Comparative analysis of Phosphate reduction in DLSU-D Lakewater using Chaetomorpha linum and Ulva lactuca

Maryjoie Lituañas,  Michelle Buchan, Rochelle Cayasa, and Manabu Onodera

College of Engineering Architecture and Technology, De La Salle University – Dasmarinas, Dasmarinas, Cavite

Abstract

As the country rapidly progresses, ecological and environmental problems arise, and these include water pollution. Consequently, a need for water pollution treatment has become urgent. Nutrient pollution, which happens due to excessive nitrogen and phosphorus in the water, is a tremendous, expensive, and tough environmental issues. As a promising approach for wastewater treatment, macroalgae was considered as a means to reduce excessive nutrient concentrations. In De La Salle University- Dasmarinas, the Environmental Resource Management Center’s Development Office (DLSU-D ERMCDO) recorded data of phosphate contents of La Salle Lake peaked at 50ppm, which is beyond the standard for Class C water. The study focused on comparing the efficacy of macroalgae U. lactuca and C. linum using by batch process in reducing phosphate levels in DLSU-D lake water in terms of time and mass. Results indicate that the longer exposure time of nutrient-rich water to the macroalgae would result in a larger reduction of phosphates at a peak of 120-hour. Macroalgae species comparison shows that C. linum had a higher reduction efficiency of phosphate at 500g at 12h absorption time than what U. lactuca had. This study suggests C. linum as the most suitable macroalgae to be used for phosphate reduction in nutrient-rich lake water.

Keywords: Phosphate, C.linum, U. lactuca, lake water, reduction efficiency, treatment efficiency

Full paper

Optimization of Concrete Hollow Blocks using Pelletized Aggregates of Polystyrene

Roberto L. Rodriguez, Jr.^1,2 and Johnny A. Ching²

¹Far Eastern College–Silang, Inc, Silang, Cavite, Philippines

²De La Salle University–Dasmariñas, City of Dasmariñas, Cavite, Philippines

Abstract

Human’s nature to demand for food and for infrastructure concomitantly grows with population through time and is linked to plastic waste mismanagement and to the purposes of Sustainable Development Goals #9 and #12. Studies attending to these concerns through plastic-blended concrete hollow blocks (CHBs) have been ubiquitous; however, there is a lack of optimization of CHBs using pelletized polystyrene (PS) as fine aggregates. Hence, this study aimed to characterize the physical properties of PS pellets and to assess PS-blended CHBs’ workability and compressive strength in accordance with ASTM C143 and C140, respectively. PS pellets were characterized, were incorporated as sand replacement by 0%, 10%, 20%, and 30% resulting to four batches, and were cured for 28 days.  Workability values revealed its potential to be used in constructing dams, bridge piers, and canal locks. Compressive strength values of PS-blended CHBs were statistically at par with the commercially produced CHB. Batch with 30% PS pellets attained the strongest and above the minimum acceptable compressive strength value among the experimental group. This implies that incorporation of PS pellets can be an auspicious solution to plastic waste dilemma and demand for stronger CHBs.

Keywords: Compressive load, concrete mixture, engineering, mass concrete, plastic utensil, slump value, workability

Full paper

Raspberry Pi-based Non-Intrusive Fake Iris Detector

Mariel A. Tinaco, Jhon Michael R. Guijo, Gem R. Aguimbag, and Joshua R. Hernandez

College of Engineering, Architecture and Technology,

De La Salle University–Dasmariñas, City of Dasmariñas, Cavite, Philippines

Abstract

The study aims to develop and deploy an effective Iris Spoofing Prevention Biometric System that strays away from conventional intrusive methods and, instead, takes advantage of recent developments in the field of Machine Learning, particularly, Convolutional Neural Networks (CNN). Previously used ocular-based techniques for liveness detection pose concerns of discomfort and health risks among the general public because of long-exposure to ocular sensors and the intrusiveness of the procedure. By using CNN, the physiological features to be extracted will solely come from a scanned image of the subject without requiring an ocular sensor or infrared radiation. This requires tapping into certain Computer Vision libraries to extrapolate the necessary data and minimize noise. The variables were then, narrowed down to subject-to-camera distance and camera resolution while the environmental lighting during sampling and the set of training images were deemed uniform. The system was able to produce positive results for very specific configurations of the camera resolution and distance and with the available resources from the Raspberry Pi 3-B. The consistency of training and testing data play a very significant role in providing accurate findings. This system, once fully proof-tested and optimized, can be used alongside existing Iris Recognition Technologies as an extension of fool-proofing capabilities.  

Keywords: Iris-spoofing, Biometrics, CNN, Machine Learning, Computer Vision

Full paper

Waste Reclamation of Aquatic Mollusk: Transforming Asian Green Mussel Shells as Alternative Architectural Interior Wallcoverings

Roczel Nicole V. Genson¹ and Juanito Y. Sy^1,2

¹De La Salle University–Dasmariñas, City of Dasmariñas, Cavite, Philippines

²GIBSY Construction and Development Corporation, Bonifacio Global City, Taguig, Philippines

Abstract

The demand for wallcoverings in the building industry increases; it is mainly driven by household customization and significant growth rate in residential constructions. With this, the escalation of calcium carbonate obtained from limestones increases since it is commonly used as an additive to improve wallpaper’s properties. Aside from limestones, Asian green mussel shells (tahong shells) are also composed of up to 95% calcium carbonate and the remaining represents an organic mix. This entire study used pulverized Asian green mussel shells, which were collected from several seafood restaurants in Cavite, as the fundamental materials for the sustainable development and production of wallpapers. The pulverized Asian green mussel shells acted as a sustainable replacement for commercial carbonate. The research study applied experimental research to support the methodological process leading towards significant outcomes. The experiment was conducted by analyzing the mussel shells’ physical, chemical and mechanical properties based on the International Organization for Standardization (ISO) test methods in order to determine their effectiveness. Based on the overall results, the innovated wallcoverings exceeded the required properties of the commercial wallpaper produced locally in terms of tear strength, tensile strength, and water absorption. Further, the tests had successfully provided evidence proving the benefits for aesthetic and unique appearance, durability, efficiency, sustainability, and workability.

Keywords: Aquatic waste, calcium carbonate, pulverized mussel shell, wallcoverings

Full paper

Full Journal Issue

JOURNAL OF ENGINEERING, COMPUTING AND TECHNOLOGY

The Journal of Engineering, Computing and Technology (JECT) is a scholarly peer-reviewed, and academic research journal for engineers, computer scientist, academicians, and research scholars aiming to publish innovative, state of the art results coming from research and advances in different aspects of engineering, architecture, computer science and information technology.  JECT is dedicated to the dissemination of advanced technologies that will be beneficial to professionals and academic researchers. It is a bi-annual publication that releases issues every June and December.

                The journal is governed by an editorial board whose members specialize in each of the mentioned disciplines.  The editor in chief is elected by the members of the editorial board.

Editorial Board

Editor-in-Chief

Maryli F. Rosas, DIT (Computer Science, De La Salle University-Dasmariñas)

Associate Editor

Ma. Cristina A. Macawile, PhD (Engineering, De La Salle University- Dasmariñas)

Members

Paulino H. Gatpandan, DIT (Computer Science, De La Salle University- Dasmariñas)

Maryjoie A. Lituanas, MSES (Engineering, De La Salle University- Dasmariñas)

Mengvi P. Gatpandan, DIT (Computer Science, Jose Rizal University, Mandaluyong City)

Daniel Dasig Jr., PhD (Field, Change Management Engineer, TELUS Communication Inc., Canada)

Nestor Tiglao, PhD (Electrical and Electronics Engineering Institute, University of the Philippines – Diliman)

Atty. Rudolph Val F. Guarin (Field, FGNG Law Office)

Prof. Sonia M. Pascua (Field, Drexel University, United States of America)

Brojo Kishore Mishra, PhD (Department of CSE, School of Engineering, GIET University, Gunupur, India)

Valentina Emilia Balas, PhD (Automation and Applied Informatics, Intelligent Systems Research, University of Arad, Romania)

Editorial Assistant

Mr. Jaime Zeus C. Agustin (Research Communication, Dissemination and Utilization Coordinator, University Research Office, De La Salle University-Dasmariñas)