Network intrusion is an increasing major concern as we are rapidly advancing in technology. To detect network intrusion, Intrusion Detection Systems are required. Among the wide range of intrusion detection technologies, machine learning methods are the most appropriate. In this paper we investigated different machine learning techniques using NSL-KDD dataset, with steps of building a model. We used Decision Tree, Support Vector Machine, Random Forest, Naïve Bayes, Neural network, adaBoost machine leaning algorithms. At step one, one-hot-encoding is applied to convert categorical to numeric features. At step two, different feature scaling techniques, including normalization and standardization, are applied on these six selected machine learning algorithms with the encoded dataset. Further in this step, for each of the six machine learning algorithms, the better scaling technique application outcome is selected for the comparison in the next step. We considered six pairs of better scaling technique with each machine learning algorithm. Among these six scaling-machine learning pairs, one pair (Naïve Bayes) is dropped for having inferior performance. Hence, the outcome of this step is five scaling-machine learning pairs. At step three, different feature reduction techniques, including low variance filter, high correlation filter, Random Forest, Incremental PCA, are applied to the five scaling-machine learning pairs from step two. Further in this step, for each of the five scaling-machine learning pairs, the better feature reduction technique application outcome is selected for the comparison in the next step. The outcome of this step is five feature reduced scaling-machine learning pairs. At step four, different sampling techniques, including SMOTE, Borderline-SMOTE, ADASYN are applied to the five feature reduced scaling-machine learning pairs. The outcome of this step is five over sampled, feature reduced scaling-machine learning pairs. This outcome is then finally compared to find the best pairs to be used for intrusion detection system.

The article examines the scientific and methodological basis of a comprehensive assessment of threats and damage to information systems of the digital economy. The information infrastructure and tasks of the digital economy have been defined. Sources of information security in the digital economy sectors and their information security requirements have been studied. The results of the analysis of the situation in the countries of the world on the Global Cyber security Index are shown schematically. The graph of the dynamics of cybersecurity expenditures in the ICT segments is shown. It is argued that cybersecurity, which is formed and developed through the use of digital systems, is a priority. Many goals and methods of cyber-attacks are given on the platform of the 4.0 Industrial revolution. Cases of information security violations in the digital economy and the processes of assessing the damage caused by them have been studied. Generalized criteria for assessing information damage in the digital economy have been proposed. Threats to information and communication systems and classification of damage are given. A structural scheme of the conceptual model of threats and damage to information systems and resources in the field of digital economy of Azerbaijan has been proposed. An expert description of the ways in which information threats are disseminated has been developed using a fuzzy approach. The main types of damage caused by threats to the security of information systems are given. The security aspects of the abundance and surplus of information in the digital economy are shown. The directions of increasing the level of security and confidence in the digital economy and the structures to ensure its security are given. The main directions of information security in the digital economy have been identified, the directions of ensuring its security and increasing its confidence have been identified. Commonly used universal base technologies have been proposed in the digital economy sectors. Some methodological approaches to integrated risk and damage assessment in the digital economy have been explored. A scientific-methodological approach based on fuzzy methods has been proposed for the implementation of complex risk and damage assessment in the digital economy.

With the increase in the availability of skilled software engineers, the process of global software development is being increasingly adopted by organizations, at a relatively lesser cost. This has led to software processes being more viable in a progressive manner for several reasons that include better communication technologies and the levels of maturity seen in the software industry.
That being said, Organizations that undertake the decision of adopting Global software development should realize that this process isn't exactly a risk-free action and there have been many failures reported with regard to it. The existing bools of globally distributed projects portray a number of challenges. During the interactive phase, the need for particular consideration towards the requirements of the client and the globally dispersed distributed software provider teams has been indicated.
This paper makes use of surveys collected from IT professionals and people working in the software industry in order to present realistic insights gathered from them.

Registration of new students’ academic information is essential for every educational institute to continue their education at every semester level and go through their whole student life. And this registration information is used when they do their form fill up of consecutive semesters. Nowadays, almost all educational institutes are using paper based registration and form fill up systems which is prone to many human errors and very time consuming for both students, teachers as well as other related administrative bodies. In this paper, we developed a web based application for academic purposes to control and save student registration and form fill up data that will be helpful for students, teachers and admin authority to make the process easier, less time consuming and error free. There are four main types of users who can use this system: student, department authority, students’ hall authority and administrator. The student can submit their registration and form fill up information by using a web form. Moreover, he/she can download their admit card and registration form after the approval of the concerned authority. The students also can be able to do other module activities. The hall and department authority can use the system to approve the students' registration, semester examination form and to provide the students' attendance data. In addition, the department and hall authority has a choice to see all students’ academic information. Moreover, the system administrator controls the system by managing (add, delete, update) student, hall and department authority, exam or registration date, subjects of a particular semester, notice board of the institute, module and programme data. The administrator can also add and remove the running and passed student data. The students also can pay their semester fees by using an online banking system.

The study determined the effects of concept mapping and guided discovery instructional strategies on student’s learning achievement in Redox concept in Chemistry in Oyo State, Nigeria. The pretest-posttest control group quasi experimental design with 3x2 factorial matrix was adopted, while six schools with one intact class each; two each for experimental groups and two for control group were used. A total of 176 senior secondary school 2 Chemistry students participated in the study. A validated Chemistry Student Achievement Test (r = 0.77) was used for data collection, while Analysis of covariance and Bonferroni post hoc were used to analyze the data collected at 0.05 level of significance. There was a significant main effect of treatment (F(2, 175) =11.84; p<0.05, partial η2 = 0.13) on student’s achievement. The participants in concept mapping strategy obtained the highest post achievement mean score (12.71), followed by guided discovery instructional strategy (9.24) and conventional strategy (8.60) groups. There was no significant main effect of gender on student’s achievement. There was no significant two- way interaction effect of treatment and gender on student’s achievement in Redox concept of chemistry. Concept mapping and guided discovery instructional strategies enhanced student’s achievement in Redox concept of chemistry. It is therefore recommended that chemistry teachers should adopt these strategies to improve student’s achievement in Chemistry.