Effectiveness of Interactive, Collaborative vs. Traditional, Lecture-Based Educational Interventions for Adolescents in Low-Income Areas to Increase Knowledge Regarding Sexually Transmitted Infections

Aim: To assess whether teens who live in low-income areas who participate in interactive, collaborative sexually transmitted infections (STI) prevention education will have a significant increase in learning outcomes in comparison to students who participate in a traditional, lecture-based approach. Background: More STIs are reported each year. Among those infected, young people are of the highest incidence at 50% of new STIs in the US annually. High STI incidence is an unintended health outcome as a result of engaging in risky sexual behaviors. This highlights the need to improve STI education among adolescents. Methods: A quasi-experimental method will be used to evaluate the effect of student participation in the two educational teaching interventions about STI knowledge and prevention. Students in both experimental groups will complete A Survey of Current Knowledge on Sexually Transmitted Diseases and Sexual Behaviour in Adolescents (Drago, 2016) questionnaire before and after each teaching intervention is presented. Analysis: Paired sample t-tests will be used to evaluate individual difference on STI knowledge pre- and post-intervention. A total of 60 adolescents (ages 13-19) from low-income areas in Hampton Roads will be recruited for this study, with a goal of 30 in each experimental group. Expected Findings: It is expected that the group who participates in the interactive, collaborative educational intervention will have a more significant difference in scores between the pretest and posttest

Cost Estimation Tool for Commercial Software Development Industries

ABSTRACT: As cost associated to the software development is increasing continuously, there is a need to direct attention at better understanding of development process and calibrating previous models and methods making them applicable to existing environment such as proposing hybrid tools using the techniques based on existing models. The main aim of this paper is to improve the cost estimation accuracy of applications at all the phases of a software development lifecycle by calibrating COCOMO using a function point as a size measure instead of SLOC being used in COCOMO model. Here we have discussed the working of proposed software estimation tool that is a hybrid implementation of various software estimation and measurement techniques helping an organization to determine metrics such as Effort, Time and Cost, essential for improving turnaround time. This tool also works towards utilizing these metrics for project planning, scheduling and tracking

A Comparison of the Effectiveness of Cocos nucifera (Coconut) Water as a Rooting Hormone in a Hydroponic and Conventional Set-up in Growing Ocimum basilicum (Basil)

Food shortage is still a problem in the Philippines since millions of people may be classified as undernourished. Efforts to augment the insufficiency include developing an efficient planting method as a source of food. This experimental study tested the effectiveness of coconut water as a rooting hormone on hydroponically and conventionally grown basil plants by measuring the height, fresh weight, leaf length, and root length for three weeks, which also served as the dependent variables. Consequently, two (2) hydroponic set-ups and two (2) conventional set-ups utilize a randomized block design. The set-ups containing coconut water served as the independent variables, while the ones without served as the control. Before the data gathering procedures, the containers were sterilized, the tap water was exposed to sunlight, and the basil seeds were soaked in coconut water. Six hours later, the seeds were planted. After three weeks, the leaf length and root length were measured using a digital caliper, while the height and weight were measured using a standard ruler and digital scale. The nutrient solution and pH level were also monitored. Data was analyzed using two-way ANOVA for leaf length and plant weight, while one-way ANOVA was used for plant height and root length. In addition, a post-hoc test was used for variables that had a significant effect. Descriptive statistics was used to analyze the mean. The hydroponic setup was effective on producing a higher yield for root length (M=112), while the conventional setup was effective on plant height (M=99.7) and leaf length (M=44.1). While the intervention had no significant contribution (p\u3e0.05), hydroponics as an alternative planting technique still has potential in the agricultural sector

Bidding House: A Web Service and Ontology based Framework for

The advent of e-commerce has brought about a radical change in the process of auctions. This has given bidders flexibility to try and get best possible deals by participating in multiple auctions. This has also lead to evaluation of usage of agents in multiple auctions. However due to varying nature of auction houses, the agents needed for participating in different auctions need to be reconfigured for each auction. This might not be possible to be done by individual users. We propose a flexible framework which will act as a bidding house and participate in the various auction houses on behalf of the user. This framework uses Web services as granular agents and ontology as shared method of communication between these agents. Keywords: e-commerce, software agent, auctions, forward auction, reverse auction, web services, ontolog

Restricting the size of Case Base(for auctions) using Genetic Algorithms

The advent of e-commerce has brought about a radical change in the process of auctions. There is a trend towards automation in the process of auctions. Agents are widely used in this automation process. Casebased reasoning is a process which provides a user a method to automate the process of bidding. This process has an inherent learning component. CBR combined with a bidding agent for strategizing the bidding functionality provides a flexible solution for automating the bidding process for any type of auction in any domain. This paper proposes the use of Genetic Algorithms to restrict the size of the structure of Case Base. This is achieved by optimizing the distributed rules in the case base. Keywords: Learning; Case-based reasoning; E-Commerce; Agents; Genetic Algorithm