Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal damping concept: features and applications

This work presents new ideas related to the synthesis of nonlinear stabilizing control laws in the framework of optimization approach. The focus is done on the optimal damping concept, proposed by V.I. Zubov in the early 60s of the last century. This theory is used to reduce significant computational costs in solving optimal stabilization problems. The essential features of the aforementioned concept are taken into account, allowing the construction of new methods for practical synthesis of control systems with desired dynamic properties. Various modern aspects of the optimal damping theory’s practical implementation are discussed. Special attention is paid to the specific choice of the functional to be damped to provide the desirable stability and performance features of the closed-loop connection.
Structural, surface morphology and optical properties of annealing treated Copper Phthalocyanine doped Fullerene (CuPc: C60) thin films

The doping process with materials related to carbon has become a newly emerged approach for achieving an improvement in different physical properties for the obtained doped films. Thin films of CuPc: C60 with doping ratio of (100:1) were spin-coated onto pre-cleaned glass substrates at room temperature. The prepared films were annealed at different temperatures of (373, 423 and 473) K. The structural studies, using a specific diffractometry of annealed and as deposited samples showed a polymorphism structure and dominated by CuPc with preferential orientation of the plane (100) of (2θ = 7) except at temperature of 423K which indicated a small peak around (2θ = 31) for C60. AFM remarks showed the existence of a compact packing film with a smooth surface. The FTIR spectra emphasized the bonding between CuPc and C60. UV-Vis Absorption spectroscopy confirmed that the CuPc was dominating the optical properties with a small shift in Q band towards higher wavelengths.
Redesign Integrated Control System GTG and HRSG to Reduce Loss of Electrical Production at Combined Cycle Power Plant Muara Karang

Combined Cycle Power Plant (CCPP) Block 1 Muara Karang control system had performance degradation since 2016-2017. Performance degradation comes from the complexity of the design architectures that are serially configured which can cause loss of electrical production. The Re-Design Method is able to simplify the architecture design by replacing hardware devices into modbus-based TCP-IP software that is compatible with the communication technology between GTG and HRSG and has a redundant path that can increase reliability. Based on the Muara Karang PLTGU Block 1 disturbance report data, redesign is able to increase reliability and better financial aspect. It shows that before the redesign there were 9 disruptions, while after the redesign there were no failures and Total saving opportunity loss of electrical production is Rp 10,792,782,094.30. This value is obtained from the unit repair time from operation failure and electricity sales price. On the corporate side, Re-Design can be applied to other generating units that have differences in technology based on open protocol.
Rooftop Solar Installations for Demand Side Management - A Case Study

Renewable energy options, especially solar energy show a strong potential to replace conventional fossil fuel based electricity generation. Demand Side Management is a method of influencing the electricity consumers’ demand for electricity and thus reducing the load on distribution and generation companies. With the help of Demand Side Management tools, consumers are able to modify their demand in such a way that installation of new power plants could be avoided. This paper studies the load pattern in the industrial sector of Jalgaon, Maharashtra and their potential for rooftop solar installations. The impact of rooftop solar on the consumption schedule is studied considering the ‘Time of Day’ (TOD) tariff in place. Further, the importance of storage system is studied by comparing the daily savings for cases with and without storage availability. For the case when battery storage is available, a linear programming based optimization model is used to estimate the maximum possible savings from the installation. To run the optimization, simulation software used is MATLAB.
Loss of Fertilizer N from Plants-soil System and the Strategies and Techniques for Its Reduction

The present paper summarizes the studies conducted in China relevant to the improvement in the efficiency of fertilizer N by reducing N losses from crop plant-soil systems. It includes those topics such as the extent, pathways and mechanisms of fertilizer N losses from soil-plant systems, the agronomic efficiency of fertilizer N and the environmental impact of N loss, and the principles and techniques for reducing N loss and improving N efficiency. The efficacy of optimization of the rate and timing of N application, deep placement, irrigation-fertilization, urease inhibitors, nitrification inhibitors, and surface film for reducing ammonia loss from flooded rice fields are thoroughly discussed.
A multi-objective optimization model for reservoir operation during droughts

General guidance for reservoir operation can be referred to as the Standard Operation Procedure (SOP). Real circumstances such as drought, however, do not necessarily comply with these ideal assumptions, which then trigger the studies on optimal hedging rules. More frequent mild droughts are preferred to less frequent severe droughts. In the present work, the-constrained-based multi-objective optimization model was developed to optimize hedging rules for a reservoir located in Lombok Island, Central Indonesia. The rules were aimed to minimize two objective functions namely maximum Single Shortage (SS) and Total Deficit (TD). The former is a measure of reservoir operation during drought in short-term, whereas the latter is for long-term evaluation. Results show that these two measures are conflicting in nature, that is, the greater the SS, the smaller the TD and vice versa. The tradeoffs between SS and TD can be a helpful assist for water operators in executing their routine daily tasks by providing water allocation alternatives.
TLBO based Power System Optimization for AC/DC Hybrid Systems

This Paper Presents a TLBO based Power System Optimization for AC/DC Hybrid Systems. The objectives is to reduce the total fuel cost of generating units with optimal setting of control variables without violating inequality constraints and satisfying equality constraints. The recent developments in power electronics allow replacing the existing transmission lines by DC links with a view of making the operation more flexible, secure and economical. The solution process involves sequential NR based AC/DC power flow. It presents simulation results of IEEE 14, 30 and 57 test systems with a view of demonstrating its effectiveness.
Multi-Granularity Matching Network for Multi-Paragraph Machine Reading Comprehension

Multi-paragraph aims to allow machines to read multiple paragraphs and infer the answer to the given question. Usually, the model needs to use the selector to narrow the range of candidate paragraphs, and then use the reader to find the answer. For the selector, the previous work generally matches the question and the paragraph on the word level and the paragraph level. In this paper, we study the encoding and matching algorithm at the chunk level, which is supposed to make our model more accurate. Combining it with gated self matching mechanism, we design a multi-granularity matching network as the selector. The experimental results show that our model achieves competitive performance on Quasar-T.
High Performance Liquid Chromatography-Determination of Different Speciations of Arsenic in Cosmetics by Inductively Coupled Plasma Mass Spectrometry

There is a way to determine four arsenic speciations simultaneously in cosmetic by using liquid chromatography (HPLC) with inductively coupled plasma mass spectrometer (ICP-MS). After being extracted by phosphoric acid solution, the samples were separated by PRP-X100 anion chromatographic column. The mobile phase was aqueous solution (pH=6.0) containing 1% methanol (V/V), 2.0 mmol/L NaH2PO4 and 0.2 mmol/L ethylene diamine tetraacetic acid (EDTA). The octopole reaction cell was adopted to eliminate mass spectrum interferences. The separation of AsIII､DMA､MMA and AsV was achieved within 12 min with flow rate of 1.00 mL/min and sample size of 100 μL. The recovery rates of AsIII, DMA, MMA and As Vranged from 80.6% to 107.2% and the relative standard deviations were less than 6.24% when the spiked amount was 0.10∼ 1.00 μg in different kinds of cosmetic samples. The developed method has the advantage of simplicity, sensitivity and good reproducibility, and can be used for the determination of arsenic speciations simultaneously in cosmetics.
Phased-MIMO Radar : Angular resolution

Phased-MIMO is very suitable for multi-target detection such as radars for bird migration, radars for autonomous cars, fish radars and others. The problem is the ability of radar to distinguish the first target, the second target and the next target. This study reports the ability of Phased-MIMO radars to be able to distinguish two or more objects that are close known as angular resolution of radar.
Research on Multi-sensor Path Planning Based on Corridor Environment

Aiming at the problems of traditional A* algorithm with many inflection points, large turning angles and not adapting to dynamic environment, the current optimized A* algorithm is analyzed and researched. Designed and built a wheeled robot platform with 4WD trolley as the carrier, single-line lidar Rplidar_A3, depth camera Kinect V2 and ultrasonic sensor TeraRanger one as environmental detection sensors. The platform conducted simulation research on the three optimized A* algorithms in the indoor corridor environment, compared the pros and cons of the planned paths, and set up path planning experiments based on the static network improved A* algorithm and dynamic obstacles and static Obstacle avoidance experiment. Experiments prove that the trajectory planned by the improved A* algorithm based on the static network contains 7 inflection points, which is relatively smooth, takes 49.8s and can effectively avoid dynamic and static obstacles.
The development of blended media learning through google classroom to support teaching and learning in IAIN Takengon

This research aims to acquire a decent and effective Google Classroom based blended learning medium to support the learning development at the State Institute of Islamic Religion (IAIN) Takengon. To develop the Google Classroom based blended learning, the writer applied 4D Development Model which consists of four stages. The four stages are the definition (define), the design stage, the developing stage and the development stage (disseminate). The results of the development activities are: (1) The learning medium of effective Google Classroom based blended learning medium of Google Classroom based blended learning and (2) the guided user book for lectures or teachers. The validation results of experts are known that the intervention in developing guide book of Google Classroom based blended learning can be declared valid or have a high level of content validity.
Kinematic modelling and analysis of single leg in hybrid wheel-legged mobile robot

Mobile manipulators are extensively used in various applications. Most of the mobile manipulators are built on a wheeled mobile platform. A wheeled mobile platform performs well on flat terrains but is not suitable for navigation in rough terrains. The legged robots are commonly used for rough terrain applications. However, the navigation speed of legged robots is lesser than wheeled mobile robots. This paper focuses on the development of hybrid wheellegged robots to overcome the above difficulties. The proposed model is quadruped with five degrees of freedom in each leg. The development of the kinematic model, its dimensional synthesis, and motion study for a single leg is presented in detail. DH-conventions are used for kinematic modelling, manipulability index is used for dimension synthesis, and motion study is carried out in ADAMS.
Solvothermal-Assisted Hybridization between Reduced Graphene Oxide and Lithium Metal Oxides: A Facile Route to Graphene-Based Composite Materials

Hybridization between lithium metal oxide and reduced graphene oxide, or RGO, can be achieved by the solvothermal treatment of the water/ethanol-based suspension of graphite oxide, or GO, nanosheets containing powdery lithium metal oxide. The solvothermal treatment for the mixture suspension of GO and Li4Ti5O12 gives rise not only to the reduction of GO to RGO but also to the attachment of the Li4Ti5O12 particles to the flat surface of RGO 2D nanosheets. The crystal structure and crystal morphology of the Li4Ti5O12 particles remain intact after the composite formation with the RGO nanosheets. The formation of chemical bonds and internal electron transfer between the RGO and Li4Ti5O12 components is evidenced by micro-Raman and X-ray photoelectron spectroscopy, showing the weakening of the carbon–carbon bonds and the formation of carbon–oxygen bonds. In comparison with the pristine Li4Ti5O12 material, the Li4Ti5O12–RGO nanocomposites display better anode performance with a larger discharge capacity of ∼175 .
Computer Multimedia Technology in the Visual Psychology Experimental Teaching of Designing Color

Designing color visual teaching is one of the most fundamental courses for students major in visual communication, and is a crucial course for student to master and control the color in a good way. Computer multimedia technology (CMT) is a prevailing teaching-aided way in recent years. This study is to explore the advantages of CMT in visual psychology experimental teaching of designing color. In this study, 87 teachers in visual communication teaching from 10 universities and colleges in Lanzhou City are selected as research objects, and they are interviewed with the purpose of knowing the current application of CMT in visual psychology experimental teaching of designing color. After interviewing, the summary and analysis on recorded information reveals that CMT can change the traditional teaching mode, enrich the current teaching content, reduce the writing pressure of teachers in blackboard, and enhance the innovation ability on color design of students. In addition, CMT can help students to display a work with current fashion colors, which can meet the market demand better. Finally, it can be concluded that CMT can be applied in visual psychology experimental teaching of designing color good, and even the whole field of education in a good way.
Research on seismic wave first arrival Picking Based on improved U-Net

For the current problem of low accuracy of seismic wave phase pickup, this paper proposes a method based on the improved U-Net seismic wave P-wave and S-wave first-to-arrival pickup. Firstly, in order to reduce the impact of pre-processing operations such as filtering, the 20,000 three-component seismic waveform data will be normalized as input. Secondly, in order to reduce the loss of information during the seismic waveform extraction and increase the amount of information of effective features at the starting point, the Residual Unit is added to the encoder part of U-Net only, instead of adding it to the decoder part. In order to reduce the loss of high frequency information of seismic waveform, convolution operation is used instead of pooling operation. Finally, the probability distributions of P-wave, S-wave and noise are used as the output. The results show that the accuracy of the first-to-arrival pickup of P-wave is 93% and the accuracy of the first-to-arrival pickup of S-wave is 90% of the test set. The improved U-Net increased 30.9% and 6.2% in P-wave accuracy, 7.6% and 2.8% in S-wave accuracy, 39.6% and 4.0% in the P-wave recall, and 41.5% and 4.7% in the S-wave recall, respectively, compared with the conventional STA/LTA and U-Net. The improved U-Net outperforms the other two models in both evaluation metrics of recall and accuracy. The research results of this paper are of great practical significance in the localization of earthquakes, the interpretation of the earthquake gestation mechanism, and the prevention and mitigation of earthquakes.
Segmentation and Reconstruction of Abdominal Multi-tissues Based on Multiple Algorithms and Networks

Liver cancer has become a major disease that seriously endangers people’s lives and health. In clinical practice, it is necessary to segment the liver, lesions, and other normal organs and tissues in abdominal CT images accurately. However, segmentation of abdominal organs and tissues is a critical and time-consuming process in radiotherapy. Therefore, it is very important to use fully automated and high-precision methods to segment and reconstruct abdominal multi-tissues. This article integrates the automatic recognition process and main segmentation algorithms of skin, bones, intrahepatic blood vessels, liver and lesions. In addition, it supports human-computer interaction to modify the segmentation results, as well as the reconstruction of 3D surface, the measurement of size and volume, and other functions. The threshold segmentation and morphological operations are used in segmentation and reconstruction of skin and bones. And the fuzzy C-means algorithm is utilized in the segmentation and reconstruction of intrahepatic blood vessels. As for the segmentation and reconstruction of liver and lesions, we use convolutional neural network named V-net to accomplish. The experimental results show that the Dice coefficients of the skin and bones segmentation were 98.4% and 92.3%, respectively. The intrahepatic blood vessel segmentation was 78.9%. And the liver and lesions segmentation were 95.4% and 80.4%, respectively. The ensemble algorithm proposed in this paper demonstrated its potential clinical utility in terms of accuracy and time-efficiency.
Realization of Dependable Digital Systems for Safety-Critical Computer Systems using FPGAs

Digital systems built based on field-programmable-gate-arrays (FPGAs) are increasingly being used in safety-critical computer systems. These systems typically require high levels of integrity, reliability, and performance to ensure the correct operation of the critical application in which the digital systems are embedded. To achieve the safety and functional objectives, many hardware architectural scenarios based on fault tolerance techniques were proposed. This research paper presents a new dependable digital system (DDS) that consists of fault tolerant blocks (FTBs), spare functional blocks (SFBs), synchronization units, and input output units. Markov-based chain have been used to model the correct operation of the proposed hardware system that is targeted to be realized on FPGA-based technology. This system was designed to be reliable against transient faults (TF), permanent faults (PF), and hardware common cause failures (CCF). The reliability analysis of the proposed system was accomplished with Markov modeling techniques which could express the regenerative behavior of the digital system. Certain states in the system represent system failure, while others represent fault-free behavior in the presence of faults. Finally, based on the MathWorks Simulink simulation results of modeling the DDS digital system, the system does meet its functionality and reliability requirements.
Cloud Computer Research on Table Detection Model Based on the DC-LSTM Model

In view of the fact that tables are not easy to detect, this paper designs a table detection model based on the DC-LSTM module, which references the Convolutional Long Short-Term Memory (ConvLSTM). The model uses the backbone network of target detection to extract convolution features. The feature pyramid network is used to complete the detection task, and the DC-LSTM module is embedded in a special position in the feature pyramid network. In order to evaluate the performance of the DC-LSTM module, we added the DC-LSTM module to the YOLO v3, SSD network. Specifically, we added the DC-LSTM module to the YOLO v3 network, the new model can achieve an accuracy of more than 98% on the Table Bank data set and own data set. The model in this paper can realize the automatic extraction of table document images, which is of great significance for the realization of automated data collection.
Innovative Application of Artificial Intelligence Technology in College Physical Education

Against the background of the new era, the birth of artificial intelligence technology opened a new chapter in human development. Artificial intelligence technology has been developed in many places. The report discusses the application and innovation of artificial intelligence technology in college sports. The first thing people think of artificial intelligence is robots. In fact, it can be said that artificial intelligence can replace human labor. Artificial intelligence is a product of modern technology and cannot be understood unilaterally. For example, the various means of transportation used in people’s daily travel is an artificial intelligence that can replace people’s walking. Another example is that elevators can replace people on stairs. It is also a type of artificial intelligence, which is not an advanced technology. Product, it is also seen everywhere in people’s daily life. Artificial intelligence is a synthesis of scientific and intelligent technology created by human beings. It is a scientific technology including computer science, cognition, logic, etc., formed through mutual intersection and integration. In recent years, artificial intelligence has achieved considerable development, but there are still a series of unsolved problems, and the development of artificial intelligence is still very long. This article studies what artificial intelligence has facilitated and changed the physical education in colleges and universities, and what changes have taken place in the teaching mode are all worthy of our thinking. As a result, artificial intelligence technology is convenient for teachers and students in teaching. Let’s take a look at how to innovate.
Hyperbolic surface wave propagation in mid-infrared metasurfaces with extreme anisotropy

Hyperbolic metasurfaces are characterized by an extreme anisotropy of their effective conductivity tensor, which may be induced at visible frequencies by sculpting metals at the subwavelength scale. In this work, we explore practical implementations of hyperbolic metasurfaces at mid-infrared wavelengths, exploiting devices composed of metals and high-index semiconductor materials, which can support the required field confinement and extreme anisotropy required to realize low loss hyperbolic surface waves. In particular, we discuss the role of broken symmetries in these hybrid metasurfaces to enable large and broadband hyperbolic responses spanning the entire mid-infrared wavelength range (3–30 μm). Our findings pave the way to the development of large scale nanophotonic devices to manipulate mid-infrared light, with applications in nonlinear optics due to the high field confinement, light routing at the nanoscale, thermal control and management, and sub diffraction imaging.
Control of information security monitoring perimeter of industrial facilities

In the process of monitoring industrial facilities information security, the sets of heterogeneous data are generated by different monitoring tools which are to be processed according to various regulatory documents not always compatible with each other. Definition of a set of security characteristics based on perimeter monitoring data and determination of security level carried out mostly by calculating integral indicator do not take into account some aspects of security. The method is proposed for the harmonization of industrial facilities interaction and for the formation of a set of security indicators on the basis of formalized subject domain description and unified data description scheme.