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In-depth research on inventory models has helped businesses find a way to deal with the uncertainty of customer demand. Stockouts of raw materials and high total inventory costs are two issues that might arise for businesses that do not apply inventory models when making purchases. However, traditional methods of analysis cannot be used to solve inventory models with stochastic demand because of the deviation from the normal distribution of its demand. To handle inventory problems with stochastic and intermittent demand, a Monte Carlo simulation method was used for this study. The continuous inventory review policy (Q, R) and the periodic inventory review policy (s, S) are the two types of inventory systems that are being evaluated through simulations. The integer linear programming method is used to optimize the simulation models utilizing the (Q, R), and (s, S) inventory models. The models are applied based on the data from one of the jewelry manufacturing companies in Indonesia, with the product being tested was diamond jewelry. In terms of total inventory costs for the component raw material group, the results showed that the continuous inventory review policy (Q, R) is better than the periodic inventory review strategy (s, S). [ABSTRACT FROM AUTHOR]

The unknown shape parameter of the inverse Kumaraswamy distribution and some other life-time properties such as the reversed hazard rate function (RHRF) deriving based on complete data, and imposed another shape parameter is known were introduced. Three methods for estimating the reversed hazard rate function were used. Maximum likelihood estimation (MLE) method was used for the non-Bayesian estimator, as well as using the Bayesian estimators with two informative priors (Gamma and Exponential) under symmetric (squared error loss (SEL) function) and asymmetric (entropy loss (EL) function) to estimate the reversed hazard rate function, which was approximated using a numerical method (Boubaker polynomials (BbP) method). The different estimators were compared experimentally by adopting the Monte Carlo simulation study, also comparing the estimators and the approximation for the reversed hazard rate function depending on the integrated mean squared error (IMSE). The program (MATLAB 2015) was used to obtain the numerical calculations. [ABSTRACT FROM AUTHOR]

Pricing a cyber insurance is challenging for actuaries due to the dynamic changes in hackers' skills and cyber security technologies. Cyber attacks on one computer can infect other computers and affect the network system. This article will discuss an insurance model for a network of computers, which provides financial protection against viruses and malware. In the model, individual computers are assumed to be in one of two states daily: healthy (susceptible) or infected. The competitive risk simulation is applied to update the status of each computer in the network. In the present paper, we present a modified cumulative distribution function that enables us to model a computer system that operates only during work hours. The average annual cost of a computer network arising from a cyber-attack is calculated through the Monte Carlo simulation. We also present a more efficient algorithm that reduces the computation time of the Monte Carlo simulation. In order to the mathematical model to be more easily used by practitioners in creating insurance products, we propose a comprehensive model for internal infection, which also reduces the computation time. The insurance can financially help the company to repair the network and prevent data breaches. The insurance risk indicators, namely the expected present value (EPV), the Value at Risk (VaR), and the Tail Value at Risk (TVaR) of the annual benefit payouts, can be computed for different scenarios of risks. Simulations were carried out for several scenarios of parameter values, which represent differences in system vulnerability in the face of virus and malware infections. [ABSTRACT FROM AUTHOR]

In this article, the parameters of the transformed circular gamma distribution (CTG) were estimated using the Maximum Likelihood method and the Moments method using Monte-Carlo simulation using MatLab program by assuming three sets of theoretical values for (α, β).) are α = 0.1,2,6 and β = 0.2, 0.1,8, and different sample sizes (25, 50, 75, 100) as the data of the random variable that follows the CTG distribution was generated and the parameters of the distribution were estimated using the two methods, and the comparison was also made Between the transformed circular gamma distribution and the traditional gamma distribution using the comparison criteria AIC, BAIC, AICc, and HQIC, As well as finding some properties of the circular transformed distribution, such as the distributive function, moments and the Unimodality function. It was concluded through simulation experiments that the transformed circular gamma distribution is better than the gamma distribution, as well as the superiority of the Maximum Likelihood method over the moments at large sample sizes and for all simulation experiments, and that the estimated parameters of the circular gamma distribution are closer to the default parameters. [ABSTRACT FROM AUTHOR]

Generally, the distributed energy storage systems (DES) can be defined as a set of small size of storage energy systems that allocated on the electrical distribution network and more specifically at the customer building side or the distribution substation. Indeed, the DES is expected to be sorely needed and with penetration, levels exceed the DG units in the future, as the DES associated with a significant number of benefits in terms of supporting renewable energy resources, improving power quality and reliability as well as managing the produced energy and the required demand. Energy storage systems provide several benefits in terms of assisting utilities toward achieving their goals. One of these benefits is improving the reliability of the system through effective islanding operation. Shortly, the reliability of the distribution grids is considered as an important objective with DG and DS units that need further investigation and research with considering the effective approach. Therefore, this research focuses on finding the optimal energy storage units location with the amount of load that need to be shed to improve the overall reliability of these systems through using particle swarm optimization technique (PSO). The general method that will be used in this research includes two phases, which will be solved and analyzed through using particle swarm optimization method (PSO) in order to reduce the objective function of this research. The first phase will perform load flow to calculate power requirement for energy storage will the second phase will apply a sequential Monte Carlo simulation (MCS) to the whole system to check the operation mode of the system. A 33-bus radial test system was used to in this study with four different storage systems that compared with the base case of without any DS units allocated in the test system. [ABSTRACT FROM AUTHOR]

Fast neutron radiography is a technique with high potential in inspecting large industrial components. The PADC material's high sensitivity to fast neutrons and light ions could be a promising imaging technique. This work is focused on studying the combination of PADC detectors with polyethylene radiators. The results of Monte Carlo simulations are compared to the experimental results. The findings will be applied in the follow up experiments, aiming to demonstrate the PADC material usage in fast neutron radiography. [ABSTRACT FROM AUTHOR]

The magnetic ground state of intercalated monolayer α-NbSi2N4 is investigated using first principles calculations. Recent debate on conduction character of the ground state questions importance of a proper description of the Nb d-electrons. Here we discuss the effect of the Hubbard on-site potential on the magnetic splitting of the conduction band resulting in the transition from the conducting to the semiconducting state. We determine exchange parameters for nearest and second nearest neighbours, and magnetic anisotropy parameters for classical Heisenberg model on a triangular lattice of the Nb atoms. The critical temperature 푇푐 = 440.3 K for ferromagnet - paramagnet transition was determined using Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

As the number of populations worldwide, including Indonesia, increases annually, the need for electrical energy also increases. With fossil-based energy starting to decrease in some places, and the global need to achieve net zero-emission, renewable energy is gaining popularity as the source of electrical power generation, for example, wind energy. Electrical power generated from wind turbines is one of the popular choices in many countries; among them is the Sidrap wind turbine plant in Sulawesi, Indonesia. Electrical power generated by a wind turbine relies on the wind speed, which varies from time to time and season to season. Therefore, building wind turbines plant should not be based on a deterministic wind speed but should bring the wind speed uncertainty into account. Taking the Sidrap wind turbine plant in Sulawesi, Indonesia, as the case study, this work aims to predict the plant's average power and uncertainty. This calculation is done by implementing the Monte-Carlo simulation to calculate the production uncertainty. The data used for simulation is public data set between 2004 and 2015, obtained from the EMD International website. The simulation result is then compared to the actual production in 2018 and 2019 for analysis. The result indicates that the product is still in the range estimated using the Monte Carlo simulation. This method can also estimate other electrical power potential and uncertainty in an area before a wind turbine plant is built, given enough data sets containing wind speed variation for years. It is expected that by correctly understanding the uncertainty in electrical power production, the decision-making process to build the plant can be accurately determined. [ABSTRACT FROM AUTHOR]

An experiment to study 2β decay processes in 106Cd using a 106CdWO4 crystal scintillator of mass 215.4 g enriched in 106Cd to 66% is ongoing in the DAMA/R&D setup at the LNGS of INFN (Italy). The events in the 106CdWO4 detector are recorded in (anti)coincidences with two large-volume CdWO4 scintillation counters. The design of the detector system, the calibration and background measurements, methods and results of data analysis to determine key detector characteristics are described. The experimental data are compared with Monte Carlo simulation results, and a background model is constructed. The radioactive contamination of the setup components is studied. The limit on the half-life for the 2νεβ+ decay in 106Cd was preliminarily estimated as lim T1/2 = 3.5×1021, which approaches the theoretical expectations for this process. [ABSTRACT FROM AUTHOR]

Indonesia is the largest archipelago consisting of approximately 17,000 islands and is at the meeting point of three big tectonic plates: the Eurasian (Sunda), Australian, and Pacific Plates. The occurrences of earthquakes may be caused by collisions between the earth's plates; active faults; volcanic eruptions; and other causes such as landslides, avalanches, and the collapse of heavy rocks. Earthquakes in Indonesia may cause large financial losses due to damages on buildings and infrastructures. For example, according to the data from Badan Nasional Penanggulangan Bencana (BNPB), the 2009 earthquake in Padang resulted in financial losses of approximately IDR 28.5 trillion; and the 2018 earthquake and tsunami in Central Sulawesi resulted in financial losses of approximately IDR 23.1 trillion. An Earthquake Catastrophe (CAT) Model may be used to model the risk of financial losses due to tectonic earthquakes. The purpose of this study is to model the risk of financial losses due to damages on school buildings in a region in Indonesia caused by tectonic earthquakes. The study focuses on the formation of an Event Loss Table (ELT) by utilizing the hazard, inventory, and the vulnerability modules in an Earthquake CAT model. In building the ELT, collective risk models are used. Based on the obtained ELT, multi-scenarios of the risk of financial losses are generated using a Monte-Carlo simulation. The topic discussed in this paper is part of a series of studies in building a State Financial Risk Model based on a Disaster Risk Financing, funded by Lembaga Pengelola Dana Pendidikan (LPDP), Indonesia Ministry of Finance. [ABSTRACT FROM AUTHOR]

In recent years, the use of radioactive Co-60 in high-dose level brachytherapy (HDR-BT) has grown rapidly. This study aims to model the HDR-BT source, precisely the Bebig Co0.A86 type, and determine its spectrum characteristics. The simulation utilizes the GEANT4 Monte Carlo code to model radiation sources and irradiation systems. The BEBIG Co0.A86 brachytherapy source was modeled by encapsulation source. The beam characteristics of the source were simulated in a spherical scoring region. The scoring region had a radius of 50 cm with water medium, as recommended by the TG-43U1 protocol, and different scoring region sizes were considered: 10 cm, 20 cm, 30 cm, and 40 cm. The physical interactions used in the simulation were performed using the penelope model with 108 generated photons (history). The characteristic parameters of the photon spectrum in the scoring region were analyzed using the root program. The GEANT4 Monte Carlo simulation revealed two photoelectric energies of cobalt at 1.173 MeV and 1.332 MeV and the Compton edge in the energy distribution spectrum of the Bebig Co0.A86 model. The discrepancy between the Compton edge simulation results with theoretical calculations is about 3.22%. The source encapsulation with stainless steel material and the addition of cables to the source model did not affect the energy spectrum distribution pattern of Co-60. Furthermore, the results show that the photoelectric energy significantly decreased with increasing scoring region size, while the Compton continuum area increased accordingly. Additionally, the GEANT4 Monte Carlo method illustrated the differences in the spectrum distribution of HDR-BT Co-60 with variations in scoring region size. The scoring region size of 10 cm shows that the photoelectric effect has an amplitude almost equal to the Compton edge and Compton Continuum. [ABSTRACT FROM AUTHOR]

Concerning corporate management's rapid increase in debt issuance, alternative financing has been widely introduced in the financial market to minimize the use of debt instruments. According to that, debt-based financing was a huge contributor to the global economic collapse. Therefore, as a means of achieving financial sustainability, this paper unleashes the possibility of equity-based financing offered by a number of sectors as an alternative to debt. To achieve this objective, this paper examines the differences in credit risk exposure between debt-based and equity-based financing for a number of Malaysian sectors within the phase of GFC until COVID-19. Equity-based financing's ability to advance financial sustainability for companies and investors was investigated using the Monte Carlo simulation approach. Through a simulation using sectorial price index data, given that the return to investors is contingent upon the firm's performance, this paper demonstrates that equity-based financing can mitigate credit risk exposure for firms across different sectors. The results of zero default exposure recorded by all sectors during the crisis phase show that equity-based financing is significant in fostering financial sustainability for firms and investors. This suggests that firms should consider equity-based financing instead of depending solely on debt to raise capital. [ABSTRACT FROM AUTHOR]

In radiotherapy of cancer located on the surface of the skin, optimization of the radiation dose is important. The technology to increase the surface dose is to use a bolus that is placed between the radiation source and the cancer. In general, the bolus material used is synthetic. However, these synthetic materials have several weaknesses, among them the limited availability of raw materials in nature. Therefore, innovation in the use of bolus materials is needed. Natural Rubber (NR) and Silicon Rubber (SR) is one of the materials that have potential as an alternative material of bolus. In this study, the modelling of bolus with dimensions of 17x17x0.5 cm2 was carried out using the Monte Carlo N-Particle version X (MCNPX) code to calculate the Percentage of Surface Dose (PSD). The photon beam comes from a linear accelerator (Linac) produced by electron with an energy of 7 MeV. As for the variation parameters of bolus thickness 0.5 cm, 1 cm, 1.5 cm, and 2 cm, Source to Surface Distance (SSD) 100 cm, and irradiation area 10x10 cm2. The result of the calculation of Percentage of Surface Dose (PSD) based on Monte Carlo simulation show that Natural Rubber (NR) and Silicone Rubber (SR) boluses each has an optimum value of 98.94% and 99.94% at a bolus thickness of 2 cm. Based on the result of the simulation, it can be concluded that modeling Natural Rubber (NR) and Silicone Rubber (SR) as boluses for radiotherapy using Monte Carlo simulations has almost the same results as experiment. [ABSTRACT FROM AUTHOR]

This paper uses a stochastic finite element approach based on perturbation theory to explore the impact of uncertain material properties on the buckling characteristics of functionally graded porous (FGP) beams reinforced with graphene platelets (GPL). The first-order perturbation technique (FOPT) has been employed to accurately quantify diverse sources of uncertainties. A stochastic finite element formulation, ensuring C0 continuity, has been developed to calculate the stochastic buckling behaviour of FG-GPLRC porous beams. Convergence and validation analyses have been performed to validate the formulation's precision, comparing results with those obtained through a conventional Monte Carlo simulation. The Halpin-Tsai micromechanics model and Voigt's mixture rule have assessed the effective material properties at a homogenised level. Ultimately, the study delves into how material uncertainties influence the buckling responses of FG-GPLRC porous beams, particularly focusing on low variability (randomness) in key material design parameters like porosity content, nanofiller quantity, Young's modulus of the metal matrix, and nanofiller properties. The findings underscore that uncertainties in material properties significantly influence the buckling behaviours exhibited by FG-GPLRC porous beams. [ABSTRACT FROM AUTHOR]

Achieving construction project objectives require good project management. However, in its implementation, there are always unexpected risks that hinder the success of a project. Risks cannot be eliminated but can be reduced or transferred (1). If a risk occurs, it will have a direct impact on the disruption of the overall project performance so that it can cause losses to the cost, time, and quality of work. Nowadays, the world is being hit by Covid-19 pandemic, which has resulted in a death toll to nearly 6.5 million people (2). Due to the pandemic, construction projects slowed down to a halt and caused a retreat from a predetermined time. To reduce the impact of cost risks in construction projects due to the pandemic, a good risk control system is needed including risk identification, risk analysis, and risk response. This research developed an application to facilitate the implementation of the risk management process. The application called "SIRISPRO" was created using Visual Basic Application (VBA) or commonly known as Macro Excel. The input variables on the application are probability (P[E]) and impact (P[I]), as well as the output of the variable in the form of the value of a potential loss. The data processing of this application uses the Monte Carlo Simulation method. This application discusses the impact on quality (defect), cost (cost overruns), time (delay), and safety. The application was tested using a case study at the Santika Premiere Padang Hotel Project with interviews and application trials to contractor and owner representatives. Based on the interview analysis, it was found that there are several risks due to the Covid-19 pandemic that have the high impact on construction, such as the increase in material prices, the difficulty of bringing in workers with special skills from outside the island, poor /low labour productivity, delays in the delivery of goods, delays in schedules, and temporary work stoppages for projects in the red zone. Respondents felt that the application was very effective in conducting risk management process and user-friendly. [ABSTRACT FROM AUTHOR]

Stock is proof of ownership of a company where the buyer pays money to the company through the stock exchange. The company issues shares when the company decides to conduct corporate funding, which attracts investors to invest and make a profit. The company's business development greatly influences the stock price. If the company's management does not run well, it will affect stock price changes, so the stock price is stochastic. The Wiener process is one of the mathematical models that can be used to model stock prices. In addition to the wiener process, Monte Carlo simulations can also be used for random number generation in the calculation of changes in stock prices. The Monte Carlo simulation method assumes that the returns are normally distributed and requires repeated experiments through the generation of random numbers so that random values are obtained at a specific frequency probability. The study's results obtained the value of volatility or the magnitude of fluctuations in the stock price of PT. BRI starting from January 03, 2022, to January 27, 2023, of 2.267801175 and the comparison of historical stock prices with an average result of 30 simulations with Monte Carlo shows a good movement pattern by following the movement pattern of actual stock price data with a MAPE (Mean Absolute Percentage Error) value of 4.781%. [ABSTRACT FROM AUTHOR]

Gamma Knife PerfexionTM (GKP) is a stereotactic surgical device that uses Cobalt-60 sources. For radiation protection purposes, it is encapsulated from specific materials. When the source beam is emitted, the photons and absorber atoms' interaction produce two possibilities: (1) photons are absorbed with some energy transferred to charged particles and (2) scattered photons. These studies were very encouraging, as the effect associated with the use of absorber capsule and PB materials on the Cobalt-60 GKP source with the Monte Carlo simulation technique (MC) will be studied. The accelerator's geometry to be simulated is built up from a series of predefined component modules (CMs) on the BEAMnrc program. The CMs used is FLATFILT, owing to its ability to produce cylindrical sources, capsules, and areas around the source. A cylindrical Cobalt-60 source with a diameter of 1 mm and 17 mm is packaged in stainless steel capsules with a density (ρ) of 8.9×103 kg/m3. The absorber in this simulation is a PB material taken from the ICRU and a capsule material from the ELEKTA AB blueprint. The results show the capsule's effect and PB material absorbers on the source beam output on the total photons with a sequential increase influence at the Compton region was 62.49%, 58.54%. The secondary photons found increasing importance in the Compton region were 61.84% and 59.87%. This increase occurs due to scattered photons when concerning capsules and PB material. [ABSTRACT FROM AUTHOR]

Bridge design in Indonesia adhere to the regulations outlined in SNI 1725:2016, the Bridge Loading Standard. Under this standard, vehicle loads are currently represented as idealized forms of the actual loads they impose. Recent technological advancements have enabled the real-time measurement of vehicle loads as they traverse bridges, providing a more accurate representation of the actual loads experienced. Weigh-In Motion (WIM) technology, consisting of sensors installed on bridge elements, captures the responses of these elements to traffic loads. The primary objective of this research is to assess the characteristics of actual traffic loads, generate traffic load simulations using WIM data, and conduct a comparative analysis between the actual traffic loads derived from WIM data and the planned traffic loads specified by SNI 1725:2016. This study utilized WIM data collected from the Kaligawe Bridge in Semarang and simulated its application on a 60 m span simple steel frame bridge using the Monte Carlo method. The comparative analysis of the internal force values derived from WIM data against those planned according to SNI 1725:2016 revealed that the internal force ratios ranged from 86% to 97%. These findings indicate that the actual traffic loads measured through WIM technology on the Kaligawe Bridge result in lower internal forces compared to the standard loads specified in SNI 1725:2016. [ABSTRACT FROM AUTHOR]

Density functional theory (DFT), ab initio, and Monte Carlo simulations have been used to study the corrosion inhibition of copper by the monoterpenoids menthol, isopulegol, terpinen-4-ol, and α-terpineol. Quantum chemical parameters to provide information about the electronic properties of the tested molecule as a corrosion inhibitor. Monte Carlo simulations present target molecules' dynamics and inhibition mechanisms on copper surfaces. Quantum parameters and adsorption energy results show that α-terpeneol has the potential to have the highest corrosion inhibition efficiency. [ABSTRACT FROM AUTHOR]

This paper deals with obtaining the best estimator for the reliability function of a two-parameter exponential distribution using the Bayesian estimation method under four different loss functions: squared error loss function, precautionary loss function, and entropy loss function. The exponential distribution prior and Gamma distribution have been assumed as the priors for the scale γ and location δ parameters, respectively. In Bayesian estimation, maximum likelihood estimators have been used as the initial estimators for the two unknown parameters, and the Tierney-Kadane approximation has been effectively employed. The estimators were compared using the Monte-Carlo simulation method based on the integral mean squared error (IMSE). [ABSTRACT FROM AUTHOR]

EGS5 is a code system for photons, electrons, and positrons transport simulations. One of the main purposes of the EGS5 is for medical physics Monte Carlo simulations, due its highly accurate modelling physics for radiation. The EGS5 system is written in FORTRAN, and for running a simulation the user must prepare a FORTRAN user-code file, and two other input files, one for materials and the second for geometry. The EGS-SMS code was developed to simplify the users' preparations and running EGS5 simulations. The EGS-SMS code is a shell developed using PYTHON that implements plain text format command lines into the EGS5 code system to run the user's simulations. [ABSTRACT FROM AUTHOR]

Indonesia is the third-largest paddy producer in the world. From 2019 to 2021 total paddy harvested was more than 100 million tonnes. This huge quantity has an inherent by-product, i.e., rice straw, even in a more significant amount. Unfortunately, poor rice straw management causes farmers to treat the waste by open field burning. Monte Carlo simulations were performed to investigate the side effect of the open-burning treatment. This paper also discussed the worth of considering applications of using rice straw that could make rice straw more valuable. The uniform probability distribution was used to deal with the uncertainty of gas emissions generated from the open field burning of rice straw. In this scheme, at the highest estimate, more than 300 million tonnes of CO2 are released into the atmosphere each year when Indonesia does not apply well management of rice straws. Another 8 million tonnes of other emissions CO, (fine) particulate matter, N2O, NOx, CH4, NMHC, and SO2. Those pollutants more harmful to human health and well-being are also released. Transforming rice straw to particle board has great potential due to this application's high demand and value. It is also an environmentally friendly approach since it can potentially reduce deforestation. In conclusion, appropriate treatment of rice straw management will significantly contribute to the sustainable development of Indonesia. [ABSTRACT FROM AUTHOR]

Carbon ions have become an effective choice to destroy cancers, especially deep and radio-resistant ones, because of their unique biological and physical characteristics. However, the nuclear reactions that occur with the patient generate a variety of charged and neutral secondary particles responsible for the dose, especially beyond the Bragg peak, which requires a comprehensive characterization. In this study, we evaluated the secondary particles produced by a primary carbon ion beam of 290 MeV/u and their contribution to the total dose, especially after the distal edge of the Bragg peak. [ABSTRACT FROM AUTHOR]

The growing concerns about global warming and fuel price volatility have made Plug-in Electric vehicles (PEVs) a viable option. However, meeting the fluctuating demand for charging PEVs has a significant impact on the reliability of distribution systems. This study aims to explore the impact of uncontrolled and controlled charging of PEVs at parking lots (PLs) on system reliability. Monte Carlo simulation is used to model system interruptions, PEV arrivals, and their parking durations. A PEV is utilized to store energy that can be supplied to the distribution system during interruptions. The study employs the RBTS BUS-2 test system, incorporating four PLs of PEVs. Energy reliability indices, such as LOEE, LOLE, LOLF, and ENSPI, are evaluated to assess the significance of regulating the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) connections to enhance system reliability while ensuring the required state of charge at departure. [ABSTRACT FROM AUTHOR]

The objectives of this research are to find the explicit formulas of the average run length (ARL) of a moving average (MA) control chart for first-order integer-valued autoregressive conditional heteroscedasticity (INARCH1))) of Poisson count data. In addition, the numerical results obtained from the proposed explicit formulas are compared with those obtained from Monte Carlo simulations (MC) for Poisson INARCH(1) counting process. An out-of-control ARL (ARL1) is the criteria for measuring the performance of control charts. The numerical results found that the values of both ARL0 and ARL1 obtained from explicit formulas are in excellent agreement with the numerical results obtained from the Monte Carlo simulation (MC), but the latter is very time-consuming. [ABSTRACT FROM AUTHOR]

Ensuring the sustainability of conservation and rehabilitation while encouraging the economy of coastal communities, especially in Pemogan Village, the role of ecotourism in mangrove ecosystem management is one of the alternative developments to overcome destructive utilization problems. The management of the mangrove ecosystem in Tahura Ngurah Rai has been carried out based on community involvement. To accommodate problems in government-based and community-based management, a collaborative-based management is used that combines government elements with users. The purpose of the study is to determine the level of sustainability of mangrove management through ecotourism activities, and formulate a collaborative mangrove ecosystem management strategy for the development of coastal ecotourism. The research methods in this study are qualitative and quantitative. The data collection was carried out by direct interviews using questionnaires to determine indicators of each dimension of sustainable mangrove ecosystem management, namely ecological, economic, social and institutional dimensions. To determine the sustainability status of mangrove ecosystem management using multidimensional scaling analysis, Monte Carlo analysis, and Leverage analysis. Analytical Hierarchy Process to determine alternative mangrove management strategies collaboratively. The sustainability status of mangrove management in Pemogan Village is categorized as quite sustainable (58.05). The sustainability index of each dimension is very sustainable ecology (85.55), fairly sustainable economy (72.95), socially sustainable (59.24), and highly sustainable institutions (81.68). The mangrove management strategy is carried out through environmental pollution control, protection and improvement of mangrove ecosystems, socialization about the importance of mangrove ecosystems, and the development of community skills. Collaborative institutional management between the community and the government, private sector, NGOs, universities, and stakeholders. [ABSTRACT FROM AUTHOR]

A comparison of the gamma ray efficiency of various standard sources of environmental radioactivity was carried out for the two types of HPGe detectors. This study aims to compare the efficiency curves of standard gamma-emitting radionuclides from experiments in the field with Monte Carlo simulations in an easy and precise way for testing various types of environmental samples with different sample densities and geometries. Standard sources used include Epoxy, Sand, RGU-1, and RGK-1. Gamma ray efficiency measurements and calculations were carried out using the Monte Carlo simulation method, namely MCNP5 by reviewing two main parameters, including the influence of dead layer geometry and germanium crystals and matrix density. The results showed that the best agreement between experimental and simulation result for gamma ray efficiency value was achieved at low energy (< 90 keV) for Canberra HPGe detector, while for the Ortec HPGe detector was achieved at high energy. The gamma-emitting radionuclides from different types of environmental samples can be analyzed properly by following those criteria. [ABSTRACT FROM AUTHOR]

An electron accelerator receives heat mainly from radiofrequency resonance. This correlates to the increase in temperature for the inner components of the accelerating structure. An analysis of the thermal characteristics within an accelerating structure of a high-energy electron accelerator has been performed by utilizing Monte Carlo radiation transport code in dose deposition calculation. Two accelerating structures, one with 5 modules and one with 7 modules, have been considered for analysis. A multi-source approach has been done to accommodate the increase in energy for each acceleration module and to equate the sources power to the analytical power loss from resonance. Each source has a conical spread to cover as much area with the sources power in each cavity. The dose in each inner component of the accelerating structure is then applied to a calorimetric heat transfer calculation to determine the temperature difference. Through this analysis, it has been found that the average temperature increases of up to 10.2401 K and 12.3555 K in 5-module and 7-module structures respectively for each radiation hour can occur without a proper cooling system in place. A peak temperature increase at a single point along the accelerating structure has been calculated to reach 75.1975 K and 107.2558 K. Furthermore, the effect of photon creation from electron-matter interaction becomes more prominent in the latter modules of the accelerating structure and accounts for up to 0.5688 K and 0.9753 K average temperature increase. [ABSTRACT FROM AUTHOR]

The therapy uses beta-ray (β-) base radiopharmaceutical was the main option in developing countries but has obsolete in advanced countries like the United States of America and many Europe countries. The alpha (α) base radiopharmaceutical was a substitute radioisotope that was used for various therapies. To follow the novelty trend, the Indonesian research will build a cyclotron in Jogjakarta with the code name DECY-13 to produce new radioisotopes. The preliminary study should be carried out to prepare for when DECY-13 has finished commissioned that it should be producing radioisotopes optimally. The Actinium-225 was the common radioisotopes that used as a various therapy. 225Ac produced with irradiated Radium with proton in cyclotron. The production process can simulated using Monte Carlo method that include in PHITS v3.28 software. Simulation was conducted by irradiating proton 30 mg RaCl2 with 13 MeV proton for 48 hours with 24 hours cooling. The irradiation results obtained radioactivity of 225Ac was 5.18 Gbq (139.97 mCi) at EOB. The heat transmitted during the irradiation was 3.40×10−1 watt. The simulation predict was found 197 stable isotopes and 846 radioisotopes. The results of this research expected will be considered as a feasibility study for the 225Ac production process in Indonesia. [ABSTRACT FROM AUTHOR]

A new kinetic-continuum technique of the direct Monte Carlo simulation coupled with solution of the electron energy equation was applied to modeling of the high-enthalpyionized rare fied flow about are entry capsule. The new technique predict selectron temperature distributions completely different from those obtained with widely used approximation Te=Tv (N2). The technique was validated against the results of the RAM-CII flight experiment. More accurate prediction of electron temperature can improve validity of the studies of communucation black out phenomena and aerothermodynamics of super orbital entry. [ABSTRACT FROM AUTHOR]

In this study, thermal creep flow around a set of plates, periodically set in a pipe, was simulated using the direct simulation Monte Carlo method with a variable soft sphere molecular model for elastic molecular collisions and a statistical inelastic cross section model for rotationally inelastic molecular collisions. The surface temperature on one side of each plate was set higher than that on the other. The computational flow field was modeled using a drive source consisting of Peltier devices in the experimental pump system. The simulation results suggested that the pressure increases from low-temperature to high-temperature surfaces in a stepwise manner and that the simulation model acts as a pump by generating thermal creep flow around each plate. [ABSTRACT FROM AUTHOR]

We present our open-source code SMARTA. It can be used to compute internal and external collisionless gas flows when surface reflections are fully diffuse and gas sources are described by drifting Maxwell-Boltzmann distribution functions. The code is based on the view-factor method, analogous to the radiosity method commonly used in the fields of radiative heat transfer and computer graphics. In SMARTA, surfaces, including flow inlets and outlets, are represented using triangle meshes. In this work, we first show the derivation of the method. Then, we provide some details of the implementation and the algorithms used in the code to increase its efficiency and accuracy. Finally, we present some simple test cases that are used to verify the code and show its capabilities. These include a numerical experiment to analyze the convergence of the solution with the mesh size, as well as more practical applications to external and internal flows. Specifically, the computation of the aerodynamic pressure on a satellite in free molecular conditions, and the evaluation of the transmissivity of an intake for Air-Breathing Electric Propulsion. Strengths and weaknesses of the code, in relation to particle methods and panel methods, will be highlighted. We show that, in the cases where the underlying assumptions of the method are valid, SMARTA represents a simple to set-up alternative that can complement or even substitute the use of a Monte Carlo method. The main advantages are represented by the absence of stochastic noise in the results, and the possibility to reuse the view-factors for different computations. [ABSTRACT FROM AUTHOR]

The Boundary Element Method (BEM) is being applied to compute the single-scattering properties of randomly oriented complex rosette ice aggregates at the frequencies of 50, 183, 243 and 664 GHz, for the temperatures 190, 230, and 270 K. The rosette aggregates were generated using a Monte Carlo model, and from the statistical runs, 65 aggregates were selected that were within ±30% of an existing mass–dimension relation that is consistent with the Met Office's cirrus microphysics scheme in its weather and climate models. The generated 65 aggregates have maximum dimensions between 10 µm and approximately 1 cm. To compute efficiently their single-scattering properties using BEM, random orientation is approximated by rotating the incident wave about the scatterer rather than the other way around as is done in all other electromagnetic methods. This exploits the BEM linear matrix equation (i.e. Ax=b) by only needing to compute the matrix A once, leaving the less computationally demanding b to change. We show that our representation of random orientation can accurately compute the single-scattering properties of non-axisymmetric particles to within 1 or 2% of T-matrix solutions, and we compare the solutions found for our rosette aggregate models with other commonly used models in the microwave. [ABSTRACT FROM AUTHOR]

The Ministry of Agriculture in Indonesia has launched a crop insurance program in order to improve farmers' welfare, adopting the MPCI model. With the results being unsatisfactory, the area yield index (AYI) model was proposed as an alternative, with the hope of increasing the participation rate of the said program and preventing MPCI's underlying risk (moral hazard and adverse selection). Yet, the profitability aspect of these models in the short-term has yet to receive enough attentions and thus, it becomes the focus of this research. By conducting Monte Carlo simulation, it was found that both models were profitable but with several differences. The profitability of the AYI model contains more variability, indicating risk towards the insurance company, nevertheless, there are no occasion in which it led to negative profit. The MPCI model on the other hand tend to have stable profit in the short-term, yet it should be noted that MPCI's drawbacks has the potential to bring huge losses. In conclusion, the AYI model is appropriate to be implemented in Indonesia as not only it has a lower premium and deals with MPCI's weaknesses, it is also profitable and is thus, safe towards the insurance company. [ABSTRACT FROM AUTHOR]

To achieve food self-sufficiency, the government supports agricultural business, one of which is paddy farming. Since 2015 the government has made a Paddy Plant Business Insurance (PPBI) to give planting capital to farmers for the next season if their land is damaged. The PPBI's purpose is to help farmers, especially farmers with the low land area because PPBI only covers up to 2 hectares for each policy. Therefore, the researchers conduct surveys to farmers with a low land area. Besides PPBI, the government has microcredit for agriculture to help the agriculture business. However, right now, the farmers are still having a hard time getting the microcredits because the microcredits provider needs to manage the risk. Therefore, the microcredit program has high risks. Besides that, from the surveys, the farmers said that the benefit from PPBI is still not enough to help them if they take out a loan. Therefore, they said they want an insurance product that can provide claims for the next season's fund and claim credit assistance. Thus, an integration scheme between PPBI and microcredit was initiated, and the researchers used an alternative I-AYI (Individual Area Yield Index) model which enhances good farming practices and also resembles the current PPBI model. In carrying out this research, the data used is farmers' total productivity, by using Monte Carlo simulation with the lognormal distribution. The Monte Carlo simulation is chosen due to no indemnity data availability. The objective of the Monte Carlo simulation is to obtain the empirical data to calculate the appropriate pure premium (exclude expense, profit margin, etc). The credit limit for this research is 30% of each farmer's total revenue obtained from the last planting season. The premium calculation uses Yc values in the range of 4.4±1 sigma with 0.2 intervals. We chose 4.4 because it is the average of paddy productivity in Indonesia from 2005-2015 based on BPS. Hence, we split the calculation for PPBI and microcredits premium, also differentiate premium price over each Yc. The range of Yc on PPBI is within 3.6 up to 5.2 and the price is around IDR 55,357 up to IDR 992,820. Meanwhile, the price PPBI at Yc equal to 4.4 is IDR 387,029. On the other hand, the microcredit premium will be a certain rate within 1.45% up to 25.847% that is evaluated from the credit limit, so that the premium price for each farmer will be different from each other. The gross loss ratio for this scheme is different for each Yc, which is valued in the range of 46%. The gross loss ratio implies that the total paid claim that happens is 46% of the earned premium (in this case is the gross written premium). Based on the gross loss ratio which is lower than 1, it provides room for expense, profit margin, commission, etc for the insurance company. According to the results, this integration can be considered beneficial for the development of crop insurance in Indonesia. [ABSTRACT FROM AUTHOR]

Two-dimensional model of a spread of a virus epidemic is presented in the paper. In the model random numbers determine the infected individuals and the days of the secondary infections. The stress in the results is on the role of the size of the area for secondary infection around an infected individual. Also the effects of the distribution function, the boundary conditions and the initial conditions on the spread of the epidemic are studied by the model. [ABSTRACT FROM AUTHOR]

We discuss a Monte Carlo model for spread of a virus in a human population. In this model, random numbers determine the days of the secondary infections and the infected individuals. In contrast to the classical SIR and SEIR models our methodology permits the use of arbitrary distribution functions for the days of transmission of a virus after an infection and for the number of the secondary infections. The main point of the study is connected to the simultaneous spread of two variants of the virus with different basic reproduction numbers and different delay of the appearance of the second variant. In addition, we study the role of the incubation period and the possibility for infection with both variants. The obtained results are compared to results of other models (e.g. the SIR model). The proposed model is flexible and can be extended in order to account for additional possible characteristic of the spreading of infections in human and animal populations. [ABSTRACT FROM AUTHOR]

This manuscript covenant by means of the random natural rate of recurrence analysis of hybrid composite plate by employing the finite element (FE) based numerical approach. Shape memory alloy (Nitinol) in the form of rods will be inserted in glass epoxy composite plates to obtain the hybrid composites. An algorithm is resultant for vagueness quantification of accepted frequencies of the hybrid composite owing to uncertain disparity in the substance properties. This deterministic finite element code is verified with the preceding copy. The effects of degree of randomness and specific volume on the first three natural frequencies will be determined. Monte Carlo simulation will be coupled with finite element code to conduct the random analysis. The outcome demonstrates the key in parameters painstaking in the current learning have momentous possessions on the randomness of initial three accepted frequencies of plank hybrid composite plates. [ABSTRACT FROM AUTHOR]

The ridge regression model has been shown to be an effective shrinking strategy for reducing the impacts of multicollinearity on a number of occasions. When the response variable is positively skewed, the gamma regression model (GR) is a popular model to use. Multicollinearity, on the other hand, is known to reduce the variance of the maximum likelihood estimator of gamma regression coefficients. A novel estimator is proposed in this paper by presenting a generalization of the Liu-type estimator using gamma regression (NGLTE). The performance of NGLTE is fully depending on the shrinkage parameter, k. In this paper, three selection methods of the shrinkage parameter are explored and investigated. In addition, their predictive performances are considered. Our Monte Carlo simulation and real application results suggest that some estimators can bring significant improvement relative to others, in terms of mean squared error. [ABSTRACT FROM AUTHOR]

The estimate of the parameter and reliability Series Rs = p[v

Free-space optical (FSO) communications have been adopted as a response to the challenges that radio-frequency (RF) communication systems. In this study, a closed-form expression was derived for the average secrecy capacity (ASC) for the FSO communication system that employs the intensity modulation/direct detection (IM/DD) detection technique. Under the influence of the different atmospheric turbulence conditions, zero boresight pointing errors, non-zero boresight pointing errors, and foggy weather conditions. To model the channel gain for all atmospheric turbulence conditions (weak, moderate, strong), the generalized Malaga-M turbulence channels of the FSO links were utilized. The accuracy of all the results that have been presented of these secrecy performances analyse was verified, by Monte-Carlo simulation. [ABSTRACT FROM AUTHOR]

We investigate the implementation of a classical algorithm inspired by the quantum neural networks to solve a Bose-Hubbard-like system within the epistemically-restricted phase-space representation. The quantum states are expressed with the continuous variable model that intuitively represents the wavelike properties of a quantum system. We use the first quantization formalism to describe bosons in a double well potential. We utilize a fully-connected feedforward neural network that enacts several layers of Gaussian transformations and nonlinear activation functions to find the minimum energy of the system. A stochastic Monte Carlo method with Metropolis sampling generates a set of phase-space variables transformed iteratively by the neural network to reach the lowest possible energy. A gradient descent algorithm attempts to optimize the parameters of the Gaussian gates to reach the ground state energy of the system. [ABSTRACT FROM AUTHOR]

We investigate the phase-space representation of quantum mechanics as a platform to perform Monte Carlo simulation of the non-interacting Jaynes-Cummings-Rabi (JCR) model involving a two-level hydrogen atom as a qubit and a quantum har-monic oscillator as a photonic cavity. Our algorithm starts by defining a trial wave function for solving the JCR model and then implement it on the "epistemically-restricted" phase-space representation, known as Budiyono-Rochrlich theory, with a Monte-Carlo sampling for the phase-space distribution, which is useful to obtain the average energy of our JCR model. We find that the numerical results are close to the analytical ones for every separate system in the JCR model, i.e., the hydrogen and the oscillator, calculated independently. Combining the two components in the non-interacting JCR model, the calculated energy values for the ground and the first excited states are then found to be —0.91 a.u. and 0.41 a.u. with corresponding standard errors of 9.12×10−8 a.u. and 1.95×10−8 a.u., respectively. We expect that the method presented in this paper can be an alternative approach to solving various qubit-photon systems. [ABSTRACT FROM AUTHOR]

A new Monte Carlo algorithm for solving systems of Linear Algebraic (LA) equations is presented and studied. The algorithm is based on the "Walk on Equations" Monte Carlo method recently developed by Ivan Dimov, Sylvain Maire and Jean Michel Sellier [4]. The advantageous of the new algorithm versus the older one is demonstrated especially for diagonally dominant matrix with dimension up to 1000. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) is an effective approach for modeling large, complex data, including survival time-to-event data (SD), which are characterized by censoring. Survival curves are routinely generated and their adjustment for specific subgroups requires special care. Estimates of adjusted survival curves can be interpreted as the survival probabilities of groups with similar prognostic covariates. One popular method for analysis of SD is the Cox model, with Proportional Hazards (PH) or the more general stratified model. A standard approach for adjustment of survival curves using results from the Cox model is the means of covariates method, which is often the default in computer survival packages. Here we compared, on left-truncated and right-censored data, several SD-adapted methods (Cox adjusted corrected group prognosis method, Random Survival Forest, Survival Neural Network) with the Cox mean of covariates approach. In a graphic, survival estimates were calculated using a Monte Carlo simulation for pair-wise comparisons over given time periods. The model comparison was carried out on a mid-size real dataset not previously analyzed by these methods as well as on simulated survival datasets where the simulated ones mimicked the real datasets. [ABSTRACT FROM AUTHOR]

A validated Monte Carlo model of the kV imaging system of the TrueBeam STx Linac based on the egs_cbct code of EGSnrc has been used to determine the scatter contribution in cone-beam computed tomography (CBCT) images. Geometrical and anatomical digital phantoms were used in this MC framework to acquire a data set of CBCT images and its respective scatter components. This data set was used to train a deep learning algorithm, based on Convolutional Neural Networks. Specifically, we analyzed the performance of UNets and Generative Adversarial Networks. UNets demonstrate more efficient and precise results, even when trained with a few hundred images. Scatter corrections in CBCT images can be achieved with a trained deep learning-based model in 3 to 4 orders of magnitude faster than MC-based methods. [ABSTRACT FROM AUTHOR]

The model of ridge regression has ultimately been shown to be an effective shrinking strategy for reducing the impacts of multicollinearity on a number of occasions. As the variable of response positively skewed, the regression model of gamma (GR) is a popular model to use. Multicollinearity, on the other hand, is known to reduce the difference of the maximum possible estimator of coefficients of gamma regression. Truly, a regression model of gamma ridge model (GRR) has ultimately been presented as a solution to this problem. Moreover, a novel estimator is suggested in this paper by presenting a generalization of the Liu-type estimator using GR. Based on absolute bias as well as mean squared error, this Monte Carlo simulation findings along with real-world application demonstrate that the suggested estimator can provide real improvements over other competing estimators. [ABSTRACT FROM AUTHOR]

The Dynamic Positioning system allows a vessel to keep a precise position and heading during stationing operations in a rough sea by using onboard actuators only. During the design phase, it is mandatory to identify the capability of the system actuators to counteract the environmental forces. Conventional predictions are limited to the estimation of a maximum sustainable wind speed on predefined encounter angles by estimating the corresponding wave parameters with questionable standard deterministic correlations. The proposed approach aims at determining the dynamic positioning performances by using site-specific long-term environmental conditions which are modelled with joint distributions of wind and wave parameters. To this end, the operability of the dynamic positioning system is evaluated as a non-deterministic multidimensional Monte Carlo integration process, based on the sampling of environmental joint distributions. For each environmental condition, a quasi-static dynamic positioning analysis is performed solving the equilibrium between external forces and the vessel's actuators through a non-linear thrust allocation algorithm. The proposed methodology is applied to a reference offshore ship in five different operative geographic areas, highlighting the suitability of the calculation methodology for site-specific operability predictions. [ABSTRACT FROM AUTHOR]

In this research, the Monte Carlo simulation software MCNP6.2 version was used to create an extremely precise mathematical model of the 2.5 x 3.8 cm NaI(Tl) detector. The NaI(Tl) detector's energy resolution curve and photon detection efficiency were measured using a gamma energy range of 53 to 1408 keV with various radioactive sources. Experimental efficiency values and simulation results for MCNP were consistent. However, experimental and simulated data for low photon energy revealed a discrepancy in terms of efficiency. This would be indicated by the internal attenuation of low photon energies. This work demonstrated that the MCNP6.2 software can be effectively employed to compute the energy resolution and FWHM of a 2.5 x 3.8 cm cylindrical NaI(Tl) detector. Simulation models provide precise initial calculations for the design of each detector or scientific research equipment. The energy deposition and electron track curves indicate that the employed NaI(Tl) detector was adequately sized to detect almost all gamma energies emitted from the radioactive sources. [ABSTRACT FROM AUTHOR]

We consider a multispecies competition model in a one- and two-dimensional formulation. To solve the problem numerically, we construct a discrete system using finite volume approximation by space with semi-implicit time approximation. The solution of the multispecies competition model converges to the final equilibrium state that does not depend on the initial condition of the system. The final equilibrium state characterizes the survival status of the multispecies system (one or more species survive or no one survives). In real-world problems values of the parameters are unknown and vary in some range. For such problems, the series of Monte Carlo simulations can be used to estimate the system, where a large number of simulations are needed to be performed with random values of the parameters. A numerical solution is expensive, especially for high-dimensional problems, and requires a large amount of time to perform. In this work, to reduce the cost of simulations, we use a deep neural network to fast predict the survival status. Numerical results are presented for different neural network configurations. The comparison with convenient classifiers is presented. [ABSTRACT FROM AUTHOR]