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.

Highly Sensitive AgNP/MWCNT/Nafion Modified GCE-Based Sensor for the Determination of Heavy Metals in Organic and Non-organic Vegetables

Abstract: Silver nanoparticles/multi-walled carbon nanotubes/Nafion modified glassy carbon electrodes (AgNPs/MWCNTs/Nafion-GCE) were fabricated and were used as working electrode in anodic stripping voltammetry (ASV) for trace level determination of lead (Pb2+) and cadmium (Cd2+). The fabricated electrodes were characterized using scanning electron microscopy and cyclic voltammetry. The amounts of the electrode modifiers and the ASV parameters were optimized. It was found that the electrode modified with 1 mg AgNPs and 2 mg MWCNTs exhibited the best analytical response towards the determination of Pb2+ and Cd2+. The optimized ASV parameters were 60 s for the deposition time, 90 s for the accumulation time, and 100 mV/s for the scan rate. The electrode exhibited linearity from 0.493 ppb to 157.2 ppb for Pb2+ and 1.864 ppb to 155.1 ppb for Cd2+. The limit of detection was found to be 0.216 ppb for Pb2+ and 0.481 ppb for Cd2+. Real sampling analysis was carried out using organic vegetables from Sitio San Ysiro, Antipolo and Daraitan, Rizal and commercially available vegetables from Divisoria, all in Luzon, Philippines. Trace amounts of lead, cadmium, and copper were detected in the samples. Unwashed vegetables contained more heavy metal concentration compared to the washed vegetables. Atomic absorption spectroscopy was performed to validate the presence of the heavy metals in the vegetables.

Comparison of Huffman Algorithm and Lempel-Ziv Algorithm for audio, image and text compression

Abstract: In digital communications, it is necessary to compress the data for a faster and more reliable transmission. As such, the data should undergo source encoding, also known as data compression, which is the process by which data are compressed into a fewer number of bits, before transmission. Also, source encoding is essential to limit file sizes for data storage. Two of the most common and most widely used source encoding techniques are the Huffman Algorithm and Lempel-Ziv Algorithm. The main objective of this research is to identify which technique is better in text, image and audio compression applications. The files for each data type were converted into bit streams using an analog-to-digital converter and pulse code modulation. The bit streams underwent compression through both compression algorithms and the efficiency of each algorithm is quantified by measuring their compression ratio for each data type.

Excitonic Fine Structure in Emission of Linear Carbon Chains

Abstract: We studied monatomic linear carbon chains stabilized by gold nanoparticles attached to their ends and deposited on a solid substrate. We observe spectral features of straight chains containing from...

Lettuce growth stage identification based on phytomorphological variations using coupled color superpixels and multifold watershed transformation

Abstract: Identifying the plant's developmental growth stages from seed leaf is crucial to understand plant science and cultivation management deeply. An efficient vision-based system for plant growth monitoring entails optimum segmentation and classification algorithms. This study presents coupled color-based superpixels and multifold watershed transformation in segmenting lettuce plant from complicated background taken from smart farm aquaponic system, and machine learning models used to classify lettuce plant growth as vegetative, head development and for harvest based on phytomorphological profile. Morphological computations were employed by feature extraction of the number of leaves, biomass area and perimeter, convex area, convex hull area and perimeter, major and minor axis lengths of the major axis length the dominant leaf, and length of plant skeleton. Phytomorphological variations of biomass compactness, convexity, solidity, plant skeleton, and perimeter ratio were included as inputs of the classification network. The extracted Lab color space information from the training image set undergoes superpixels overlaying with 1,000 superpixel regions employing K-means clustering on each pixel class. Six-level watershed transformation with distance transformation and minima imposition was employed to segment the lettuce plant from other pixel objects. The accuracy of correctly classifying the vegetative, head development, and harvest growth stages are 88.89%, 86.67%, and 79.63%, respectively. The experiment shows that the test accuracy rates of machine learning models were recorded as 60% for LDA, 85% for ANN, and 88.33% for QSVM. Comparative analysis showed that QSVM bested the performance of optimized LDA and ANN in classifying lettuce growth stages. This research developed a seamless model in segmenting vegetation pixels, and predicting lettuce growth stage is essential for plant computational phenotyping and agricultural practice optimization.

Higher education, brain drain and overseas employment in The Philippines: towards a differentiated set of solutions

Abstract: This paper describes the interlocking conflicts and resulting problems of higher education in the Philippines. The educational system produces first degree graduates for certain professions and fields of specialization while failing to produce enough graduates in ‘unpopular’ fields of pure science, middle-level technician specializations, and graduate training for research and higher education. The few scientists and graduate degree holders trained abroad migrate to other countries, making the shortage even more acute. For oversubscribed professions, graduates seek overseas employment. In the meantime, the mismatch continues. The author proposes different solutions for each problem; no uniform solution is possible as the nature of the problem is different for each area. For oversubscribed professions, the writer accepts overseas employment as a viable option; it is a source of foreign exchange and a natural way of population control. For undersubscribed professions he proposes a system of incentives tied to a period of mandatory service, after which the beneficiary may exercise his/her options. The writer concludes with some general insights about allowing the ‘invisible hand’ to regulate the process of manpower demand and supply but supports limited and specific government interventions at the right moment.