Research | SDG 9 – Industry, Innovation and Infrastructure

Mar Heisen A. Yanos, Jeremiah Jathniel O. Guevarra

Abstract

Land use and land cover maps play a critical role in program design, management, and monitoring. Development of land use map aids to understand land use issues and formulation of policies and programs necessary for development planning. In this study, satellite images for the year 2014 and 2019 were used for supervised classification. For the classification purposes, four classes were decided. For accuracy assessment classification matrix and KAPPA analysis was done. The comparison of land use in 2014 and 2019 derived from satellite imagery interpretation indicates significant increase in built-up and barren areas. It is also noted that substantial amount of agricultural and water area vanished during the period of study which may be due to rapid urbanization and economic factor. The overall accuracy of the supervised classification image is 90% and 97.50% and kappa statistics is 0.86 and 0.96 respectively for the year 2014 and 2019.

Keywords: Land Use, Land Cover, San Mateo, GIS

Mar Heisen A. Yanos, Johna Mae B. Udan

Abstract

Growing crops has always relied on the availability of land. The land suitability classification process comprises the evaluation and grouping of a specific land area in terms of its appropriateness for a well-defined use. The term "land suitability" refers to the degree to which a piece of land is suitable for a specific use. In this research, a multi-criteria evaluation technique was used to identify and outline the area in San Mateo, Isabela that can best support the growth of the mungbean plant. Using GIS technology to construct a spatial model for evaluating land suitability for mungbean cultivation and to generate a suitability map by classifying agricultural land in the study area into several suitability classes based on a set of criteria and constraints. The precise assessment of land suitability for specific agriculture production is essential to minimize negative environmental impacts. The optimal constraint approach was used to choose different parameters that affect mungbean product yield, such as soil properties, agro-climatic conditions, and topography. This addresses San Mateo, Isabela tagged as the “Munggo Capital of the Philippines,” where farmers plant mungbeans after harvesting rice.

Keywords: Suitability analysis, map, GIS, AHP, San Mateo, Mungbean

Bondee L. Peñaflor

Abstract

This study aimed to assess the lighting systems in the selected buildings of Isabela State University, Cabagan Campus which will serve as basis in determining intervention potentials and energy saving opportunities. Two biggest electricity-consuming buildings were considered in this research: Campus Administration Building (CAB) and College of Education Building (CEB). Using infrared distance meter, light meter and a self-prepared Lighting Assessment Data Sheet, the level of illuminance was measured in each room/office. Results show that the total electricity consumptions per day are 2.73KW and 1.049KW for CAB and CEB, respectively, and the costs per day are PhP2,989.16 and PhP114.57, respectively. The shift into 10W LED Pin Lights as replacement to the existing non-LED lighting fixtures would make total electricity consumptions per day at 1.11KW and 0.75KW, respectively while the cost would result into PhP121.23 and PhP81.91. A potential annual saving of PhP46,709.1 in CAB while PhP8,621 in CEB. Meanwhile, Only the Cashier’s Office at CAB was found to have sufficient illumination while all the rest are under lit. When the window blinds are rolled-up, the Conference Room and the Registrar’s Office are still under lit while the Executive Officer’s Office, Human Resource Management Office, MIS Office, Planning Office and the Cashier's Office are over lit. In CEB, the mean illumination levels of the offices/rooms are under lit wherein the levels are way below the standard. It is recommended that all non-LED type lamps should be replaced with LED-type. The design of lighting system should be revisited and the use of LED-type lamps should be considered in the Conference Room and the Registrar’s Office including those rooms/offices in CEB.

Keywords: Energy Audit, Lighting System, Illuminance, LED-type Lamps

Orlando F. Balderama, Christine Mata, Lanie A. Alejo, Jeoffrey Lloyd R. Bareng, Elmer Rosete, Czarimah L. Singson, Alvin John B. Felipe, Jeremy T. Balderama, Anthony Jordan Justo, Genesis Querubin

Abstract

Philippines is one of the most flood-affected countries in the world. While floods have become more damaging throughout time, it requires risk assessment quantifying flood risk damages as accurately as possible. An up-to-date database containing information on hazard-prone regions is critical for supporting hazard preparedness and response operations, particularly in the case of recurring floods. To deal with flood damage assessment due to lack of visualization and estimation, a satellite-imagery based method for flood inundation map using Google Earth Engine was performed. The study reported the recent flood inundation (November 2020) during typhoon Ulysses in the Cagayan Valley in CRB that led to the inundation of an extensive area 661.73 km2. The flood affected an enormous population (approximately 225,634 people), with worst in Cagayan (53.96% of inundation; 50.36% of the total affected population) followed by Isabela (45.93% of inundation; 49.62% of the total affected population) the flood severely affected approximately 5.04% (477.44 km2) of the total cropland and 16.14% (4.36 km2) of wetlands in the region. The overall accuracy of datasets used is 97.78% while flood extent is 95%. The data and methodology of the study can be replicated for other flood events in the Philippines.

Keywords: socio-economic impact, flood, synthetic aperture radar, flood risk assessment, Google Earth Engine, damage

Rose Mary A. Velasco

Abstract

Protecting the computer lab can be challenging as it was meant to be easily accessible to the student. This study presents the development of a prototype model for securing a computer laboratory using RFID, and Internet of Things (IoT) solutions with the application of the Shamir Secret Sharing (SSS) Scheme. The prototype model aims at resolving manual or traditional methods of checking classroom attendance. The system was tested and evaluated by IT experts and students at the computer Laboratory of Isabela State University, Cauayan Campus. The factor of acceptability as to technical support and processes of the system gained a general weighted mean of 4.35 (sd=.490) which means there is an evaluator's agreement of the functionality of the developed system based on ISO 25010 standards. The system is a web-based that can be utilized on PC or mobile phones using the specific IP Address of a web browser. The model prototype has the capability of recording teachers’ and students’ attendances, classroom entry logs, calculation of tardiness and absences, can retain current and previous records, capable of entry log history, data security, and printing reports. Moreover, the system should have another platform for accessing and viewing the students’ attendance such as Mobile Application (APK); and send notifications via SMS to remind the students’ status in their respective course/subject using GSM Module.

Janet P. Cunanan, Audelon Benito, Joey C. Cereno, Clammie S. Cullanan, Eddie I. Peru

Abstract

The focus of the study is to assess the present existing system the university is utilizing relative to records’ security, preservation as well as their general awareness on data archiving and duration of valuable records to be kept. Fifteen (15) offices served as the respondents. Existing Data Archiving System identified by each of the offices were Digital Material, Databases and Archiving Personnel in-charge only. Others responded to have none-existing system used. Textual documents, Still Images, Video, Inventory System, Databases, Audio, Management Information System, Human Resources Management System were specified data to be stored in a data bank and will be preserved for future used. Among all records identified which found to be extremely important were; Filled-up and Encoded Data Forms, Submitted Reports, Received/Out-going Communication, Memorandum and not cited in the survey included by them were Trainings/Seminars attended by personnel, Researchers’ Profile, Project Status, Project Proceeds, Funding Agencies other related forms and jpeg/images. Uncertainties is evident as to their awareness on data archiving and security and no specific duration as to how long does record/data should be kept. Managing records effectively is to keep significant ones so long as they are needed and requires permanent storage whereas obsolete or superseded information and files maybe removed if possible. Stemming from the gathered responses, no existing automated system for recording, filing, keeping and storing of data was evident. The development of an archiving system then to be utilized by the campus should be developed based on discussions in the paper.

Keywords: Data Archiving, Information Management, awareness, data preservation, data security, automation

Manocher C. Alipour

Abstract

With the proliferation of media material on today's networks, a need for safeguarding ownership, authentication, and data tampering has arisen. One of the difficulties confronting individuals and industry artificial neural network models such as deep fake and media content editors is the protection from the tapering of media contents. The PSNR and SSIM are used to analyze the watermarked picture. The results prove improved watermarking security and resilience compared to current watermarking architectures and methods. The researcher method is designed in a way that has a lesser footprint on the covered image. The result showed proposed process has a higher peak signal-to-noise ratio (PSNR) for a color image with an average value of 83.9754838, compared to other studies outcomes. The proposed method improved image watermark impersonality.

Keywords: discrete wavelet transform; DWT; discrete cosine transform; DCT; Encryption

Manocher C. Alipour

Abstract

Data, undoubtedly, is a single commodity that never loses its value in a different era. Data exists in different formats all around us, from the minor beginning up to the most significant creation generating some data. Steganography transfers data via various mediums such as pictures, text, music, video, QR code, and platforms such as SMS, MMS, and multimedia. one of the widespread media images used in day to day communication. The image uses widely by users and computing technology in numerous applications. Hidden the payload in the cover image by using some factors improves steganography output. Image, on the other hand, is one of the most widely used forms of media. In this study, the researcher employed the Least Significant Bit to create a watermarked image. The researcher uses the Peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM), and visual histogram attack to evaluate the results. The method produces the average PNSR value of 54.70, which shows that the method has properly hidden the data into the cover image, and histograms between the original image and the watermarked output show minimal changes. That suggests the method applied improved Imperceptibility.

Keywords: Steganography, Data hiding, Similarity-based method, MSE, PSNR

Renaldo G. Manipon, Jenalyn C. Andres

Abstract

This sought to develop and fabricate a sewing cabinet purposely for the Garments Fashion Design laboratory room of Isabela state university San Mateo Campus, and to be introduced to tailoring shops within the community. The prototype design focused on multifunctionality likened to the “bagani” with various traits. The criteria for evaluation of the prototype include effectiveness and multifunctionality, portability and compactness, transformability and space-saving potential, ease of use, and economy and affordability. The study made use of the descriptive-qualitative research method. The respondents of the study include fifty-six (56) BTVTE-GFD students of the Isabela State University – San Mateo Campus, seven (7) owners of tailoring shops, and twelve (12) workers for a total of 75 samples. Data were collected using a survey questionnaire after the project demonstration. Findings of the study reveal that the effectiveness and multifunctionality is highly acceptable while the portability and compactness, transformability and space-saving potential, the ease of use, and the economy and affordability aspects of the Bagani Sewing Cabinet is acceptable

Keywords: Sewing cabinet, bagani, multifuntionality, compactness, ease of use, transformability, affordability, space-saving

Renaldo G. Manipon, Jenalyn C. Andres

Abstract

This study aimed to develop and evaluate a multipurpose table for the Garments Fashion Design laboratory room of Isabela state university San Mateo Campus and to be introduced to tailoring shops within the community. The criteria for evaluation of the prototype include versatility, collapsibility, practicality, and space sustainability. The study utilized the descriptive-qualitative research method. The respondents of the study were composed of 48 GFD students at the Isabela State University – San Mateo Campus, 7 tailoring shop owners, and 10 dressmakers within the vicinity of San Mateo, Isabela identified using the simple random sampling technique. Data were collected using a survey questionnaire that followed after the prototype demonstration. The findings of the study reveal that the versatility, practicality, and space sustainability of the multipurpose table are highly acceptable. Moreover, the collapsibility as an aspect of the prototype is acceptable.

Keywords: multipurpose table, versatility, collapsibility, practicality, space sustainability

Irma T. Plata, Edward B. Panganiban, Darios B. Alado, Allan C. Taracatac, Freddie Rick E. Labuanan

Abstract

Object detection technology aims to detect the target objects with the theories and methods of image processing [1][2][3] and pattern recognition [4][5], determine the semantic categories of these objects, and mark the specific position of the target object in the image. This study aims generally to establish a recognition method for Cassava Phytoplasma Disease (CPD) real-time detection based on transfer learning neural networks. Different methods and procedures were conducted such as the testing of two methods in transmitting long-distance high definition (HD) video capture; establishment of a compact setup for a long-range wireless video transmission system; the development, testing of the real-time CPD detection and quantification monitoring system, providing the comparative performance analysis of the three models used. We have successfully custom-trained three different artificial neural networks using transfer learning namely, Faster R-CNN[6] [7] Inception v2, SSD Mobilenet v2[8], and YOLOv4[9]. These deep learning models can detect and recognize CPD in actual environment settings. Overall, the developed real-time CPD detection and quantification monitoring system was successfully integrated into the wireless video receiver and seamlessly visualized all the incoming data using the three different CNN models. If the consideration is the image processing speed, YOLOv4 is better compared to other models. But, if accuracy is the priority, Faster R-CNN inception v2 performs better.

Keywords: Cassava phytoplasma disease, Faster R-CNN Inception, image processing, object detection, precision agriculture

Irma T. Plata, Edward B. Panganiban, Darios B. Alado, Allan C. Taracatac, Freddie Rick E. Labuanan

Abstract

Crop diseases like Cassava Phytoplasma Disease (CPD) play a key role in reducing cassava production and quality. Therefore, detection is fundamental in precision agriculture tasks. Manual detection of CPD diseases takes additional time and effort on the larger area of the cassava farm. A deep learning approach like Convolutional Neural Networks (CNN) can be used to detect diseases more accurately on leaves and other parts of the cassava plants. The methods used in this project helped detect CPD by performing custom training/fine-tuning on three CNN models for object detection which are comprised of Faster R-CNN, SSD Mobilenet v2, and the YOLO v4. The results revealed that the Faster R-CNN inception v2 has a training accuracy of 95%, SSD Mobilenet v2 has 73% training accuracy, while YOLOv4 has 85% training accuracy. Finally, the study concluded that in terms of image processing speed consideration, the YOLOv4 is best compared to Faster R-CNN inception v2 and SSD MobileNet v2, however, in terms of accuracy, Faster R-CNN inception v2 performs the best compared to the two other models. Hence, these two models can be used depending on the purpose of CPD detection. However, since CPD detection is the main purpose of this study, the Faster R-CNN model is recommended for adoption to detect CPD in a real-time environment.

Keywords: Cassava phytoplasma disease, Convolutional neural networks, Deep learning, Faster R-CNN, image processing, precision agriculture

Irma T. Plata, Edward B. Panganiban, Darios B. Alado, Allan C. Taracatac, Freddie Rick E. Labuanan

Abstract

The development of Web-Based Visual Imaging of CPD Heat Map Using Arc GIS Java Script API is intended for the detection of Cassava Phytoplasma Disease. Cassava phytoplasma disease (CPD) is a current serious threat to the country’s cassava industry. Philippines is one of the countries in Asia that produces Cassava as one of its agricultural products. This project provides innovative tools to address the problems of the Cassava farmers in the Region. The Rapid Application Development (RAD) Methodology was used as guide of the researchers to develop the system. Data Flow Diagramming was used to conceptualize the process flow of the system. The methods used in the detection process are Pixel Intensity, Color Intensity and Ratio and Coordinates Plotting using Raw Data and Featured Layer. The development of the WEB-BASED VISUAL IMAGING OF CPD HEAT MAP USING ARC GIS JAVA SCRIPT API is an effective and innovative tool in detecting CPD in order to prevent the spread of the disease. The implementation of the developed system addressed the current needs of the partner agency in monitoring and preventing the occurrence of the CPD in their cassava plantation. Visual Imaging of CPD Heat Map Using Arc GIS Java Script API was an effective tool in detecting the presence of Cassava Phytoplasma disease in cassava plantation using the different techniques and methodologies.

Keywords: ARC GIS, Heat Map, JAVA Script, Visual Imaging, Web-based system

Precila C. Delima, Ermel Delima, Lorelei C. Tabago, Marisol Foronda

Abstract

This is an assessment of the current situation of public transport system in Cauayan City that determines “fair fare” ensuring that commuters and drivers both share the burden of petroleum price increases. It evaluates commuters’ behavior, perception of the current level of trike fares and assessment of the overall situation of the public transport system in Cauayan City using a survey method. Important findings include the following : the city’s population continue to depend on public utility trikes as their primary mode of transport to travel within and around the city; the primary destinations of commuters when rising public utility trikes within Cauayan City are workplaces, the public market and supermarkets, malls, schools, and church; respondents are almost divided when asked on their perception of whether the current level of tricycle fares within the city are moving in parallel with the movements in petroleum prices, as well as on changes in prices of other commodity products and services and more than 60% agree that trike fares should be adjusted annually to reflect changes in petroleum prices.

Keywords: Cauayan City, Sustainable Development Goals, Fare Hike

Lito S. Guzman, Jr.

Abstract

The study aims to examine the dimensions of psychosocial stimuli of the mining operation of Dinapigue Mining Corporation in Dinapigue, Isabela. It also aims to explore the potential utility of Exploratory Factor Analysis (EFA) to extract latent variables and identify common constructs that can be used as the main thematic areas of the psychosocial dimension for the mining company to strategize its operation and as bases to support its goals to earn a high social acceptance or social license to operate. Common constructs that were contextualized from aggregates of variables that explain common context or idea were used to distinguish the uniqueness and perceptual differences between the group of respondents under different job classifications and gender using the Canonical Discriminant Analysis. Results have shown that six (6) constructs represent the psychosocial dimension of mining which can be used as future bases of the mining company in determining the scope, and extent of implementation of its corporate social obligations to earn social acceptance, and future reference for policy formulation, planning, and decision making. These include the “attribution of responsibility and causal attribution of events”, “awareness of consequences”, “personal branding and social persuasiveness”, “equity and social inclusion”, “perceptual understanding of socio-cultural and economic performance”, and “social embracement”. For the result of the Canonical Discriminant Analysis, mining and unemployed respondents can be easily classified from other groups of respondents since they highly express distinct aggregation in areas within the psychosocial dimension which are expressed by other groups the least. On the other hand, respondents who are classified under farming, employed, and fishing categories have no distinct clustering in the psychosocial dimension that would separate them from each other, and their irregular patterns make their distinction from each less obvious.

Maria Theresa R. Aggabao

Abstract

This paper discusses the outcomes and the possible impact of an extension development intervention to a group of women who were involved in the processing of tomato food products with the end in view of establishing their own micro-business enterprise for them to have another source of income which could greatly augment the meager amount that they were earning. The major source of income of most of the women in this study was through their work as farm laborers. Most of them earned an estimate of less than four thousand pesos a month which, according to economic standards, is way below the poverty line. The assessment tool used in this study is based on an impact assessment framework where the context of the project is driven by the project objectives and provides a guide in determining the needed inputs and activities that could eventually lead to the realization of the expected outputs, outcomes and impacts of the intervention on the personal life of the members and on their association. With inputs and activities provided by different collaborating agencies into the development intervention, possible outputs include medium and long-term effects on the social well-being and the financial status of the women members of the association.

Mariflor H. Devibar

Abstract

Global communities had been transforming into greener economy by utilizing and adopting green technology from farm to industrial sector. Countries need to employ strategies to addressed the global concern, that is climate change. This paper evaluated and assessed the green technology practices adopted by the farmers/cooperatives and the puzzling lag that the encountered. Results of the study revealed that majority of them are already practicing green technology adoption such as vermicomposting, manure and sileage without proper training and information about it. Moreover, they also adopted the 5R’s of Waste Management. On the contrary, there are some puzzling lag such as lack of financial, slow loan processing and lack of government support were just some of the mentioned that they encountered. Consequently, there is an urgency on awareness on the utilization of Green technology among cooperatives. This can be done through massive information drive and trainings and workshop to be conducted by the ISU as a partner and strengthen the tie-up with the local government to sustain their capability as adopters of green technology.

Ryan C. Ancheta, Orlando F. Balderama, Richard Martin E. Rinen, Jeoffrey Lloyd R. Bareng, Lanie A. Alejo, Rafael J. Padre, Jackson B. Ramos

Abstract

This study sought to assess the vulnerability of critical infrastructures (CI’s) in Tuguegarao City during flood disasters. The study also aims to establish the interdependencies of CI’s and later assess the overall synergistic effect during flood disasters. The critical infrastructures were identified by classifying CIs based on the definition of FEAM and CISA, identifying CIs through the NDRRMC’s definition, and by conducting a community survey. The SYNEFIA methodology developed by David Rehak was applied to determine the degree of interdependency of these critical infrastructures and their over-all impact in the society. A 5, 25, and 100-Year flood hazard map from UP DREAM LiPAD was utilized in the study to assess the vulnerability of the CIs. Aside from the flood hazard map, an ocular survey was conducted to assess the structural exposure to flood. Government and institutional drivers were also included in the criteria. These drivers are warning systems, flood control facilities, and flood protection to CI. It was found out that the electricity management sector, the sector with the highest impact percentage is not vulnerable to flooding. The healthcare systems, financial establishments and commercial sectors were found to be at low vulnerability. While the evacuation center specifically located at the “Centro” is moderately vulnerable.
Keywords: Critical Infrastructures, Flood Vulnerability Assessment, Interdependency, SYNEFIA

Ma. Teresa S. Alvarez, Diosdado C. Cañete

Abstract

Dairy farming plays a vital role in social and economic livelihood of the farmer household and cooperatives in Cagayan Valley. For the adoption of new technologies such as greening technology in dairy production, profiling of the dairy farm is an important factor in developing in the assessment of the viability of the green tech to be adopted by the farmer as a means to increase their productivity and efficiency in farming. By considering this aspect the study was undertaken in Cagayan Valley and the respondents were purposively selected. There were four cooperatives that represents the region while 10 farmer household were also randomly selected. The data were collected using a predesigned interview schedule on-farm/ site, Key Informant interviews (KII) and FGD will be the means in gathering relevant information. The collected data were analysed using basic descriptive statistical methods such as frequency, percentage, proportions, average and rating. The results indicate that majority of the dairy farmers in the Cagayan Valley belonged to the old aged group, with ages ranges 54 and above, with a degree in college, had high income up to P15,001- above/ monthly which represents the large and medium size family. The majority of the dairy farmers possessed a minimum of 5 years level of experience using green technology, in 60 percent of them has both cattle and carabao as dairy farm animals. The adoption rate of green technology using vermicomposting and using solar panel by both category of respondents reveals that there is a potential market expansion for the implementation of the greening tech for the dairy farming industry and for further improvement of the socio-economic status of the farmers and its stakeholders which may lead to embracing greening tech culture.

Keywords: Dairy farming, green technology, vermicomposting and solar tech

Diosdado C. Cañete, Ma. Teresa S. Alvarez

Abstract

The study assessed the technical and economic efficiency of green dairy technology utilization in the Cagayan Valley. Specifically, it assessed the determinants that affect the technical and economic efficiency performance of the dairy farmers by utilizing green technologies. Descriptive statistics and stochastic frontier analysis were used to process the data. The majority of 11 dairy farmers were male, older farmers, greater household size, 9 years in schooling, and lower-income of Php13,863.91/month. They had realized an average net income of Php8,679.01 with an ROI of 88.50%. Material costs contributed to increasing milk productivity due to adoptions of green cost-reducing dairy technologies like silage making, vermiculture/composting, and farm wastes recycling. The number of dairy animals, pre/post-harvest labor cost, and investment were insignificantly affected productivity. The age and years in farming have greater technical inefficiency effects on dairy farmers. Farmers have got older (55.54 years) deteriorating their technical efficiency performance attributed to physical strength, while years in the farming of 23.32 and above have attributed to their resistance to adopting green technologies. Household size of 4 and below family members denotes less technical inefficiency effects. Less number of workers is usually drawn from the family members that contributed better technical efficiency performance.

Keywords: Green Dairy Technologies, Stochastic Frontier Analysis, Technical Efficiency