The Infosys TIMES, Vol. 5, No. 3

Chukwuemeka C. Monwuba wins Robert E. Applebaum Scholarship worth $12,000! Professor Lynn Collen accepts the position as the Chair of the IS Department Farewell to Professor Susantha Herath IS and IA students attend Student 360 conference at 3M MSIA Student Orientation Spring 2019 UnitedHealth Group (UGH) Networking Event Academic Success and Life at SCS

The Infosyst TIMES, Vol. 3, No. 2

SCSU Impresses at Inaugural Student360 Conference TERP 10 ERP Integration of Business IS Graduates get OPT Extension Meet the Faculty: Dr. Jim Chen, Dr. Paul Safonov, Dr. Jianxun Li Meet the IS Club President, Kehinde Sodunke Shoveling the Snow, Shivendran Tiruchanpalli Application Design, Terry Kisner Alumnus Insight, Hareesh Reddy My Journey, Jayakrishnan Karunanidhi NSF STEM Scholarship, Kayla Jensen Information Systems Role in Sustainability: Why is this important? Student Research Colloquium ABET Accreditation ITS Club + IA Club = CSIA Club Uncovering Fraud Triangle SCSU and Maverick Partnership Recognize Five Years of Success CSIA Competes in Cyber Defense Competition CSIA Club Works on Technical Skill

A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future

Evapotranspiration (ET) is a major component of the water cycle and agricultural water balance. Estimation of water consumption over agricultural areas is important for agricultural water resources planning, management, and regulation. It leads to the establishment of a sustainable water balance, mitigates the impacts of water scarcity, as well as prevents the overusing and wasting of precious water resources. As evapotranspiration is a major consumptive use of irrigation water and rainwater on agricultural lands, improvements of water use efficiency and sustainable water management in agriculture must be based on the accurate estimation of ET. Applications of precision and digital agricultural technologies, the integration of advanced techniques including remote sensing and satellite technology, and usage of machine learning algorithms will be an advantage to enhance the accuracy of the ET estimation in agricultural water management. This paper reviews and summarizes the technical development of the available methodologies and explores the advanced techniques in the estimation of ET in agricultural water management and highlights the potential improvements to enhance the accuracy of the ET estimation to achieve precise agricultural water management

Organizational Dynamics and Adoption of Innovations: A Study within the Context of Software Firms in Sri Lanka

This paper examines the effect of organizational dynamics on innovation focus using the residual dominant and emergent theoretical framework (RDE) and the empirical evidence of four case studies. The findings revealed that different types of innovation coexist, but one type becomes dominant over other types at a certain time as the innovation focus is changed in line with the strategic priorities of firms. We found that innovation focus takes the form of product, process, and organizational innovation pattern over time when the firms move from an entrepreneurial organization to a more formal business corporation. More importantly, the RDE framework provides an appropriate lens for practitioners, in identifying the enablers and barriers of innovation

Effectiveness of Best Management Cropping Systems to Abate Greenhouse Gas Emissions

Best management practices (BMPs) for cropping systems that involve conservation tillage and nutrient management are proposed as potential win-win solutions for both farmers and the environment. While originally targeted as a means for improving soil and water quality, these BMPs may also contribute to the mitigation of greenhouse gases (GHGs). Mitigation efforts have focused primarily on the ability of BMPs to sequester carbon and the subsequent potential revenue source carbon sequestration may represent to farmers. Increasingly, evidence from experimental stations calls into question the potential for C-sequestration with reduced tillage in soils in Eastern Canada. However, there are other ways in which BMPs can reduce GHG emissions: lowering fuel and nitrogen fertilizer consumption and, potentially, lowering emissions of nitrous oxide from the soil. This article examines the profitability and emission reduction potential of best management cropping practices for Ontario.Agricultural and Food Policy, Farm Management,

Tool to Detect Spam Websites

Traveling is about relaxing and not worrying about being scammed and losing money. The Internet is a wide place that is changing every day. Having a guide to navigate unknown places goes a long way to staying safe. In this paper, I have used several identifiers and provided analysis on the effectiveness of these identifiers. Travel Website fraud is a severe problem which is widespread around the world. Studies of travel scams are mainly focused on finding different ways that attacker’s targets on the innocent travelers. Now the technology is advanced and that is causing newer and newer techniques to scam people. By illustrating the techniques to find such frauds and to prevent people from getting scammed is something this paper is trying to achieve. In this paper we will look at the various problems and preventive measures that need to be taken while browsing the internet. In this paper I will be talking about the tools I have used for analyzing a website. I will also be providing the analysis of the different identifiers in finding out if a website is fake or genuine. The results and the conclusions from the analysis can then be used in designing a safe tool which can be used for keeping the internet users safer and wiser. The safe rules can be used to develop browser addons, computer applications etc

Probabilistic Models for Anomaly Detection Based on Usage of Network Traffic

Recent advances in intrusions and attacks reflect vulnerabilities in computer networks. Innovative methods and tools can help attack defenses, prevent attack propagations, detect and respond to such attacks in a timely manner. Intrusion detection and prevention systems search for unauthorized use, recognize anomalous behavior, and prevent attempts to deny services.  These systems gather and analyze information from the network, identify possible breaches of the security profile, as well as misuses. We have been experimenting with methods for introducing important concepts related to intrusion detection and improving undergraduate research experiences and education. To achieve this goal, probabilistic models are introduced to students in computer, information system and network security courses. This article presents a set of probabilistic methods and statistical models for network traffic anomaly detection. It also describes some prospects and how models have ripened from theories to big data analysis applications. Keywords: Intrusion, conditional probability, network system, regression, data analysi