Validation of Non-destructive Methodology of Grapevine Leaf Area Estimation on cv. Blaufränkisch (Vitis vinifera L.)

This paper evaluates the application of a statistical model to estimate leaf surface area in grapevines, expressed asleaf area of an individual leaf as well as total leaf area per shoot, including any lateral shoots. Estimating the area ofan individual leaf was based on a formula obtained by regression analysis that uses the sum of length of two inferiorleaf veins as an independent variable. To estimate the leaf area per main shoot and per lateral shoot we used themodel derived from multiple regression analysis that has the following independent variables: the number of leaves,and surface area of the largest and of the smallest leaf on the shoot. High values of the coefficient of determination(r2), as well as satisfactory levels of mean absolute error (MAE), suggest that the applied models appear valid. Theseresults have shown a good fit of observed and predicted values of shoot and lateral leaf areas

Restorative and Transformative Justice Responses to Sexual Violence

Background: #MeToo movement raised the profiles of restorative justice (RJ) and transformative justice (TJ) in the United States (US) as approaches to repairing harm resulting from sexual violence that center survivors’ needs and emphasize meaningful accountability for persons responsible for harm. This focus on RJ and TJ as viable approaches to sexual violence represents a departure from carceral interventions, which has dominated the US public discourse for decades. Given the shift, mapping the current state of knowledge is critical for practice, policy and research. This scoping review aims to map the available literature to provide an overview of RJ and TJ as responses to sexual violence. Methods/Design: The proposed scoping review will be conducted in accordance with the Joana Briggs Institute methodology for scoping reviews (Peters, Godfrey-Smith, & Mcinerney, 2017). The concept of interest is the use of RJ and TJ as responses to sexual violence. This scoping review will include both peer-reviewed and grey literature. We will employ a standardized extraction form and represent the data using a descriptive summary, charts and tables that align with the stated objectives. Discussion: Since the #MeToo movement emerged in 2017, public interest in RJ and TJ as meaningful responses to sexual violence has grown. This comprehensive scoping review will systematically organize the literature in order to understand the current landscape of evidence related to these approaches. Given the transformative potential of these interventions, past controversies, and current public interest in the approaches, understanding the current state of knowledge is critical for practice, policy and research

TECHNOLOGICAL CHARACTERISTICS OF SOME NEW PROKUPAC CLONES

The research carried out in experimental vineyard-collection at Faculty of Agriculture experimental field Radmilovac, which is located at GPS coordinates N 44º 45' 21" and E 20º 34' 53". Experimental vineyard is located at southeast part of Belgrade, at an altitude of 130 m and covers southern exposure. It belongs to Šumadijsko-velikomoravski vineyard area, Belgrade sub-region and Grocka vineyard region. Rows were extending in southeast-northwest direction with line spacing of 3 m and 1 m between vines in row. In experiment tested clones were under codes 40/2, 42/1, 43/1 and 43/3. From technological characteristics in paper is presented data related to weight of biomas discarded in pruning, yield, mechanical composition of berries and cluster, structural indicators of berries and bunches and qualitative parameters-sugar and acid content. The biggest mass of pruning shoots was determiner at clone 40/2 (1.008 kg/vine). The highest yield is recorded at clone 42/1 (7.1 kg/grapevine) and the smallest for clone 43/1 (3.6 kg/vine). Maximum cluster mass was recorded at clone 43/1 (276 g), whereas for clone 40/2 was determined the largest weight of berries meat (254 g) and the biggest seeds number per 100 berries (208). Clones 42/1 and 43/1 are characterized with the highest recorded skin weight of 100 berries (10 and 23 g/100 berry). Same trend was recorded for percent of stem, skin and seed in cluster. Clone 42/1 had the lowest percent of meat in berry (88.21%). According to sugar content were founded the highest level for clones 42/1 (24.1%) and 40/2 (22.4%). Same trend of variation is determined for acid content in grape juice

Hybrid Product Cost Calculation Model as a Decision Support Tool

Cost calculation is of huge importance both for determining a rational and competitive price of the product and preparation of offers according to customer\u27s demand, where deadlines for sending offers are limited. In individual and small batch production, which is characterised by a wide product range, reduced quantities, and short delivery times, cost calculation in forming the price of the product according to customer requirements is of essential importance. Traditional methods of calculating the cost of products in these cases are inefficient, considering the number of offers that need to be made, timing, as well as their competitiveness in the market. For product cost calculation in individual and small batch production, it is necessary to apply modern, efficient methods and models based on the application of artificial intelligence. A wide range of products, which is characteristic of individual and small batch production in some companies, enables the development of modern costing models with the use of basic principles of group technology. The constructional and technological similarity of products enables the formation of groups of similar parts and appropriate group technological processes. Combining that with artificial intelligence, it is possible to develop appropriate cost calculation models. This paper presents a developed model for production cost calculation, based on the principles of group technology and adaptive neuralfuzzy networks (ANFIS)

Mathematical Modeling of Heat Transfer of Liquefied Natural Gas Engines

The article presents a mathematical model for pressure growth in the line supplying the engine KAMAZ with cryogenic fuel under specific insulation conditions. By using the heat balance equation the model in a simple linear form is obtained. This makes the model suitable for use in solving practical tasks related to the design of a liquefied natural gas engine fuel system. According to the above-mentioned method, the geometric parameters of the section of the main elements are determined under different external conditions and the boundary parameters of the gas fuel (maximum and minimum values of pressure, temperature, and flow). These data are necessary to determine the consumption, hydraulic and project features of the project. Fuel pipes are optimized (for hydraulic resistance, pressure and flow impulses, structural strength) to improve the accuracy of fuel dosing. The adequacy of the model was tested on a special modified test stand

Models of wages and incentives contracts in the conditions of information asymmetry on the labor market

The theoretical model of a perfectly competitive market leads to the efficient allocation of resources, and one of the assumptions of that model is complete information of market participants. In reality, however, market participants are usually asymmetrically informed. The goal of this analysis is to point out the fact that asymmetric information is almost ubiquitous, and also to point out the consequences of asymmetric information and the possibility of their elimination or mitigation. In addition, the research aim also reflects in achieving a theoretical confirmation of the presence of such asymmetric information and its consequences on the labor market as well, and in an attempt to mathematically formalize such markets, especially the labor market, by modeling the method of calculating wages and the employer’s objective function as an opportunity to overcome the principal-agent problem. The precisely defined research goals determined the structure of the paper, as well as the methodological tools. In order to test and prove the defined research hypotheses in this study and to realize the defined research goals of the study, the methods of theoretical analysis, abstraction, comparison, concretization, generalization, and critical evaluation are used

An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem

With the widespread deployment of smart meters worldwide, quantification of energy used by individual appliances via Non-Intrusive Load Monitoring (NILM), i.e., virtual submetering, is an emerging application to inform energy management within buildings. Low-frequency NILM refers to NILM algorithms designed to perform load disaggregation at sampling rates in the order of seconds and minutes, as per smart meter data availability. Recently, many deep learning solutions for NILM have appeared in the literature, with promising results. However, besides requiring large, labelled datasets, the proposed deep learning models are not flexible and usually under-perform when tested in a new environment, affecting scalability. The dynamic nature of appliance ownership and usage inhibits the performance of the developed supervised NILM models and requires large amounts of training data. Transfer learning approaches are commonly used to overcome this issue, but they often assume availability of good quality labelled data from the new environment. We propose an active learning framework, that is able to learn and update the deep learning NILM model from small amounts of data, for transfer to a new environment. We explore the suitability of different types of acquisition functions, which determines which function inputs are most valuable. Finally, we perform a sensitivity analysis of the hyperparameters on model performance. In addition, we propose a modification to the state-of-the-art BatchBALD acquisition function, to address its high computational complexity. Our proposed framework achieves optimal accuracy-labelling effort trade-off with only 5-15% of the query pool labelled. The results on the REFIT dataset, demonstrate the potential of the proposed active learning to improve transferability and reduce the cost of labelling. Unlike the common approach of retraining the entire model once a new set of labels is provided, we demonstrate that full re-training is not necessary, since a fine-tuning approach can offer a good trade-off between performance achieved and computational resources needed

PRODUCTIVE AND TECHNOLOGICAL CHARACTERISTICS OF TABLE VARIETIES GROWE IN THE CONDITIONS OF OPLENAC VINEYARDS

Investigations were carried out in vineyard of King Petar I Karadjordjevic Foundation of at Oplenac. In experiment were tested four table grapes varieties: Black Magic, Victoria, Michel palieri and Muscat Hamburg. Training system is characterized with height of 90 cm on which Guyot pruning is used. In research is studied vegetative potential, fertility, mechanical composition of grape and berries and sugar content and acidity. In red varieties is determined anthocyanins concentration. Michel palieri was with the largest vegetative potential expressed through shoot mass (0,590 kg/vine). The highest values of fertility parameters (number productive shoots, number of inflorescences on spur and arc, coefficients of fertility) had a variety Muscat Hamburg. The highest sugar content was determined in Muscat Hamburg must, a total acid in Victoria variety must. According to anthocyanins Mikele palieri content variety is dissociate (0.179 mg/g fresh weight)