Approach to Implement Security In Service Oriented Architecture Using Deception Technique

Service Oriented Architecture is a relatively new field in computing. However, web services in a Service Oriented Architecture are usually open and vulnerable to attacks. Intrusion detection is a technique widely used for protecting web services. In this thesis, we use deception on top of Intrusion Detection in a Service Oriented Architecture. We implemented three attacks on web services, namely, SQL Injection attack, Brute Force attack and Insufficient Authorization attack. We developed algorithms to deceive against these attacks. From our result we saw that deception wastes the time and resources of the attacker and furthermore is able to reduce attacks by more than 90 percent. Deception is therefore complementary to intrusion detection and can be effectively used to protect web services.Computer Science Departmen

Female Workers' Attitudes on Industrial Disputes at RMG Sector in Bangladesh: An Empirical Analysis

Industrial disputes one of the important issues that hindrance the development of the sectoral growth. RMG sector in Bangladesh is mainly human resource especially women workers intensive industry and they have remarkable contribution in the economy of Bangladesh. Last few years this sector not contributing as much as we expected because of industrial disputes narrowing the performance of this sector. As the paramount proportion of human resources in garment sector are women workers, so their attitudes has significant impact on minimizing industrial disputes and increasing the productivity at garment industry in Bangladesh. In this study, we have attempted to measure the woman workers attitude on the industrial disputes and its minimization process for sustainable development of this sector. Mixed research methods were used to analyze female workers' attitudes toward the industrial disputes at RMG sector of Bangladesh

Virulence of entomopathogenic fungus, metarhizium anisopliae to sweetpotato whitefly, bemisia tabaci (hemiptera: aleyrodidae) under osmotic stress

The aim of the present study was to investigate the virulence of the entomopathogenic fungus Metarhizium anisopliae (isolates PR1 and GT3) under osmotic stress condition. The virulence study of the fungus was conducted by three ways—growth (germination, vegetative growth and sporulation); enzymatic activities (chitinase, protease and lipase) of M. anisopliae and percentage mortality of Bemisia tabaci to M. anisopliae. Conidia of M. anisopliae were produced under different osmotic stress conditions as SDA medium as control, SDA medium with 0.5 M NaCl, SDA medium with 0.5 M KCl, SDA medium with 1 M NaCl and SDA medium with 1 M KCl. The germination percentage, vegetative growth, sporulation, chitinase and protease activities were highest for control of PR1 isolate, reaching up to 97 %, 4.1 cm and 6.6 × 106 conidia/ml, 2.6 mU/ml and 1.7 µg/ml/min, respectively. These values decreased up to 86.7 %, 3.6 cm and 4.1 × 106 conidia/ml, 1.6 mU/ml and 1.0 µg/ml/min, respectively under osmotic stress. The lipase activity was highest for 0.5 M NaCl of PR1 isolate, reaching up to 18.2 µmol/ml/min. The mortality percentage of B. tabaci was highest for control of PR1 and GT3 isolates, reaching up to 83.9 and 83.8 %, respectively. These values decreased up to 77.4 and 77.5 %, respectively under osmotic stress. This paper concludes that both the isolate PR1 and GT3 are virulent to B. tabaci under osmotic stress condition

A Case Study of the Notion and Model of Micro Hydro Power Plant Using the Kinetic Energy of Flowing Water of Burinadi and Meghna River of Bangladesh

Bangladesh is progressing through a stage of development where automation is the solution to its economy. At this stage for the progression of this country electricity is very vital to sustain the economic growth. These days it becomes extremely challenging to cope up with the required energy demand of the country. Continuous increase in price of fuel in the world market and also the unavailability of fuel are the reasons behind this. On the other hand fuel burning in energy generation is responsible for global climate change and Bangladesh residing in high risk of this. Renewable energy can be an immense hope under this circumstance. The country is blessed with a good number of rivers consisting adequate flow of water throughout the year. Harnessing this driving water of rivers can be a great source of kinetic energy and utilizing this kinetic energy of driving water Hydro Electricity can be produced. In this paper the real life practical data of Burinadi and Meghna rivers were considered. A system is introduced that does not need the Dam or Reservoir to produce Electrical Power and is observed that 21.1 MW-hr and 12.48 MW-hr worth of energy can be produced annually from Burinadi & Meghna rivers respectively. This extent of power can be very useful for these rivers nearby inhabitants in remote areas as they are still out of national grid range

LEARNER ACUMENS OF ONLINE EFL CLASSES AT THE PRIVATE UNIVERSITIES IN BANGLADESH

This study intended to evaluate the English as Foreign Language (EFL) learner responses to online classes during the covid-19 pandemic. It focused on the learner's insights rather than the teachers' views because the purpose is how the large population deals with technology during this pandemic. Though teachers are the real fighters, they are in a vacuum without the students' engagement. Therefore, this study showed EFL learners' readiness of using technology in attending online classes and what barriers they face during assessment and classes. It examined whether students can participate in group discussions, pair work, online assessment, respond to class, build their rapport, and get proper feedback or not. Data were collected randomly using a google form questionnaire having five elementary questions, fifteen Likert-type questions from 92 students of five private universities in Bangladesh. Besides, five questions were finally added to have an overview of multiple response analyses. Some imperative variables of flexibility, reliability, availability, and integrity regarding online classes were brought into light with descriptive analysis. Finally, the data were analysed in a qualitative approach. It shows that learners attending online courses and assessments are diverse regarding the availability of required facilities, and the students are having difficulties participating in online examinations. The result further implicates ensuring an intelligent learning environment in the 'new normal period' with more efficacy. Article visualizations

可塑的シナプスのイメージングによる解析と工学応用

神経系の最大の特徴は、環境に応じて学習や記憶する柔軟性(可塑性) と、記憶 したことを忘れない頑強性（安定性）という相反する性質を併せ持つことです。神経細胞が他の神経細 胞に信号を伝える部分はシナプスと呼ばれ、その信号伝達効率が適当な条件刺激で変化するものが可塑 的シナプスです。近年、可塑的シナプスが脳神経系各部で発見され、神経可塑性の少なくとも一部は、 これらに依存するとされています。また、ロボットや自動診断装置など機械学習の分野でも、可塑性と 安定性のバランスは極めて重要で、可塑性が高いと学習は早いが過去の記憶を忘却し、安定性が高いと 学習が進まないという問題が生じています。本研究では可塑的シナプスの特性を実際の生物で実測する と共に、機械学習に相応しい数理モデルやアルゴリズムを開発しました。福井大学平成２２年度重点研究「重点研究育成経費

Problems and prospects of mobile banking in Bangladesh

The main objective of the study is to find out the problem and prospect of mobile banking in Bangladesh. For this research primary data were used. This study adopts with descriptive in nature. Total respondents were 120 within that 61 % respondents think it saves time than traditional banking, the highest number of respondents use mobile banking for Air-time top-up service, that is 21%, out of 120 respondents 56% replied it is less costlier than traditional banking, 100% respondents did agree that it is speedy, and 38% respondents are upper class. Although this concept is new in Bangladesh but its potentiality is high. From this research, other researchers and policy makers will get an insight about the problems and prospects of mobile banking in Bangladesh. Key words: Problem, prospect, Mobile banking

Isolation, screening and molecular identification of antagonistic bacteria against Colletotrichum gloeosporioides in mango

The study was conducted at the Postharvest and plant Biotechnology laboratory, Department of Horticulture, Patuakhali Science and Technology University, Patuakhali, Bangladesh during the period from January to July 2017 to isolate, screening and molecular identification of antagonistic bacteria against anthracnose of mango. All treatments were arranged in a completely randomized design (CRD) with replications and repeated twice. Epiphytic bacteria, isolated from leaf and fruit surfaces of mango, were tested as biocontrol agent against anthracnose disease caused by Colletotrichum gloeosporioides wherein 20 strains were confirmed as antagonistic. Molecular characterization of the three potential strains of bacteria were done by the amplification of 16S rDNA gene following the extraction of genomic DNA, polymerase chain reaction (PCR) amplification, gel electrophoresis and gel documentation. The PCR amplified products and the genomic DNA samples were sent to the Macrogen Company through Sunchon National University, Seoul, South Korea for molecular identification by sequence analysis. Among the 20 antagonistic bacteria screened in vitro by dual and concomitant tests, two isolates, namely GB6 (PSTU-Hort-8), and GB19 (PSTU-Hort-14) were recognized as antagonistics to the test fungus. Using the molecular identification systems, isolated bacterial strains PSTU-Hort-8 was identified as B. subtilis with National Center for Biotechnology Information (NCBI) accession numbers MW659188; on the other hand, strain PSTU-Hort-14 was identified as Stenotrophomonas rhizophila with NCBI accession number MW659190

Artificial intelligence-enabled rapid and symptom-based medication recommendation system (COV-MED) for the COVID-19 patients

In a general COVID-19 population in Cox’s Bazar, Bangladesh, we developed a medication recommendation system based on clinical information from the electronic medical record (EMR). Our goal was also to enable deep learning (DL) strategies to quickly assist physicians and COVID-19 patients by recommending necessary medications. The general demographic data, clinical symptoms, basic clinical tests, and drug information of 8953 patients were used to create a dataset. The learning model in this COVID-MED model was created using Keras (an open-source artificial neural network library) to solve regression problems. In this study, a sequential model was adopted. In order to improve the prediction capability and achieve global minima quickly and smoothly, the COVID-MED model incorporates an adaptive optimizer dubbed Adam. The model calculated a mean absolute error of 0.0037, a mean squared error of 0.000035, and a root mean squared error of 0.0059. The model predicts the output medications, such as injections or other oral medications, with around 99% accuracy. These findings show that medication can be predicted using information from the EMR. Similar models allow for patient-specific decision support to help prevent medication errors in diseases other than COVID-19