The Implementation of Self Evaluation Teacher Talk (SETT) in Teaching English: A Case Study

This study analyzed the implementation of SETT (Self Evaluation Teacher Talk) (Walsh, 2011) by an English teacher in a senior high school in Surabaya. A descriptive analysis was conducted towards the talk used by teacher in delivering the material. As the law, the teacher regulated the students to speak the target language anyhow. On the other hand, the teacher applied a classroom interaction in English. There are four modes available based on the SETT criteria; managerial mode, material mode, skill and system mode, classroom context mode. The result shown that the teacher mostly applied two mode, namely managerial mode and skill and system mode, and was followed by classroom context mode, then material mode.

IoT Modes of Operations with Different Security Key Management Techniques: A Survey

The internet of things (IoT) has provided a promising opportunity to build powerful systems and applications. Security is the main concern in IoT applications due to the privacy of exchanged data using limited resources of IoT devices (sensors/actuators). In this paper, we present a classification of IoT modes of operation based on the distribution of IoT devices, connectivity to the internet, and the typical field of application. It has been found that the majority of IoT services can be classified into one of four IoT modes: gateway, device to device, collaborative, and centralized. The management of either public or symmetric keys is essential for providing security. In the present paper, we survey different key management protocols concerning IoT, which we further allocate in a map table. The map table is a link between modes of operation and the associated security key management elements. The main target of this mapping table is to help designers select the optimum security technique that provides the best balance between the required security level and IoT system mode constraints.

Research on Dynamic Balance of Spindle Rotor System Based on Particle Swarm Optimization

The dynamic balance is a significant issue for the nonlinear dynamic characteristics of the spindle rotor system. However, there is a problem that the dynamic balance is lacking detailed study on optimization method. In the paper, a modal dynamic balance optimization model of spindle rotor system is proposed, which can intend to improve the accuracy of spindle rotor system modal dynamic balance. Because the multiorder unbalance components are the main spindle rotor system mode shapes, the particle swarm optimization (PSO) method is adopted. The sum of squares of residual vibration after balancing is taken as the optimization objective, and the correction is presented as the optimization variable in the optimization model. The optimal correction weight of every unbalance component is calculated through a modal matrix equation of PSO. The vibration amplitude that is greatly reduced after optimization balance is presented under different conditions. The balancing effect shows a better dynamic characteristic than that of traditional methods. And the fluctuation range of the axis track of the rotor system also shows reductive phenomenon. The proposed optimization spindle rotor system model is well verified through experiments. It can contribute a theoretical optimization foundation for available dynamic balance in spindle rotor system.

Predictive management of enterprise power consumption based on the SINGULAR SPECTRUM ANALYSIS method using recurrent forecasting

Modern energy strategies aimed at the development of energy industry presuppose a significant change in the structure of process of formation, transmission, consumption of electrical energy and increasing energy efficiency by introducing modern technologies at all stages. The growth of capacities of industrial enterprises in the conditions of wholesale market of electrical energy and capacity in the modern energy system determines the need for development technologies of predictive control of power consumption process of these enterprises. The introduction of such technologies at the control rooms of the operational management of enterprises will allow to reduce the number of human errors, the number of emergency stops of technological process, increase the reliability of power system mode, rationally manage the process of power consumption of enterprises. In this regard, forecasting the load demand and consumption is an important stage in the functioning and planning of modern power systems. An accurate, correctly compiled forecast is the key to effective management of energy consumption process and reliable operation of the enterprise. Forecasting errors lead to imbalanced supply-demand, which negatively affects operating costs, reliability and efficiency.

The Practice Teaching Model of “Workplace” in Environmental Art Design Education

Objectives: With the rapid development of our country, the pace of reform has never ceased, and the work of all walks of life is clear and clear. Methods: The market has gradually improved the professional level of technical requirements, and it is a preferred choice for real technicians. In recent years, the state has paid more and more attention to the environmental art design industry, and the environmental art design education industry has also developed. Results: This paper put forward the practice teaching mode of “workplace”, which is based on the data mining algorithm and considers from many aspects. First, we need to consider the market’s demand for this industry, Conclusion: then train talents in this area according to supply and demand, innovate and reform the curriculum system mode, make art education more innovative and more characteristic, and cultivate talents that the society needs.

Pretreatment and Bioprocess Trials in Various Reactor System on Lignocellulosic Biomass for Cellulosic Biomaterials

Pretreatment on lignocellulosic biomass prior to extraction of biomaterials, degradation of bioproduct, or production of biomaterial/bioproduct/biofuel, crucially influences the intended outcomes. The pretreatment of oil palm fronds (OPF), one of the most abundant agriculture residues in Malaysia, can be conducted based on the need of the methodology, either for small, lab, pilot, or industrial scales. In this article, examples of reactors for the pretreatment for instance microreactor (Bioshake iQ), conical shake flask, and mini-cylindrical reactor scale (fabricated) as well as the monitoring bioreactor (BlueSens Monitoring GmbH) reactor system dedicated for fermentation process using the outcome material from pretreatment process, are presented. All pretreatment trials with ionic liquid (IL) of 1-ethyl-3-methylimidazolium acetate [EMIM]Ac on OPF were conducted with a scaling-up strategy from micro-to-macro to fabricated reactors, monitoring Crystallinity Index (CrI) and Lateral Order Index (LOI). Electron beam irradiation pretreatment using 1000kGy was also tested in macroscale mode for CrI and LOI. Effectiveness of approximately 23 to 37% of CrI via microreactor experiments using 50, 70, and 90% v/v of [EMIM]Ac and at a temperature of 99oC was observed. Higher concentration of IL and temperature with nearly insignificance of solid loading of OPF in reaction liquid to the increase of the amorphous level of OPF was reported by macroscale mode in the 570-mL fabricated reactor. A short oxygen uptake rate (OUR) phase was observed in a 500-mL BlueSens shake flask with the real-time monitoring systems for 45-mL working volume, a nearly 10% of the total reactor volume for saccharification-fermentation using Escherichia coli K011 ATCC 55124 on approximately 2.22% w/v pretreated OPF from macroscale mode. Various data examples from these micro-to-macro scales including in a fabricated reactor system mode are crucially needed for further observations prior to pilot or industrial scales, needing a systematic data collection to be simulated and investigated in the future.

Fuzzy-Model-Based Robust Control of Markov Jump Nonlinear Systems With Incomplete Transition Probabilities and Uncertain Packet Dropouts

Interval type-2 fuzzy Markov jump systems (IT2FMJSs) have received much attention because they can better describe complex nonlinear systems with uncertainties and stochastic system mode switching. Over the past decade, many excellent results of fuzzy MJSs (FMJSs) have been reported. However, the transition probabilities which govern the dynamic behaviour of MJSs have been assumed to be completely known, limiting real-world applications of existing results. Different from the previous studies, transition probabilities between system modes switching are partly unknown, and packet dropouts of data transmission are uncertain in this study. The main contributions of this work are: (1) To analyze stochastic stability and reduce conservatism, a novel Lyapunov function which both depends on system mode and fuzzy basis function is constructed; (2) The existence of a mode-dependent and fuzzy-basis-dependent state-feedback controller is investigated; (3) The closedloop system is stochastically stable with a desired H∞ performance, thereby addressing the problem of incomplete transition probabilities and uncertain packet dropouts. An illustrative example of a robot arm is used to demonstrate the effectiveness and practicality of the proposed approach. By virtue of the proposed approach, the effects of incomplete transition probabilities and uncertain packet dropouts on IT2FMJSs are alleviated.

Temperature field of a thermoelectric system for extracting foreign objects when introducing into the human body

Objective. The objective of the article is to create a design model of a thermoelectric system for extracting foreign objects from the human body by freezing when introduced into the cavity, as well as to study the internal thermophysical processes.Methods. A design model of a thermoelectric system for extracting foreign objects from the human body by freezing the thermoelectric system introduced into the cavity is developed, based on solving the problem of thermal conductivity, taking into account the thermophysical characteristics of a biological object, foreign object, and a thermoelectric module.Results. As a result of the numerical experiment, the authors obtained graphs of temperature changes at various points of the thermoelectric system when introduced into the human body to extract a foreign object, depending on the power of the thermoelectric system, the parameters of the module materials, and external conditions. It is determined that the device can use a standard thermoelectric module with a cooling capacity from 4500 W/m2 to 7000 W/m2 with a duration of 6-7 minutes for entering the system mode.Conclusion. It is established that the selection of thermoelectric module parameters must be guided by the limitations of the device operation, as well as medical norms and standards to avoid the process of cold injury of adjacent tissues, which is fully provided in the proposed design. A method for improving the efficiency of the system is proposed, according to which the thermoelectric system is pre-cooled using an external cold source, and forced modes of thermoelectric module operation are used.

Taking into account the constraints in power system mode optimization by genetic algorithms

Over the past decades, many publications on the use of genetic algorithms, which offer a new and powerful approach for solving the problem of power system mode optimization, have appeared. Despite this, the issues of effectively taking into account various constraints when solving such problems with genetic algorithms remain opened. In this regard, this article proposes an algorithm for optimizing power system modes by genetic algorithm, taking into account functional constraints in the form of equalities and inequalities by various penalty functions. The results of effectiveness research of the given algorithm in the example of optimization of 8-nodal power system with four thermal power plants and three lines with controlled power flows are presented.