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This paper explores possible scenarios for the Research Culture of Camarines Sur Polytechnic Colleges (CSPC), to be known as Polytechnic State University of Bicol (PSUB). The paper utilized Jim Dator’s four archetypes of alternative futures to construct PSUB’s Research Culture possible scenarios by 2030. This paper highlights the assumption that the research culture in PSUB is of world class quality and all of its faculty members are actively involved in research, its disciplined, collapsed, transformative, or business as usual scenarios. Four plausible scenarios have surfaced in this paper: Progressive Research Culture, Lax and Deficit Research Culture, Sophisticated Research Culture, and Transformative Research Culture. The article explored areas for a preferred future by 2030. It requires multiple drivers along faculty, students, administration and community for a better research culture. This study proved to be useful in crafting and anticipating the future scenarios of PSUB’s research culture. Preliminary as it may, this study highlighted important building blocks of the four future scenarios. Dator’s framework was proved to be very useful in developing the four scenarios, the use of other future study tools will further amplify plausible scenarios for the Polytechnic State University of Bicol.

Thorough and precise estrus detection plays a crucial role in the fertility of dairy cows. Farmers commonly used direct visual monitoring in recognizing estrus signs which demands time and effort and causes misinterpretations. The primary sign of estrus is the standing heat, where the dairy cows stand to be mounted by other cows for a few seconds. Through the years, researchers developed various detection methods, yet most of these methods involve contact and invasive approaches that affect the estrus behaviors of cows. So, the proponents developed a non-invasive and non-contact estrus detection system using image processing to detect standing heat behaviors. Through the TensorFlow Object Detection API, the proponents trained two custom neural network models capable of visualizing bounding boxes of the predicted cow objects on image frames. The proponents also developed an object overlapping algorithm that utilizes the bounding box corners to detect estrus activities. Based on the conducted tests, an estrus event occurs when the centroids of the detected objects measure a distance of less than 360px and have two interior angles with another fixed point of less than 25° and greater than 65° for Y and X axes, respectively. If the conditions are met, the program will save the image frame and will declare an estrus activity. Otherwise, it will restart its estrus detection and counting. The system observed 17 cows, a carabao, and a bull through the cameras installed atop of a cowshed, and detects the estrus events with an efficiency of 50%.

The MobileNet model was used by applying transfer learning on the 7 skin diseases to create a skin disease classification system on Android application. The proponents gathered a total of 3,406 images and it is considered as imbalanced dataset because of the unequal number of images on its classes. Using different sampling method and preprocessing of input data was explored to further improved the accuracy of the MobileNet. Using under-sampling method and the default preprocessing of input data achieved an 84.28% accuracy. While, using imbalanced dataset and default preprocessing of input data achieved a 93.6% accuracy. Then, researchers explored oversampling the dataset and the model attained a 91.8% accuracy. Lastly, by using oversampling technique and data augmentation on preprocessing the input data provide a 94.4% accuracy and this model was deployed on the developed Android application.

This paper presents the development of an online procurement system and the integration of blockchain technology. Various tools such as PHP, JavaScript, HTML, CSS, and jQuery were used in designing the graphical, programming logic, and blockchain aspect of the system. Every page and function will have their respective construction and result. In addition, the proposed system's flow of process and the methods on the testing and hosting of the site as well as the different web development languages used in every part of the development and design process were presented. The proposed system was successfully and functionally developed starting from the execution of procurement proper, to the placement of procured items or goods, and up to the signing of contracts by the winner and the procurer. Lastly, features were added such as user profiles of the bidder and procurer.

EMG speed-controlled rehabilitation treadmill (BitAid) uses the muscle activity at lower extremities to determine the speed of the treadmill necessary for the rehabilitation of the patient. It targets on aiding patients with lower extremity problems and neurologic cases like after-stroke. The biomedical equipment used is a plugged type BITalino Kit which can determine electrocardiogram (ECG), electrodermal activity (EDA), electromyogram (EMG) and balance using accelerometer (ACC). The data from these sensors are displayed in the tablet attached in front of the patient allowing them to see the reaction of their body during rehabilitation. A suit was designed for placing the electrodes to several points on the patient's body. The overall performance of the device has been evaluated and shown excellent ratings on its necessity, reliability, stability, user-friendliness and ease of operation.

Hormonal imbalance is often pointed out by medical experts to be the cause of menstrual irregularity, a common problem of women. This study aims to develop a device that would determine if a patient has hormonal imbalance by testing saliva’s conductivity onto the device for 28 consecutive days, thus, determining the cause of the patient’s menstrual irregularity. To test the accuracy of the device, the researchers selected three women residing in one home to use the device. To determine if a woman has hormonal imbalance, the data, when plotted in a chart, should have a sudden peak. However, data can’t be analyzed through visual assumptions only. Therefore, the data is analyzed through sample standard deviation. If one data is higher or lower than the sum and difference of the sample standard deviation and the mean, the woman is negative in hormonal imbalance. Comparing the result from the device and from the blood test, it is concluded that the results from the device matched the results from the blood test and medical expert interpretation.