The amount of heat input to the weld per unit length and per unit volume

This paper presents a comparative analysis of heat input per unit length and per unit volume for selected methods of welding. The purpose of the analysis is to assess the usability of calculating heat input per volume unit. The interpretation of heat input per unit length according to the standards: QW-409.1 of ASME IX, EN ISO 1011-1 is discussed. The concept of calculating heat input per unit volume is described. For exemplary padded welds and spot welded joints, the heat input values were calculated in accordance with the above-mentioned standards and based on the concept of heat input per unit volume. The study showed a lack of consistency between the individual standards in the interpretation of the heat input. In addition, the practical application of the heat input per unit volume method in calculating the actual amount of heat introduced into the weld was justified.

PECULIARITIES OF ESTATE OF THE NATIONAL GEODESIC NETWORK IN THE CENTRAL REGION OF UKRAINE

A common feature of NGN in the central region of Ukraine is aging. The differences are determined by the peculiarities of fixing its points on the locallity place. The choice of a specific type of geodetic signal was determined by local physical and geographical features of the location of the point, such as: soil properties, depth of soil freezing, visibility conditions, etc. On the territory of Poltava and Kirovohrad regions there are 70 types of centers, benchmarks and brands, which are fixed points of the planimetric, altitude and gravimetric networks. At the same time, only 9 types significantly prevail of distribution: soil centers and benchmarks for areas with shallow (up to 1.5 m) seasonal soil freezing of types 1, 1op, 2, 2op, 146, 160 and 160 Late; wall benchmarks type 143 and wall beacons type 144. The peculiarity of the central region of Ukraine is the presence of points that are both points of the planimetric NGN 1, 2 and 3 classes, and altitude NGN I or II classes. Thus such points are fixed either by the ground centers, or ground benchmarks, or horizontal beacons. Because of the lack of geodetic information on a significant part of the points of the planned and altitude networks, the condition of the NGN of the central region of Ukraine cannot be considered satisfactory at present. For the requirements of monitoring, it is proposed to expand the content of maps of construction, survey and updating of geodetic points with data on the rights of ownership or use of land locations of points and their cadastral numbers. It is also necessary to update the data on those points in the central region of Ukraine, the inspection of which was realized before 2010. The indicator of admissibility of losses of points of NGN which should be defined separately for networks of 1, 2 and 3 classes is offered. If according to the results of the calculation the actual amount of points is less than the minimum allowable for the corresponding class, and the indicator of admissibility of losses of points has a minus sign, then the corresponding network does not meet the technical parameters. Loss of points in this case is not allowed, and lost points must be restored. The results of the calculation of this indicator for the central region of Ukraine indicate the need to restore 6 points of the planimetric network of the 2 class in the Kirovohrad region and the inadmissibility of further losses of points of this class.

A Prediction Model of Forest Preliminary Precision Fertilization Based on Improved GRA-PSO-BP Neural Network

The optimal amount of fertilizer application which was needed by the trees and the factors that influence the fertilization have an intricated nonlinear relationship. According to the problems that the traditional fertilization prediction model has, such as lacking of the scalability and practicality, this paper initiates an accurate fertilization prediction model that was based on the GRA-PSO-BP neural network which can make the accurate fertilization come true and improve the economic benefits of forest industry. This paper uses the GRA method to determine the input of the neural network as the site index and make the forest age, nutrient content of the advantage trees, biomass of the advantage trees, biomass of average trees, and target yield as the output numbers of the Actual amount of fertilizer applied. During the calculation process, the global particle swarm optimization algorithm is used to optimize the initial numbers and threshold numbers of BP neural network which build a phased GRA-PSO-BP accurate fertilization model. Compared with the prediction algorithm of full input variate that is based on the single BP neural network and the prediction algorithm of full input variate that is based on PSO-BP Neural Network, the GRA method can determine the key factors that influence the amount of fertilizer applied in different forest areas and modify the prediction model to improve the scalability and accuracy of the prediction and finally achieve the precision fertilization as the data of different forests updated, so we can see that the prediction result of this paper is more accurate. The result demonstrates that the GRA-PSO-BP neural network Segment fertilization model is more accurate than the traditional BP neural network and BP Neural Network that was optimized by the PSO algorithm, and specifically, the error of the predicted amount of fertilizer application and the actual amount of fertilizer application is less than 5%, which can effectively guide the fertilization in stages.

ANALISIS KEBUTUHAN UDARA PEMBAKARAN UNTUK MENGOPTIMALKAN PROSES PEMBAKARAN BOILER PT. PLN (PERSERO) SEKTOR PEMBANGKITAN ASAM ASAM UNIT 3 & UNIT 4

The performance of a power plant unit is strongly influenced by various aspects, one of which is very determined by how the combustion process occurs in the combustion chamber, because it can affect the efficiency of the power plant itself, especially in the efficiency aspects of the boiler combustion process. To find out the efficient operation of the boiler, the operator as the holder of the power plant must understand what the combustion process is like in it. Good combustion will always require the right combination of fuel and air (oxygen). From the results of the research that has been done, it can be seen that if the actual amount of air flow needed for the combustion process is closer to the ideal air flow value it will indirectly increase the combustion efficiency value of the boiler.

Evaluating the Recessionary Impact on Election Administration Budgeting and Spending

Recent research indicates the need to understand the role financial resources play in election administration. A key question is, when considering “financial resources,” how much does economic hardship affect the differences between the budgeted amount and the actual amount spent?. The limited research that has examined this question comes from the United Kingdom; it shows that there are significant differences between the two measures and they vary systematically based upon fiscal environmental conditions. This research examines whether the fiscal environment influences election administration budgets, spending, and the resulting budget variance in local US jurisdictions. Using county election administration spending data from four states, this research indicates election administration budgets, spending, and variances are related to the fiscal environment. Not only does this work have implications for measurement of election cost, but this work is key to understanding the financial situation election administration faces given pandemic-related economic woes.

The Hidden Welfare State

Are a trillion dollars in middle-class entitlement programs really hidden in the tax code? Yes, give or take . . . The actual amount is in dispute for reasons we’ll get to, but many spending programs, big and small, are run through the income tax....

Dragnet: A Method for Tagging Bitcoin Addresses of Exchanges

<div>Currently, there are hundreds of Bitcoin exchanges on the market, so choosing a reliable exchange is a critical issue for users. We know that the amount of Bitcoin holdings is an essential indicator for evaluating an exchange, but people have very few ways to access this information. Besides, many reports indicate that the trading volumes of most Bitcoin exchanges do not match their real situations, and the fake volume has become an unspoken rule of the whole industry. It causes the public to doubt the actual amount of Bitcoin owned by each exchange.</div><div> </div><div>To solve the problem of information asymmetry between users and exchanges, we propose a method for tagging Bitcoin addresses of exchanges. Through vertical, forward, and backward address mining, the method can utilize only one or several addresses of an exchange to find out all its addresses and distinguish different address types: deposit wallet, hot wallet, and cold wallet. Then the balance and transfers of the exchange can be further obtained through these addresses, helping users understand the real Bitcoin holdings of the exchange. Several experiments are conducted to evaluate the effectiveness of the proposed Bitcoin address tagging method.</div><div> </div><div>Our method has very little dependence on off-chain information. Only one address is needed for each exchange as a seed to find out all the other addresses. Such a seed address can be easily obtained by depositing some Bitcoin into the exchange or withdrawing some from it, which makes our method feasible for all exchanges.</div>

Dragnet: A Method for Tagging Bitcoin Addresses of Exchanges

<div>Currently, there are hundreds of Bitcoin exchanges on the market, so choosing a reliable exchange is a critical issue for users. We know that the amount of Bitcoin holdings is an essential indicator for evaluating an exchange, but people have very few ways to access this information. Besides, many reports indicate that the trading volumes of most Bitcoin exchanges do not match their real situations, and the fake volume has become an unspoken rule of the whole industry. It causes the public to doubt the actual amount of Bitcoin owned by each exchange.</div><div> </div><div>To solve the problem of information asymmetry between users and exchanges, we propose a method for tagging Bitcoin addresses of exchanges. Through vertical, forward, and backward address mining, the method can utilize only one or several addresses of an exchange to find out all its addresses and distinguish different address types: deposit wallet, hot wallet, and cold wallet. Then the balance and transfers of the exchange can be further obtained through these addresses, helping users understand the real Bitcoin holdings of the exchange. Several experiments are conducted to evaluate the effectiveness of the proposed Bitcoin address tagging method.</div><div> </div><div>Our method has very little dependence on off-chain information. Only one address is needed for each exchange as a seed to find out all the other addresses. Such a seed address can be easily obtained by depositing some Bitcoin into the exchange or withdrawing some from it, which makes our method feasible for all exchanges.</div>

Using Thermal Imaging to Detect Deception Following a Staged Theft

We conducted an experiment to test whether thermal imaging could detect deception. Half of the participants (n = 42) were randomly assigned to be “thieves” by stealing money from an unattended briefcase. The other half (n = 41) were randomly assigned to be “innocent suspects.” Immediately after the simulated theft, we interrogated all participants, although we instructed them to deny any involvement in the theft. During the interrogation, we measured each participant’s facial temperature using a consumer-grade, infrared thermometer. We hypothesized that lying would produce physiological reactions resulting in elevated skin temperatures. Although nearly all group means showed that thieves had higher skin temperatures than innocent suspects, most of the differences were not statistically significant. However, we found that thieves had statistically significantly higher skin temperatures when asked about the actual amount of money that was stolen. Thus, we found that thermal imaging was able to detect that thieves had concealed information regarding the mock crime. Thieves also reported statistically significantly more anxiety from the beginning to the end of the interrogation.