Validation of a cat activity monitor

Early detection of diseases and injuries in animals is crucial for their health and well-being. Early diagnosis can be assisted by objective registration of different types of physical activities or behaviour patterns. Monitoring specific parameters, such as changes in activity levels or habits, could serve as an indicator of underlying health issues. It can be challenging for pet owners to notice subtle changes in those characteristics at an early stage. It becomes more difficult in the case of parameters of a low frequency of occurrence, such as drinking and littering behaviours. Hydration status is extremely important in cats and changes in drinking and littering patterns could be early symptoms of potential disorders, in particular diabetes mellitus. There is a noticeable increase in owners’ awareness about the physical and mental health of their pets. With a growing demand for higher standards of tools to assess animals’ everyday habits, more technologies are being developed. Activity monitors utilizing accelerometers provide broad and continuous measures of physical activity, that enable remote and non-invasive monitoring of an individual’s actions. The aim of this study was to validate the registrations of an activity monitor. Specifically, the study aimed to assess the effectiveness of the activity monitor in detecting drinking and littering activities, which might suggest underlying health issues. To monitor these activities, this study used an activity monitor equipped with an accelerometer and attached to a collar. The validity and effectiveness of the activity monitor were established by comparing the measurements obtained from the activity collar to video recordings from the motion sensor camera. For forty-eight days, activity data on drinking and littering actions were collected from a single adult cat. Descriptive statistics were performed to summarize the main findings of the dataset to obtain key results. From the total of 5989 recordings registered by the motion sensor camera, 671 recordings containing actions of drinking and littering were selected for further analysis. Accordingly, 53 recordings were extracted from the activity monitor. This study found no correlation between the data obtained from the activity monitor and the video observations from the motion sensor camera. Further research is needed to investigate the reasons behind this lack of agreement and to improve methodologies for monitoring feline activities using activity monitors. Despite underwhelming findings, it should not rule out all potential applications in monitoring feline behaviors, managing health disorders, and promoting overall health remain promising

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong

                Sistem inferensi fuzzy bisa digunakan untuk diagnosis penyakit pada sapi potong. Untuk mendapatkan akurasi yang tinggi maka batasan fungsi keanggotaan fuzzy perlu ditentukan secara tepat. Penggunaan metode logika fuzzy untuk memperoleh hasil diagnosis penyakit pada sapi potong sesuai pakar berdasarkan batasan gejala penyakit dan aturan-aturan yang diperoleh dari pakar. Batasan tersebut bisa diperbaiki menggunakan Algoritma Genetika untuk mendapatkan akurasi yang lebih baik. Pengujian yang dilakukan pada 51 data dari beberapa gejala penyakit menghasilkan akurasi sebesar 98,04% dengan menggunakan parameter genetika terbaik antara lain ukuran populasi sebesar 80, ukuran generasi sebesar 15, nilai Crossover rate (Cr) sebesar 0,9, dan nilai Mutation rate (Mr) sebesar 0,06. Akurasi tersebut mengalami peningkatan sebesar 3,54% sesudah dilakukannya optimasi pada metode logika fuzzy.Kata kunci: diagnosis penyakit sapi potong, logika fuzzy, Algoritma GenetikaAbstract                Fuzzy inference systems can be used to diagnose cattle disease. Prior to obtaining the most accurate of limitation, fuzzy membership functions must be defined precisely. Thus, the limits will be optimized along with Genetic Algorithm to get more accurate results. The function of fuzzy logic methods in the diagnosis of disease is relied upon the parametres set by experts. Tests that were performed on 51 data from some of the symptoms of the disease resulted in an accuracy of 98.04% using the best genetic parameters with the population size of 80, the size of the generation of 15, crossover rate value of 0.9, and the value of mutation rate of 0.06. The accuracy has increased by 3.54% compare to results before optimization. Keywords: cattle disease diagnosis, fuzzy logic, genetic algorithm

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Centaur 1950

Digitised by the Faculty of the Veterinary Scienc

Centaur 1950

Digitised by the Faculty of the Veterinary Scienc

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

Studies on neurological disorders of neonatal calves associated with spongy changes in the central nervous system : neuroaxial oedema and the inborn errors of amino acid metabolism

Investigations of neurological disease in neonatal calves were conducted over a four and a half year period. The studies commenced with so called Hereditary Neuraxial Oedema of Poll Hereford calves. It was determined that two distinct disease entities in this breed had led to confusion regarding the diagnosis of this disorder

Public Health Rep

19313676PMCnul