Adaptive Management of Volatile Edge Systems at Runtime With Satisfiability

Edge computing offers the possibility of deploying applications at the edge of the network. To take advantage of available devices’ distributed resources, applications often are structured as microservices, often having stringent requirements of low latency and high availability. However, a decentralized edge system that the application may be intended for is characterized by high volatility, due to devices making up the system being unreliable or leaving the network unexpectedly. This makes application deployment and assurance that it will continue to operate under volatility challenging. We propose an adaptive framework capable of deploying and efficiently maintaining a microservice-based application at runtime, by tackling two intertwined problems: (i) finding a microservice placement across device hosts and (ii) deriving invocation paths that serve it. Our objective is to maintain correct functionality by satisfying given requirements in terms of end-to-end latency and availability, in a volatile edge environment. We evaluate our solution quantitatively by considering performance and failure recovery.

COPULA FRANK UNTUK PERHITUNGAN VALUE AT RISK PORTOFOLIO BIVARIAT PADA MODEL EXPONENTIAL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY

Stocks are one type of investment that promises return for investors but often carries a high risk. Value at Risk (VaR) is a measuring tool that can calculate the amount of the worst loss that occurs in a stock portfolio with a certain level of confidence and within a certain time period. In general, financial data have a high volatility value, which causes the residuals are not normally distributed. ARCH/GARCH modoel is used to solve the heteroscedasticity problem. If the data also have an asymmetric effect, it is modelled with Exponential GARCH model. Copula-Frank is part of the Archimedian copula which is used to solve empirical cases. The data on this study were BBCA and KLBF stock price return data in the observation period 30 December 2011 – 6 December 2019. Furthermore, to test the validity of the VaR model, a backtesting test will be carried out using the Kupiec Test. The results showed that the best model used for BBCA stocks was ARIMA (1,0,1) EGARCH (1,1) and for KLBF stocks was ARIMA (1,0,1) EGARCH (1,2). The amount of risk with a 95% confidence level used a combination of the EGARCH and Copula-Frank models was 2.233% of today's investment. Based on the backtesting test used the Kupiec Test, the VaR model of the portfolio obtained was declared valid.

PEMODELAN DAN PERAMALAN INDEKS HARGA SAHAM GABUNGAN (IHSG) MENGGUNAKAN ARIMAX-TARCH

The Composite Stock Price Index (IHSG) is a value that describes the combined performance of all shares listed on the Indonesia Stock Exchange. JCI serves as a benchmark for investors in investing. The method used to predict future conditions based on past data is forecasting . Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) is amodel time series that can be used for forecasting. Financial data has high volatility which causes the variance of the residual model which is not constant (heteroscedasticity). ARCH / GARCH model is used to solve the heteroscedasticity problem in the model. If the data is heteroscedastic and asymmetric, then the model can be used Threshold Autoregressive Conditional Heteroskedasticity (TARCH). The data used are the Composite Stock Price Index (IHSG) for the January 2000 - April 2020 period and the dollar exchange rate data for the January 2000 - April 2020 period asvariables independent from the ARIMAX model. The best model used to predict the JCI from the results of this study is the ARIMAX (1,1,0) -TARCH (1,2) model with an AIC value of -0.819074.

Biocontrol Potential of Essential Oils in Organic Horticulture Systems: From Farm to Fork

In recent decades, increasing attention has been paid to food safety and organic horticulture. Thus, people are looking for natural products to manage plant diseases, pests, and weeds. Essential oils (EOs) or EO-based products are potentially promising candidates for biocontrol agents due to their safe, bioactive, biodegradable, ecologically, and economically viable properties. Born of necessity or commercial interest to satisfy market demand for natural products, this emerging technology is highly anticipated, but its application has been limited without the benefit of a thorough analysis of the scientific evidence on efficacy, scope, and mechanism of action. This review covers the uses of EOs as broad-spectrum biocontrol agents in both preharvest and postharvest systems. The known functions of EOs in suppressing fungi, bacteria, viruses, pests, and weeds are briefly summarized. Related results and possible modes of action from recent research are listed. The weaknesses of applying EOs are also discussed, such as high volatility and low stability, low water solubility, strong influence on organoleptic properties, and phytotoxic effects. Therefore, EO formulations and methods of incorporation to enhance the strengths and compensate for the shortages are outlined. This review also concludes with research directions needed to better understand and fully evaluate EOs and provides an outlook on the prospects for future applications of EOs in organic horticulture production.

A universal co-solvent dilution strategy enables facile and cost-effective fabrication of perovskite photovoltaics

Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.

Modelling and condition-based control of a flexible and hybrid disassembly system with manual and autonomous workstations using reinforcement learning

Remanufacturing includes disassembly and reassembly of used products to save natural resources and reduce emissions. While assembly is widely understood in the field of operations management, disassembly is a rather new problem in production planning and control. The latter faces the challenge of high uncertainty of type, quantity and quality conditions of returned products, leading to high volatility in remanufacturing production systems. Traditionally, disassembly is a manual labor-intensive production step that, thanks to advances in robotics and artificial intelligence, starts to be automated with autonomous workstations. Due to the diverging material flow, the application of production systems with loosely linked stations is particularly suitable and, owing to the risk of condition induced operational failures, the rise of hybrid disassembly systems that combine manual and autonomous workstations can be expected. In contrast to traditional workstations, autonomous workstations can expand their capabilities but suffer from unknown failure rates. For such adverse conditions a condition-based control for hybrid disassembly systems, based on reinforcement learning, alongside a comprehensive modeling approach is presented in this work. The method is applied to a real-world production system. By comparison with a heuristic control approach, the potential of the RL approach can be proven simulatively using two different test cases.

Analysis of Herding Behavior in Developing Countries

When faced with market uncertainty and high volatility in financial markets, the potential for herding behavior in the stock market is likely to increase. This will cause instability in the financial market and also the economy of a country. The purpose of this study is to analyze herding behavior in the stock markets of developing countries including China, the Philippines, India, Indonesia, Korea, Malaysia, Pakistan, Taiwan and Thailand. This type of research is quantitative research and the population in this study is stocks listed on the Stock Exchanges of all developing countries with a time period from January 2016 to December 2020. The sampling method used is purposive sampling. The data used are monthly stock index data, VIX, world oil prices and the fed funds rate. Data analysis was performed through panel data regression, which is a combination of cross section and time series using the Eviews program. The results showed that there was no herding behavior in developing countries. The result of this research is that the fed fund rate has a significant effect on herding behavior in developing countries, especially in Indonesia. Keywords: Herding, Market Volatility, Oil Price, Fed Fund Rate.

Legalitas dan Pandangan Majelis Ulama Indonesia terhadap Bitcoin sebagai Alat Transaksi

ABSTRAK Bitcoin adalah sistem pembayaran online dari uang elektronik peer-to-peer (P2P) yang dikirim langsung dari satu pihak ke pihak lain tanpa melalui lembaga keuangan. Di Indonesia Bitcoin tidak memiliki legalitas untuk dijadikan sebagai alat transaksi yang sah karena bertentangan dengan Undang-Undang nomor 7 tahun 2011 dan Peraturan Bank Indonesia nomor 17 tahun 2015 serta kepemilikan Bitcoin hanya dianggap sah apabila Bitcoin dijadikan sebagai asset kripto dalam bursa berjangka komoditi. Konsep Bitcoin menurut ulama Indonesia haram karena mengandung gharar dan dharar serta bertentangan dengan Undang-Undang. Gharar disebabkan karena penemu atau penciptanya tidak diketahui secara pasti, tidak adanya otoritas yang memastikan keabsahan transaksi, tidak memiliki nilai intrinsik, tidak memiliki validitas dalam sistem ekonomi, nilainya yang tidak stabil karena volatilitas yang tinggi, sulit untuk diawasi akibat ketidakjelasan pemiliki. Dharar disebabkan karena factor kemanan yang rentan akan peretasan, nilai yang fluktuatif sehingga harga bisa turun drastis dan merugikan pemilik, tidak adanya regulasi yang memberikan jaminan terlindung dari kerugian. ABSTRACT Bitcoin is an online payment system of peer-to-peer (P2P) electronic money sent directly from one party to another without going through a financial institution. Bitcoin does not have the legality to be used as a legal transaction tool because it is contrary to Undang-Undang nomor 7 of 2011 and Bank Indonesia Regulation number 17 of 2015 and Bitcoin ownership is only considered legal if Bitcoin is used as a crypto asset in the commodity futures exchange. The concept of Bitcoin according to Indonesian scholars is haram because it contains gharar and dharar and is against the law. Gharar is caused by the inventor or creator is not known with certainty, there is no authority to ensure the validity of transactions, has no intrinsic value, has no validity in the economic system, the value is unstable due to high volatility, difficult to announce due to the uncertainty of the owner. Dharar is caused by security factors that are vulnerable to hacking, fluctuating values ​​so that prices can drop drastically and harm the owner, there is no regulation that guarantees protection from losses.

PRICE THE MAIN CONDITION FOR COFFEE EXPORTS AN ANALYSIS WITH GOOD NEWS AND BAD NEWS APPROACHES IN INDONESIA

This study aims to analyze the effect of prices and income of the United States of America on 5 superior commodities in Indonesia and see between good news and bad news. The research data uses quarterly data from 2005Q1-2017Q4. The research model uses the TGARCH model. The results show that the income per capita of the United States, the previous price per commodity and previous exports have a positive and significant influence on commodity exports. However, the effect of per capita income on superior rubber commodities was found to have a negative and significant effect. This indicates an increase in foreign income will reduce rubber exports. Extreme volatility shocks occur in palm oil and other agriculture. High volatility is only cocoa commodity. Meanwhile, for coffee and rubber, the volatility is low. 3 commodities that have symmetrical information are coffee, cocoa, and other agriculture. Asymmetric information on palm oil and rubber commodities.