Detecting Malicious Websites Using Machine Learning

The growing use of the internet resulted in emerging of new websites every day (Total number of Websites - Internet Live Stats, 2020). Web surfing has become important for everyone regardless of their occupation, age or location. However, as the use of the internet is increasing so is the vulnerability to malware attacks through malicious websites (Softpedia, 2016). Identifying and dealing with such malicious website has been quite difficult in the past as it is quite challenging to separate good websites from bad websites. However, by using machine learning algorithms on large datasets it is now possible to detect such websites beforehand. Classifiers trained using algorithms such as logistic regression and Support Vector Machine (SVM) can be used to detect malicious websites and the users can be warned about the risk before they visit such sites. This project focuses on using a variety of different classification algorithms to distinguish whether a website is malicious or not using the Kaggle Malicious and Benign Website Dataset. We have showcased that it is possible to detect malicious websites with a reasonable amount of certainty (90% of the 75 malicious websites in the test set were identified) using machine learning models. We have also determined the features that were critical in predicting the likelihood of a website being malicious. Most of our key features are easily available (URL Length, number of Special characters, Country, Age of website)

The New Construction Approach Adapted by Ashghal for the Public Projects in Qatar

"The purpose of this paper is to review the new strategy adapted by Ashghal to implement lean construction in Qatar to improve project performance and predictability of delivery. This is a significant change programme led by a government delivery entity. In 2017, the Public Works Authority (ASHGHAL) piloted the implementation of lean construction principles within 3 projects. Following realization of tangible benefits through the pilot application, Ashghal made it contractual to implement lean in all future projects. Since then, Ashghal has awarded 26 projects with the enhanced requirements in the construction contracts. The enhanced requirements within the construction contract are intended for improving public satisfaction and project delivery performance. This paper discusses the changes implemented by Ashghal and provides some recommendations. The paper presents findings from Literature reviews, interviews with Ashghal, and site visit to one of the projects undergoing the transformation. Qatar had not implemented lean construction principles at such large scale before 2018. Ashghal has realised various challenges in embedding the new strategy, which will be explored in this paper. Ashghal recognizes that the program requires time and effort, and has invested in building local capability. The enhanced requirements are applicable only to full infrastructure construction projects awarded post October 2018. Thereby the new approach is focused on contractors and supervision consultants’ way of delivery. There is scope however to expand the application of lean principles to improve internal processes. Other influencing government agencies could also benefit from this program. Finally, this paper presents the efforts by Ashghal in raising the bar of delivery in the state of Qatar and the region. It is a rare example of a public sector authority leading a major change initiative that can benefit all parties involved and especially in construction, which makes this a very unique and special case that deserves to be written about.

The Legal Framework of Electronic Data Crimes

In order to determine the legal framework of these crimes, we should distinguish between two types of crimes or attack electronic data, the first type when the technology of electronic data process and telecommunication have used in remote to commit crimes. In other words these crimes are committed through computer and the criminal description of these businesses belongs to the known of types of traditional crimes like theft, fraud and other crimes. This type of crimes call un informatics in the global information network “ internet” also this field includes the crimes of usage of “internet” and electronic data processes tools to show the pornographic images or diffusion a messages which are inciting to racism, racial, religious, discrimination or exposure to the personal liberty or intellectual property. The second types of electronic data process crimes when the technology of the electronic data and telecommunications are on remote and make it as a means of this crimes and their purpose too. And now we are in front of anew criminal acts which associated mostly to the exposure of security and integrity of electronic data systems and the confidentiality of the data and information that consist on. And this type of criminal information network called “internet”, this is done in the case of illegal entry in to these systems and exposure to it or to the information that contain it. So this research will base on the electronic data crimes which are connected to the internet, when it becomes a direct target and a goal in their contents, and regardless on the impulsive of behind of committing

Understanding the Relationship Between Use of Innovative Technology and Employee Performance: A Case of the Bank of Jordan

Technological implementation and innovation are considered highly critical in today’s competitive and dynamic business environment. This study aimed at analysing the role of innovative technology and work practices on employee performance within the Bank of Jordon. Quantitative methods aligned with survey technique were used to gather data from managerial and non-managerial staffs of the bank. A close ended questionnaire was used for data collection. Further, statistical analysis using correlation and regression was used to explore research objectives comprehensively. This study found positive correlation between technology implementation, innovative work practices, employee attitudes and employee performance.  Employee attitudes were least correlated with performance outcomes. Further, results suggest that innovative technology implementation, work practices and employee attitudes have significant impact on employee performance within the Bank of Jordon. The results of study are not generalisable considering the methodological limitations and sample size. Further researchers can expand scope of this study by incorporating large samples by taking into account triangulation approach. Keywords: Innovative technology, Employee performance, Bank of Jordo

How an Innovative Climate can motivate an Entrepreneur

This is a theoretical paper of a conceptual model whose primary aim is to test, how innovative climate, Perceived Net Desirability of Self Employment (NDSE), Tolerance for Risk (TR), and Perceived Feasibility (self-efficacy) of self-employment (SE), could affect self-employment intentions.  The model also proposes how Psychological Climate Adjustment, Emotional stability, and Openness to experience, impacts perceptions of the innovative climate of organizations

The Impact of the Application of International Accounting Standard 34 (IAS 34) on the Industrial Public Shareholding Companies’ Sector in Jordan

This study aims at identifying the extent to which IAS 34 (Interim financial reporting) is applied in the Jordanian public shareholding companies, along with highlighting the impact of its application on individual investors at these companies. Study population consists of all Jordanian public shareholding industrial companies (45 companies) listed at Amman Stock Exchange. Due to the large number of the study population, preparers of financial statements (employees of companies), and individual investors, we have selected a simple random sample. The total number of preparers of financial statements (employees), and individual investors were (500) individuals who were selected for the sample. The results showed that all companies are committed to issue and publish interim financial reports within the period specified for that purpose. There is a statistically significant relationship between the variables relevant to the company including (the firm's nature, profitability, and age) and the compliance with issuing the reports and the information content of the financial statements. Moreover there are statistically significant differences in the extent to which IAS 34 is applied in the Jordanian public shareholding companies. These differences arise due to the personal and occupational characteristics of the preparers of financial statements (gender, age, qualification, position, and experience)

Factors Affecting Knowledge, Attitude, and Practice of COVID-19: A Study Among Undergraduate University Students in Bangladesh

The global expansion of the COVID-19 outbreak is one of the worst disasters the world has faced in recent decades. This study explored various factors of knowledge, attitude, and practice regarding COVID-19 among Bangladeshi undergraduate university students. In addition, we also look at how COVID-19 based knowledge, attitude, and practice influence each other. Using a random sampling technique and a self-administered structured questionnaire survey, this study collected data from 167 private university students in Bangladesh from 1st October to 30th October 2020. Data were analyzed using descriptive statistics (including frequencies, percentages, and means), binary logistic regression, bivariate regression analysis, and factor analysis. The findings suggest that most of the students learned about COVID-19 from various sources, including news media (TV, radio, newspapers, etc.), international organizations (WHO, UN, etc.), various government programs, or from their friends, family members, or neighbors. Most of the students were concerned about becoming sick, keeping social distance, and family members’ job insecurity, followed by the university shutdown and the subsequent quarantine. Many students believe Bangladesh’s media, government, medical sector, and religious organizations played a significant role during COVID-19. Binary logistic regression demonstrates that students’ gender, department, and residency significantly explained their COVID-19 knowledge. In addition, students’ attitudes significantly vary with their religion and place of residence. Students’ departments and semesters found significant in explaining their practice regarding COVID-19. Moreover, factor analysis results also identified several crucial factors in explaining students’ overall knowledge, attitude, and practice of COVID-19. Finally, we found a statistically significant relationship between knowledge, attitude, and practice

The Effects of Emotional Intelligence on Job Satisfaction

Emotional Intelligence (EI) becomes a key element in organisation’s success and one of must-have skills and capabilities- among other things- needed by leaders and followers in the workplace to encounter the environment changes and do as possible as they could to gain the organisation commitments that could lead to organisation’s success. It is also found that there is a strong relationship between emotional intelligence and job satisfaction and organisation commitment. Hence, the higher employees’ EI scores, the more performance and commitment towards organisation. Emotional intelligence is also a key component to job satisfaction. Therefore, this paper presents a review on Emotional Intelligence (EI) and its effects on job satisfaction. Therefore, the main purpose of this paper is to investigate the relationship between emotional intelligence job satisfactions. The findings of this paper are that in any organisation, emotional intelligence has a strong relationship with job satisfaction. It is also found that the higher employees’ EI scores, the higher performance and commitment towards organisation. Key Words: Emotional Intelligence, Job Satisfaction

Automatic detection of potential buried archaeological sites in Saruq Al-Hadid, United Arab Emirates

The use of remote sensing in archaeological research allows the prospection of sub-surfaces in arid regions non- intrusively before the on-site investigation and excavation. While the actual detection method of expected buried archaeological structures is based on visual interpretation, this work provides a supporting archaeological guidance using remote sensing. The aim is to detect potential archaeological remains underneath the sand. This paper focuses on Saruq Al-Hadid surroundings, which is an archaeologist site discovered in 2002, located about 50 km south-east of Dubai, as archaeologists believe that other archaeological sites are potentially buried in the surroundings. The input data is derived from a combination of wavelength L-band Synthetic Aperture Radar (ALOS PALSAR), which is able to penetrate the sand, and multispectral optical images (Landsat 7). This paper develops a new strategy to help in the detection of suspected buried structures. The data fusion of surface roughness and spectral indices enables tackling the well-known limitation of SAR images and offers a set of pixels having an archaeological signature different from the manmade structures. The potential buried sites are then classified by performing a pixel-level unsupervised classification algorithm such as K-means cluster analysis. To test the performance of the proposed method, the results are compared with those obtained by visual interpretation