OUR INDIAN SHOP – E-Commerce Website Interconnecting the Farmers, Shopkeepers, Delivery Personnel and Consumers

A system named ‘Our Indian Shop’ has been developed and presented in this paper. This system involves an android application, a website and an IVR system for online selling and delivery of agricultural products from farmers to the consumers directly at the market price without the involvement of any middleman. It provides facilities of online shopping of essentials from consumers’ nearby shops as the delivery options will be localized according to pin code to lower the risks of spreading of Covid-19. It also supports selling of groceries, vegetables, and medicines by relevant shop owners directly to the consumers. It enhances the employment as delivery personnel for economically backward people or daily wagers who have lost their livelihood due to the pandemic. The IVR system is to be provided to make all the above facilities available in the offline mode for technologically backward classes, for efficient working of the system in a digital divide environment. The prime objective of this development is to promote social distancing and provide efficient technical solutions for sustainability in the post pandemic world. Our Indian Shop is an all in one platform which provides the online facilities of shopping and selling as well as it will help to enhance the employment and prevent the brokerage charges.

Exact Techniques for Hardware Modelling of Machine Learning Algorithms with Building of Neuron Network

System getting to know algorithms are complicated to version on hardware. that is due to the truth that those algorithms require quite a few complicated design systems, which are not effort lessly synthesizable. Therefore, through the years, multiple researchers have developed diverse kingdom-of-the artwork techniques, every of them has sure distinct advantages over the others. In this newsletter, we compare the specific strategies for hardware modelling of the various device gaining knowledge of machine learning algorithms, and their hardware-stage overall performance. this newsletter could be useful for any researcher or gadget dressmaker that needs to first evaluate the superior techniques for ML layout, and then inspired with the aid of this, they are able to similarly enlarge it and optimize the device’s performance. Our assessment is based on the 3 number one parameters of hardware layout; that is; place, power and postpone. Any layout approach that can find a stability among those three parameters may be termed as greatest. This work additionally recommends sure enhancements for some of the techniques, which can be taken up for similarly studies. Machine Learning is a concept to find out from examples and skill, while not being expressly programmed. Rather than writing code, you feed knowledge to the generic formula, and it builds logic supported the info given. for instance, one reasonably formula could be a classification formula. It will place knowledge into totally different teams. The classification formula accustomed notice written alphabets may even be accustomed classifies emails into spam and not-spam. Machine learning has resolve many errors ranging from simple arithmetic problems like TSP (Travelling Salesman Problem) to complex issues like predicting the variations in stock market price, Machine learning algorithms like genetic algorithm, particles swarm optimization, deep nets and Q-learning are currently being developed on software platforms due to the ease of implementation. But the full utilization of core algorithms can only be possible. If they are designed & integrated inside the silicon chip. Companies like Apple, Google and Snapdragon etc. are continuously updating their ICs to incorporate these algorithms. But there is no standard architecture defined to implement these algorithms at chip level, due to these inefficiencies of every alternative multiply when these devices connected together. In this research work, we plan to develop a standard architecture for implementation of machine learning algorithms on integrated circuits so that these circuits. connected together work seamlessly with each other & improve the overall system performance. Finally, we planned to implement at least two algorithms on the proposed architecture & verify its optimization capability for practical systems. Our assessment is based on the 3 number one parameters of hardware layout; i.e.; place, power and postpone. Any layout approach that can find a stability among those three parameters may be termed as greatest. This work additionally recommends sure enhancements for some of the techniques, which can be taken up for similarly studies. Machine learning has solved many problems ranging from simple arithmetic problems like TSP (Travelling Salesman Problem) to complex issues like predicting the variations in stock market price, Machine learning algorithms like genetic algorithm.

Credit Risk in G20 Nations: A Comparative Analysis in International Finance Using Option-Adjusted-Spreads

Corporate bond yields are the manifestation of the cost of financing for private firms, and if properly evaluated, they provide researchers with valuable risk information. Within this context, this work is the first study producing corporate yield spreads for all S&P-rated bonds of G20 nations to explain their comparative riskiness. The option-adjusted spread analysis is an advanced method that enables us to compare the bonds with embedded options and different cash flow characteristics. For securities with embedded options, the volatility in the interest rates plays a role in ascertaining whether the option is going to be invoked or not. Therefore, researchers need a spread that, when added to all the forward rates on the tree, will make the theoretical value equal to the market price. The spread that satisfies this condition is called the option-adjusted spread, since it considers the option embedded into the issue. Ultimately, this work investigates the credit risk differentials of S&P rated outstanding bonds issued by the G20 nations to provide international finance professionals with option-adjusted corporate yield spreads showing the credit risk attributable to debt instruments. Detailed results computed using OAS methodology are presented in tables and used to answer the six vital credit-risk-related questions introduced in the introduction.

Approaches towards Land Valuation and Land Pricing under the Influence of Geo-Climate Change

The Czech Republic is more or less unique in its dual system (official and market price) of agricultural land prices. In the case of the market price, there are several studies and approaches that assess the impact of individual variables on the market price of land. If we focus on the official price of land, its value in the Czech Republic is influenced by the evaluated soil ecological unit (ESEU) price. The ESEU price expresses the production potential of the land on the basis of soil quality indicators, which include the climatic region, the main soil unit, slope and exposure and, last but not least, the depth of the soil profile and skeletonisation. Climate change also means that the current values of the definition (e.g., for a climatic region, this refers to the average temperature or average precipitation) do not correspond to reality. No studies have looked in detail at the impact of soil quality indicators or climate change on the price of ESEUs. New and more accurate measurements of soil characteristics are increasing the number of ESEU codes, and prices have not yet been set for some codes. For this reason, we proposed the use of a hedonic method to determine shadow prices, which reflect the intensity and direction of the effect of each input variable on the price of an ESEU. A heteroscedastic corrected linear regression model was used to determine the coefficients, which presents in detail the effect of all included parameters on the final price of an ESEU in the results section. From the results, it was obvious that the shadow price coefficients themselves corresponded to basic generally accepted assumptions regarding the direction of effect. In the conditions of the Czech Republic, a significant influence on the price of an ESEU was mainly the slope with exposure and the depth of the soil profile with skeletonisation. These factors affected the productive capacity of the soil, which, in turn, translated into lower profitability of agricultural entities. The high explanatory ability of the hedonic model, with a high parametric significance for most of the used variables, was an important factor determining the robustness of the model as a repricing tool. The model set according to the prices of the applicable price decree can be used to set the prices of new or not-yet-valued ESEU codes under the conditions in the Czech Republic, or shadow prices can be used during climatic changes in the event of the transfer of the given soil unit to another climate region according to the general specification. It is therefore an important tool for the needs of the public administration.

Effect of biomass-based carbon capture on the sustainability and economics of pulp and paper production in the Nordic mills

Bioenergy with carbon capture and storage (BECCS) is one of the key negative emission technologies (NETs). Large-scale implementation of BECCS has been criticized of the associated increase in land use. The existing large Nordic pulp and paper production units enable BECCS deployment without additional land use, as they currently release large amounts of bio-based carbon dioxide (CO2). The application of BECCS in pulp mills has been found technically feasible in earlier studies. This study explores key factors that affect the propensity to invest in BECCS in different types of existing European pulp and paper mills. The results give fresh understanding on the effects of BECCS on the market price of pulp and paper products and the required level of incentives. Based on statistical data, the marginal carbon dioxide credit (€ per ton CO2) to make BECCS profitable was derived. The results show that the required level of credit greatly depends on the mill type and details and that the feasibility of BECCS does not clearly correlate with the economic performance or the measured efficiency of the mill. The most promising mill type, a market kraft pulp mill, would find BECCS profitable with a credit in the range of 62–70 €/tCO2 and a credit of 80 €/tCO2 would decrease pulp production costs by 15 €/tproduct on average if 50% of CO2 emissions was captured. The EU Emission Trading System (ETS) is the main policy instrument to achieve the climate targets related to fossil energy use, but does not yet contemplate bio-based emissions.

Faktor yang Mempengaruhi Return Saham dengan Harga Saham sebagai Variabel Moderasi (Studi Kasus pada Perusahan Perbankan yang Terdaftar di BEI)

This study aims to know the factors that impact stock return with Market Price as the moderating variable of the banking company listed on the IDX from 2015 to 2020. The data is retrieved from idx.co.id. The population of this article is 43 banking companies, and to select the sample for this article has used purposive sampling and has selected 11 companies. The analysis method of this article has used descriptive statistics. The data has gone through BLUE (best linear unbiased estimator) test, such as normality test, autocorrelation test, multicollinearity test, and heteroscedasticity test before doing the hypothesis test. Further, the analysis data has used F-test, t-test, the equation of multiple linear regression, determination coefficient, and moderation. The study's findings are that, partially, LDR does not affect SR, ROA does not affect SR, and BOPO does not affect SR. PBV can not moderate the effect of LDR, ROA, and BOPO on stock return. The determination coefficient is 0.048 (4.8%), which means that the LDR, ROA, and BOPO have impacted SR as much as 4.8%, and the remaining is affected by other factors. The contribution of the research is to help the investors select the right stock.

Is It Possible to Monetarily Quantify the Emotional Value Transferred by Companies and Organizations? An Emotional Accounting Proposal

Social accounting focuses on value transactions between organizations and their stakeholders; both market ones, where the value perceived by the different stakeholders is identified, and non-markets ones, where transactions are monetized at their fair value. There was long awareness of an emotional value translation, linked to the transfer of different products, services, remunerations, and incentives, regardless of whether they were market or non-market. Yet that emotional value seemed to be anchored in the field of psychology and managed to elude economic science. This study seeks to identify emotional value with consumer surplus and, by extension, of the other stakeholders in a value transfer process. This proposal allows the emotional value to be anchored in the micro-economy and allows it to be objectively calculated using a regression involving three elements: the market price, the fair value interval, and a perceived satisfaction score by the different stakeholders in the form of significant sampling. The result obtained not only allows Social Accounting to be complemented with emotional value, but it also facilitates its incorporation in the strategy to optimize the emotional value. Furthermore, it enables a quantification of the perceived subjective utility, which opens up a research path where some possible lines are clearly identified.