De La Salle University

About: De La Salle University is a education organization based out in Manila, Philippines. It is known for research contribution in the topics: Population & Computer science. The organization has 2951 authors who have published 4374 publications receiving 49567 citations. The organization is also known as: Pamantasang De La Salle.

Does Facebooking make us sad? Hunting relationship between Facebook use and depression among Filipino adolescents

Abstract: The current paper looked at the linkage between the use of Facebook and depression levels of selected Filipino adolescents. Two hundred college students whose ages ranged from 17 to 20, in a private and sectarian collegiate institution were selected through purposive sampling. Goldberg Depression Scale (GDS) and a survey regarding the number of hours allotted in the use of Facebook per week served as data collection instruments. Utilizing a descriptive-correlational research design, the researchers found that there is no significant association between respondents’ level of depression and the use of Facebook (r = 0.04, p = 0.70). Hence, depression cannot be sufficiently linked to the use of Facebook. Implications of the findings to the fields of counseling and psychology were discussed.

Detection of Wolbachia in field-collected Aedes aegypti mosquitoes in metropolitan Manila, Philippines.

Abstract: Recent reports reveal the presence of Wolbachia in Ae. aegypti. Our study presents additional support for Wolbachia infection in Ae. aegypti by screening field-collected adult mosquitoes using two Wolbachia-specific molecular makers. A total of 672 Ae. aegypti adult mosquitoes were collected from May 2014 to January 2015 in Metropolitan Manila. Each individual sample was processed and screened for the presence of Wolbachia by selected markers, Wolbachia-specific 16S rDNA and its surface protein (wsp), under optimized PCR conditions and sequenced. Totals of 113 (16.8%) and 89 (13.2%) individual mosquito samples were determined to be infected with Wolbachia using the wsp and 16S rDNA markers, respectively. The Ae. aegpyti wsp sample sequences were similar or identical to five known Wolbachia strains belonging to supergroups A and B while the majority of 16S rDNA sample sequences were similar to strains belonging to supergroup B. Overall, 80 (11.90%) individual mosquito samples showed positive amplifications in both markers and 69% showed congruence in supergroup identification (supergroup B). By utilizing two Wolbachia-specific molecular makers, our study demonstrated the presence of Wolbachia from individual Ae. aegypti samples. Our results showed a low Wolbachia infection rate and inferred the detected strains belong to either supergroups A and B.

Machine vision for traffic violation detection system through genetic algorithm

Abstract: This paper presents a machine vision algorithm to detect traffic violations specifically swerving and blocking the pedestrian lane. The proposed solution consists of background difference method, and focuses on the genetic algorithm of the system to detect these violations. The general process is as follows: a capture picture is to be subtracted first by the reference image, then the genetic algorithm is run to find the violator, and finally a display is outputted with the corresponding type of violation. The machine vision traffic violation detection system was found to have an average convergence of about 8 iterations, within an average of less than 300 generations. These results show that the algorithm is well-suited for real time implementation in traffic detection system. Provided the system inputs were captured photos from a CCTV camera, whereas the outputs were cropped pictures of the car that was detected to have such violations mentioned earlier.

Personal software process (PSP) assistant

Abstract: The personal software process (PSP) is a process and performance improvement method aimed at individual software engineers. The use of PSP has been shown to result in benefits such as improved estimation accuracy and reduced defect density of individuals. However, the experience of our institute and of several others is that recording various size and defect data can be onerous, which in, turn can lead to adoption and data quality problems. This paper describes a system that we have developed that performs automatic size and defect recording, aside from providing facilities for viewing and editing the usual PSP logs and reports. Moreover, the system automatically classifies and ranks defects, and then consolidates schedules and defect lists of individual developers into a schedule and defect library for the developers' team.