Multi-Criteria Evaluation of Site Selection for Smart Community Demonstration Projects

Some researchers in Taiwan argue that the current mechanism by which government subsidies are allocated for smart city demonstration projects warrants improvement. A comprehensive literature review determined that the development potential of smart cities should be prioritized in site selection for such demonstration projects. This study developed an evaluation framework on the basis of multi-criteria evaluation methods to enable the identification of suitable smart community demonstration sites. Evaluation criteria were first identified through the Delphi method. Next, the weights of each criterion were derived through the analytic hierarchy process. Furthermore, the capability of the proposed evaluation model was determined through simulation testing.

Experimental Study of Strain Rockburst considering Temperature Effect: Status-of-the-Art and Prospect

In deep mining and excavation of tunnels with high geothermal, the surrounding rock is not only subjected to high ground stress but also subjected to high temperature. Temperature will change mechanical characteristics and energy storage capacity of rocks, as well as increase the destructiveness and randomness of rockburst. To reveal the mechanism of high-temperature strain burst in deep rock, the rockburst tests from uniaxial compression to three-dimensional compression were reviewed, and the research results of the minimum principal stress rapid unloading, true-triaxial loading with one free face, and dynamic disturbance triggered pre-heated granite rockburst simulation tests were focused on. According to the occurrence state of country rock for deep high-temperature and stress state in the whole process during excavation, six development directions for high-temperature strain rockburst simulation tests were proposed: (1) constructing the damage constitutive models of high-temperature rocks according to linear energy dissipation law; (2) developing the true triaxial rockburst simulation testing system accomplishing the function of “real-time high temperature + unloading + dynamic disturbance”; (3) considering the true triaxial rockburst simulation test after microwave irradiation; (4) developing the real-time high-temperature rockburst simulation testing device for large-size specimens and internal unloading; (5) focusing on the energy actuating mechanism for deep high-temperature rock failure via rockburst simulation tests; and (6) implementing the three-dimensional rockburst simulation test on the basis of deep in situ coring.

Scaling data PLC sebagai pengontrol motor stepper penggerak ulir extruder

Scaling data PLC untuk penggerak motor stepper pada sistem extruder memengaruhi bentuk produk yang dihasilkan saat proses ekstrusi melalui kecepatan putar dan torsi motor. Produk hasil cetakan akan gagal jika kecepatan putar motor stepper terlalu cepat atau lambat karena pengaruh torsi motor yang bekerja. Dibutuhkan pembatasan kecepatan putar motor stepper menjadi beraturan untuk menghindari kegagalan proses ekstrusi. Tujuan penelitian ini adalah mendesain scaling setpoint dan kecepatan putar motor (rpm) beserta torsi motor (Nm) untuk kontrol torsi motor melalui kecepatan putar motor stepper. Metode yang digunakan adalah eksperimen kuantitatif data scaling dengan menggunakan persamaan matematis scaling setpoint, kecepatan putar motor (rpm) dan torsi motor (Nm). Data hasil didapatkan melalui pengujian simulasi persamaan matematis scaling pada PLC dengan sampel input periode pulsa setpoint antara 100us sampai 1000us. Hasil pengujian dengan daya motor 24Watt menunjukkan kecepatan putar motor stepper antara 49,3rpm sampai 9,4rpm berbanding terbalik dengan torsi motor stepper antara 0,49Nm sampai 2,55Nm. Pada setpoint 800us didapatkan hasil scaling setpoint 820us nilai error sebesar 2,5%, cukup ideal diaplikasikan dengan kecepatan putar 11,4rpm serta torsi 2,1Nm untuk menjalankan extruder dimensi kecil. PLC data scaling for stepper motor drive in extruder system affects the shape of product produced during extrusion process through motor rotational speed and torque. Printed product will fail if rotational speed of stepper motor is too fast or slow due the working torque influence of the motor. It is necessary to limit rotational speed of stepper motor to be regular to avoid failure of extrusion process. The purpose of this research is design scaling setpoint and motor rotational speed (rpm) along with motor torque (Nm) to control motor torque through stepper motor rotational speed. Method used is quantitative experimental data scaling using mathematical equations of scaling setpoint, motor rotational speed (rpm) and motor torque (Nm). Result data is obtained by simulation testing the scaling mathematical equation on PLC with input samples of the setpoint pulse period between 100us to 1000us. Test results with 24Watt motor power show that stepper motor rotational speed is between 49.3rpm to 9.4rpm and inversely proportional to stepper motor torque between 0.49Nm until 2.55Nm. At 800us setpoint, the 820us setpoint scaling results in error value of 2.5%, which is ideal for application with rotational speed of 11.4rpm and torque of 2.1Nm to run small-dimensional extruder.

Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework

The research paper is devoted to developing a mathematical approach for dealing with time-varying parameters in rolling window logit models for credit risk assessment. Forecasting coefficients yields a better model accuracy than a trivial approach of using computed past statistics parameters for the next time period. In this paper, a new method of dealing with time-varying parameters of scoring models is proposed, which is aimed at computing the default probability of a borrower. It was empirically shown that in a continuously changing economic environment factors’ influence on a target variable is also changing. Therefore, forecasting coefficients yields a better financial result than simply applying parameters obtained by accumulated statistics over past time periods. The paper develops a new theoretical approach, incorporating a combination of the ARIMA class model, the DCC-GARCH model and the state–space model, which is more accurate, than using only the ARIMA model. Rigorous simulation testing is provided to confirm the efficiency of the proposed method.

Chaos is not rare in natural ecosystems

Chaotic dynamics are thought to be rare in natural populations, but this may be due to methodological and data limitations, rather than the inherent stability of ecosystems. Following extensive simulation testing, we applied multiple chaos detection methods to a global database of 175 population time series and found evidence for chaos in >30%. In contrast, fitting traditional one-dimensional models identified <10% as chaotic. Chaos was most prevalent among plankton and insects and least among birds and mammals. Lyapunov exponents declined with generation time and scaled as the -1/6 power of mass among chaotic populations. These results demonstrate that chaos is not rare in natural populations, indicating that there may be intrinsic limits to ecological forecasting and cautioning against the use of steady-state approaches to conservation and management.

Research on Semi-Physical Simulation Testing of Inter-Satellite Laser Interference in the China Taiji Space Gravitational Wave Detection Program

To guarantee a smooth in-orbit space gravitational wave detection for the Taiji mission, a semi-physical simulation test of inter-satellite laser interference is carried out. The semi-physical simulation test consists of three aspects: the establishment of the inter-satellite laser link, interferometry of the inter-satellite ranging, and simulation of the space environment. With the designed specifications for the semi-physical simulation platform, the test results for the inter-satellite laser interference can be obtained. Based on the semi-physical simulation test, the risks of inter-satellite laser interference technology can be mitigated, laying a solid foundation for the successful detection of in-orbit gravitational waves.

Catch and Length Models in the Stock Synthesis Framework: Expanded Application to Data-Moderate Stocks

Many fisheries in the world are data-moderate, with data types (e.g., total removals, abundance indices, and biological composition data) of varied quality (e.g., limited time series or representative samples) or available data. Integrated stock assessments are useful tools for data-moderate fisheries as they can include all available information, can be updated due to the availability of more information over time, and can directly test the inclusion and exclusion of specific data types. This study uses the simulation testing and systematic data reduction from the US West Coast benchmark assessments to examine the performance of Stock Synthesis with catch and length (SS-CL) compositions only. The simulation testing of various life histories, recruitment variabilities, and data availability scenarios found that the correctly specified SS-CL can estimate unbiased key population quantities such as stock status with as little as 1 year of length data although 5 years or more may be more reliable. The error in key population quantities is decreased with an increase in years and the sample size of length data. The removal of the length compositions from benchmark assessments often caused large model deviations in the outputs compared to the removal of other data sources, indicating the importance of length data in integrated models. Models with catch and length data, excluding abundance indices and age composition, generally provided informative estimates of the stock status relative to the reference model, with most data scenarios falling within the CIs of the reference model. The results of simulation analysis and systematic data reduction indicated that SS-CL is potentially viable for data-moderate assessments in the USA, thus reducing precautionary buffers on catch limits for many stocks previously assessed in a lower tier using catch-only models. SS-CL could also be applied to many stocks around the world, maximizing the use of data available via the well tested, multifeature benefits of SS.