-efficacy had positive significant relationship and influence of the use of mobile phone in agricultural activities. ‘Insect and disease control measures’ was found the 1st ranked agricultural activities in which mobile phone played highest role for information services. It suggests that issues related to economic impact or effect of mobile phone on sustainable livelihood could be considered for future research to be undertaken.

The indispensability of information in agricultural development led to the setting up of Farmers’ Information and Advice Centres (FIACs) by the government of Bangladesh all over the country. The FIACs mainly provide information related to different agriculture sub-sectors like crop, fisheries and livestock with the overall aim of improving farmers’ livelihood. Hence, the effectiveness along with problems and suggestions for improvement of the FIACs’ services were examined in this study by surveying two FIACs of Dinajpur sadar upazila. The effectiveness of FIAC was determined on some selected farm (crop, fisheries and livestock) information based on three dimensions viz. information received, its understanding and application. Data were collected using interview schedule from a sample of 96 farmers selected by proportionate random sampling method. Descriptive statistics and Pearson’s Product Moment Correlation Coefficient (r) were used in the analysis. In terms of crop production sub-sector, all the respondents (100%) received, understood and applied ‘tomato seed production technology’ information, followed by ‘rice seed production and preservation technology’ (96.9%). Also, as for the livestock sub-sector, all the respondents (100%) received, understood and applied ‘beef fattening through UMS method’ information, followed by ‘livestock rearing’ (89.5%). Similarly, in case of fisheries sub-sector, all the respondents (100%) receive, understand and apply ‘Pangas (Pangasius pangasius) culture method’ information, followed by ‘preparation of an ideal pond’ (92.3%). In essence, the FIACs are quiet effective in their service delivery. Among the seven selected characteristics of the respondents, educational qualification, family income and perception on the service delivery efficiency of FIACs showed positive significant association with the effectiveness of the FIAC. However, the foremost problems mentioned by the respondents were FIACs staff inefficiency (83.33%) and lack of effective long term training program for both farmers and staff (73.84%). To address the identified problems, the respondents suggested recruitment of more staff (78.13%) and organizing more training programs for both staff and farmers (67.71 percent). Keywords: Effectiveness, Farmer, Information, Advice and centers

Nowadays addiction to drugs and alcohol has become a significant threat to the youth of the society as Bangladesh’s population. So, being a conscientious member of society, we must go ahead to prevent these young minds from life-threatening addiction. In this paper, we approach a machinelearning-based way to forecast the risk of becoming addicted to drugs using machine-learning algorithms. First, we find some significant factors for addiction by talking to doctors, drug-addicted people, and read relevant articles and write-ups. Then we collect data from both addicted and nonaddicted people. After preprocessing the data set, we apply nine conspicuous machine learning algorithms, namely k-nearest neighbors, logistic regression, SVM, naïve bayes, classification, and regression trees, random forest, multilayer perception, adaptive boosting, and gradient boosting machine on our processed data set and measure the performances of each of these classifiers in terms of some prominent performance metrics. Logistic regression is found outperforming all other classifiers in terms of all metrics used by attaining an accuracy approaching 97.91%. On the contrary, CART shows poor results of an accuracy approaching 59.37% after applying principal component analysis.

This paper designs and implements a high availability clusters and incorporated with load balance infrastructure of web servers. The paper described system can provide full facilities to the website hosting provider and large business organizations. This system can provide continuous service though any system components fail uncertainly with the help of Linux Virtual Server (LVS) loadbalancing cluster technology and combined with virtualization as well as shared storage technology to achieve the three-tier architecture of Web server clusters. This technology not only improves availability, but also affects the security and performance of the application services being requested. Benefits of the system include node failover overcome; network failover overcome; storage limitation overcome and load distribution., Comment: 6 pages. arXiv admin note: text overlap with arXiv:1311.3070 by other authors

IEEE802.11 wireless networks have become one of the most widely used networks. Due to open nature of wireless medium, hackers and intruders can make utilization of the loopholes of the wireless communication; as a result, there are many security threats associated with Wireless Local Area Network (WLAN). In this paper, we have worked an experimental analysis to study some of the well known attacks pertaining to IEEE 802.11 WLAN. At first, some of the open issues related to this fragile technology have been discussed. Based on this vulnerabilities and threats categories some of the major attack has been performed in a live environment by using open source software tools i.e Aircrak-nj, kismet. etc. The analysis and finding from this paper’s proved that the complexity of attacks had increased by time and the Wifi technology are becoming more dangerous to the end users and business environment.

Word completion and word prediction are two important phenomena in typing that have extreme effect on aiding disable people and students while using keyboard or other similar devices. Such autocomplete technique also helps students significantly during learning process through constructing proper keywords during web searching. A lot of works are conducted for English language, but for Bangla, it is still very inadequate as well as the metrics used for performance computation is not rigorous yet. Bangla is one of the mostly spoken languages (3.05% of world population) and ranked as seventh among all the languages in the world. In this paper, word prediction on Bangla sentence by using stochastic, i.e. N-gram based language models are proposed for autocomplete a sentence by predicting a set of words rather than a single word, which was done in previous work. A novel approach is proposed in order to find the optimum language model based on performance metric. In addition, for finding out better performance, a large Bangla corpus of different word types is used.