Analysis of Factors Affecting the Decision of the JABODETABEK Community in Using Equity Crowdfunding Platform

This research analyzes the factors that influence the decision to use the equity funding platform in Indonesia. Equity crowdfunding platform is a platform that organizes the crowdfunding process, where investors will receive an equity instrument that provides a share of ownership or a share of future income. This research model is compiled based on the merging of previous research models related to the intention to use the equity funding platform, such as Financing Objectives, Number of Shares Assigned, Number of Inquiries, Familiarity with the Company or Its Product, Target Attractiveness and Campaign Specification. Sources of data were collected from respondents using the equity crowdfunding platform who are JABODETABEK people through a questionnaire, and obtained 428 respondents. The data were analyzed using the SmartPLS 3, and the results show that the variable Familiarity with the Company or Its Product and Target Attractiveness affects people's decisions in using the equity crowdfunding platform.

Bounded Risk Two-stage Estimation Procedure for a U(aq, bq) Distribution

In the literature, an extensive work on sequential fixed-width confidence interval for the parameter of U( q, m q) model, where m > 1 is known, is available. In this article, we propose a two-stage sampling procedure for estimating the parameter q of U( aq, bq) distribution, where a < b are positive and known. Here, the risk of an estimator [Formula: see text] of q is less than a pre-assigned number w (>0), that is, [Formula: see text], 0 < A < ∞ is known. We determine the parameter Bk of stopping variable so that the risk is uniformly bounded by a pre-assigned value w. We have also tabulated the values of the expected stopping time and its standard deviation (SD).

Circuit-Based Electrothermal Simulation of Multicellular SiC Power MOSFETs Using FANTASTIC

This paper discusses the benefits of an advanced highly-efficient approach to static and dynamic electrothermal simulations of multicellular silicon carbide (SiC) power MOSFETs. The strategy is based on a fully circuital representation of the device, which is discretized into an assigned number of individual cells, high enough to analyze temperature and current nonuniformities over the active area. The cells are described with subcircuits implementing a simple transistor model that accounts for the utmost influence of the traps at the SiC/SiO2 interface. The power-temperature feedback is emulated with an equivalent network corresponding to a compact thermal model automatically generated by the FANTASTIC tool from an accurate 3D mesh of the component under test. The resulting macrocircuit can be solved by any SPICE-like simulation program with low computational burden and rare occurrence of convergence issues.

Comparing System Optimum-based and User Decision-based Traffic Models in an Autonomous Transport System

The paper introduces a framework to perform the demand management and route planning tasks of a highly developed transport system managing scheme, assuming an autonomous transport system. Two types of autonomous transport system managing models have been introduced. In case of the first model, the assigned number of trips is assumed to be the modified variable related to the optimization problem. In case of the second model, the decision process is directly influenced by the travel prices defined by the optimization method. These approaches represent different demand management strategies. The first model aims to directly assign the incoming user demands to the system, while the second procedure lets the users make the decision. However, in the second case the system can strongly influence the users’ choices through the values of the travel prices. Accordingly, it seems to be a reasonable assumption that the firstly presented model has significantly higher efficiency in distributing the load on the network. On the other hand, the method of the second model would be much more tolerable and acceptable from a social point of view. Therefore, the aim of the paper is to introduce the developed models and to compare their efficiencies.

Evaluation of Thromboelastometry in Sepsis in Correlation With Bleeding During Invasive Procedures

Prolongation of prothrombin time (PT) is often encountered in patients with sepsis. On the other hand, thromboelastometry as a global coagulation test might yield normal results. The aim of our study was to evaluate whether prolonged PT in the presence of normal thromboelastometry parameters is associated with severe bleeding in patients with sepsis undergoing invasive procedures. In patients with sepsis undergoing low-risk bleeding invasive procedures (central venous catheter placement, dialysis catheter insertion, drain insertion, and so on) or high-risk bleeding invasive procedures (surgical tracheostomy, surgical laparotomy, thoracotomy, and so on), coagulation was assessed by thromboelastometry using EXTEM test (test for evaluation of the extrinsic pathway of coagulation, contains activator of extrinsic pathway) and with PT. For period of years 2013 to 2016, we assessed occurrence of severe bleeding during those procedures and 24 hours later in patients with prolonged PT and normal thromboelastometry results. This retrospective study was performed at Department of Anaesthesiology and Intensive Care Medicine of Motol University Hospital in Prague. Data from 76 patients with sepsis were analyzed. Median value of international normalized ratio (INR) was 1.59 (min—1.3 and max—2.56), and median value of prothrombin ratio (PR) was 1.5 (min—1.23 and max—2.55) with normal thromboelastometry finding. Despite prolonged INR/PR, no severe bleeding was observed during invasive procedures. Our data show that sepsis may be accompanied by normal thromboelastometry results, despite prolonged values of PT, and invasive procedures were performed without severe bleeding. This approach to coagulation assessment in sepsis may reduce administration of fresh frozen plasma to the patients. The study was registered at Clinical Trials.gov with assigned number NCT02971111.

Distributed Generation Capacity Evaluation Using Combined Genetic Algorithm and OPF

A range of techniques has been proposed to define the optimal locations and capacities of distributed generation (DG) as a means of ensuring that the maximum amount of DG can be connected to existing and future networks. However, there are limitations inherent in these methods, not least in finding the best combination of sites for connecting a predefined number of DGs. Here, a method combining optimal power flow and genetic algorithms aims to meet this requirement. Its use would be in enabling Distribution Network Operators to search a network for the best sites and capacities available to strategically connect a defined number of DGs among a large number of potential combinations. Some applications of the proposed methodology confirmed its effectiveness in sitting and sizing an assigned number of DG units.