Breed Recognition and Estimation of Live Weight of Cattle Based on Methods of Machine Learning and Computer Vision

A method of measuring cattle parameters using neural network methods of image processing was proposed. To this end, several neural network models were used: a convolutional artificial neural network and a multilayer perceptron. The first is used to recognize a cow in a photograph and identify its breed followed by determining its body dimensions using the stereopsis method. The perceptron was used to estimate the cow's weight based on its breed and size information. Mask RCNN (Mask Regions with CNNs) convolutional network was chosen as an artificial neural network. To clarify information on the physical parameters of animals, a 3D camera (Intel RealSense D435i) was used. Images of cows taken from different angles were used to determine the parameters of their bodies using the photogrammetric method. The cow body dimensions were determined by analyzing animal images taken with synchronized cameras from different angles. First, a cow was identified in the photograph and its breed was determined using the Mask RCNN convolutional neural network. Next, the animal parameters were determined using the stereopsis method. The resulting breed and size data were fed to a predictive model to determine the estimated weight of the animal. When modeling, Ayrshire, Holstein, Jersey, Krasnaya Stepnaya breeds were considered as cow breeds to be recognized. The use of a pre-trained network with its subsequent training applying the SGD algorithm and Nvidia GeForce 2080 video card has made it possible to significantly speed up the learning process compared to training in a CPU. The results obtained confirm the effectiveness of the proposed method in solving practical problems

Characterization of a major modifier locus for polycystic kidney disease (Modpkdr1) in the Han:SPRD(cy/+) rat in a region conserved with a mouse modifier locus for Alport syndrome.

The genetic analysis of rodent disease models provides a powerful tool to investigate how modifier loci cause variation in the phenotypic expression of a disease. In order to test the existence of modifier loci influencing polycystic kidney disease (PKD) phenotypes, we derived a backcross between PKD susceptible Han:SPRD(cy/+) and control Brown Norway (BN) rats, and performed a whole-genome scan in 182 PKD affected hybrids showing different grades of disease severity. The genetic dissection of PKD in the cross allowed us to detect a modifier locus, Modpkdr1, on rat chromosome 8 that controls PKD severity, kidney mass and plasma urea concentration. Results from database searches and computational analyses demonstrated that the Modpkdr1 locus shows strong evidence of synteny conservation with human and mouse chromosomal regions controlling kidney diseases, including disease progression of Alport syndrome. Comparative genome mapping also provided an inventory of potential candidate genes for modifier(s) of PKD. Analyses of the coding regions for four strong candidates (Ctsh, Bcl2a1, Trpc1 and Slc21a2) in (cy/+), BN and Lewis rat strains did not reveal sequence variants that could be associated with PKD. The characterization of Modpkdr1 may provide new insights into modulating mechanisms involved in the pathogenesis of PKD that could delay disease progression in humans. It may also have strong implications in the identification of pathophysiological factors common to different renal disorders

An approach to quantitative assessment of inbound tourism impact on the country’s economy

У статті запропоновано підхід до кількісної оцінки впливу в’їзного туризму на економіку країни, що заснований на застосуванні теорії нечіткої логіки та системи нечіткого логічного виведення. Як фактори, на основі яких робиться висновок, були обрані кількість іноземних туристів, що прибувають в країну, середня кількість грошових надходжень, одержуваних від одного іноземного туриста і відсоток населення країни, зайнятого в індустрії подорожей і туризму. Для отримання результату були визначені необхідні лінгвістичні терми для оцінки вхідних змінних, побудовані функції належності для всіх лінгвістичних термів; створена база правил з використанням методу парних порівнянь; обчислена ступінь істинності кожного правила і проведена дефазифікація за методом центру ваги. Запропонований підхід дозволяє отримати кількісну оцінку впливу в’їзного туризму та її якісний еквівалент. Використовуючи даний підхід з іншими вхідними параметрами можна проводити кількісне оцінювання будь-якої системи, що має аналогічну природу.В статье предложен подход к количественной оценке влияния въездного туризма на экономику страны, основан-ный на применении теории нечеткой логики и системы нечеткого логического вывода. В качестве факторов, на основе которых делается вывод, были выбраны количество иностранных туристов, прибывающих в страну, среднее количе-ство денежных поступлений, получаемых от одного прибывшего туриста, и процент населения страны, занятого в индустрии путешествий и туризма. Для получения результата были определены необходимые лингвистические термы для оценки входных переменных, построены функции принадлежности для всех лингвистических термов; создана база правил с использованием метода парных сравнений; вычислена степень истинности каждого правила и проведена де-фазификация по методу центра тяжести. Предложенный метод позволяет получить количественную оценку влияния въездного туризма и ее качественный эквивалент. Используя данный подход с другими входными параметрами можно проводить количественную оценку любой системы, имеющей аналогичную природу.Today tourism is one of the leading sectors of the global and the regional economy. But along with the positive impact of tourism on the country's economy, there are certain factors which are negative. The purpose of this article is to formulate and justify an approach to the calculation of quantitative assessment of the inbound tourism impact on the country's economy and its qualitative equivalent. To reach this goal, the application of the theory of fuzzy logic and fuzzy inference system was used. Fuzzy inference includes all the main components of the theory of fuzzy logic, such as linguistic variables, membership functions, meth-ods of fuzzy implication. As a method for the implementation of fuzzy inference the simplified fuzzy inference algorithm was cho-sen. As input parameters to carry out the calculation of the impact on the country's economy the number of international tourist arrivals to the country, the average receipts per arrival and the percentage of employment in the travel and tourism industry were chosen. To obtain the result, the necessary linguistic terms to estimate the input variables were determined; membership functions were constructed for all linguistic terms; a rule base (the set of if-then rules that define the relationships between the input and output of the system) was built; a firing strength of each rule on the base was obtained and the result was obtained by the centre of gravity method. Using this approach, a numerical experiment was carried out to quantitatively determine the in-bound tourism impact assessment on the economies of 6 countries as well as the qualitative equivalent of this assessment in ac-cordance with the verbal-numerical Harrington scale. This numerical experiment shows, that countries such as the USA, China and France have positive or even high positive impact on their economies, Poland and Bulgaria have low positive impact and Ukraine has negative inbound tourist impact on the country's economy.Using this approach with other input parameters, it is possible to perform an assessment (quantitative and qualitative) of any systems of a similar nature