nils-herrmann/clean_scirepeval huggingface dataset:
Distributed Management for High Resolution Ocean Environmental Data

The volume of ocean environmental data is extremely massive, which makes it inefficient to manage them in standard ways. This paper promotes a new method to handle this problem. It presents a non-standard method that stresses on query-oriented organization of the data. Then it describes in details of the distributed management of the data based on the new relation schema design. The method has been implemented in a database cluster middleware named Distributed Ocean Environmental Data Manager (DOEDM). Experiments show that DOEDM gives a better support to the Marine and Atmosphere Geographic Information System (MAGIS) because it requires less storage space and has better query performance.
Adaptive Multistate Markov Channel Modeling Method for Reentry Dynamic Plasma Sheaths

Channel modeling of a plasma sheath for hypersonic reentry vehicles is important in addressing reentry communication blackout issues. Given that the time-varying property of the transmission medium is caused by physical factors such as large-scale flight conditions variation, especially angle of attack, and small-scale fluid turbulence, a new adaptive multistate Markov channel modeling method is proposed to present the dynamic effects of reentry plasma sheaths on wireless channels. First, a quasi-Gaussian function mathematical model for the electron density of a dynamic plasma sheath is established according to the variation frequency of the dynamic physical factors. Then, the time-varying attenuation is calculated by combining the quasi-static Monte Carlo and uniform hierarchical analytical methods for nonuniform electronic density distribution. Finally, a hidden Markov model is employed to model the channel characteristics of the dynamic plasma sheath, and a reversible-jump Markov chain Monte Carlo algorithm is used to adaptively estimate the channel parameters of the multistate Markov channel. Simulation results show that the first-order statistical properties of the proposed channel are in good agreement with the calculated variable attenuation of radio waves, and this method has the adaptive capacity to estimate the number of multiple states and the channel parameters in each state without a need for manual setting.
BDS / GPS fast satellite selection algorithm

In order to realize the rapid satellite selection of BDS / GPS dual-mode navigation system under the premise of satisfying the normal positioning accuracy, a new fast satellite selection algorithm is proposed. The algorithm combines the traditional satellite selection algorithm with genetic algorithm. The satellite area is divided by the elevation angles information of the visible satellite, according to the characteristics of satellite distribution, then the optimal geometric distribution of satellites are selected. And the simplified GDOP calculation model is used as the fitness function to judge the merits and demerits of the individual in the genetic algorithm, so as to obtain the optimal solution of the smaller GDOP value and achieve the goal of fast satellite selection. Finally, the algorithm is compared with the optimal GDOP algorithm, and the experimental results show that the fast satellite selection algorithm guarantees real-time, which is better than the optimal GDOP algorithm, and the standard deviation in the two-dimensional coordinate system of longitude and latitude is 1.90m.
Design study of gripping module for multi-size objects with tactile sensory feedback control

Automated grasping for a wide range of objects is challenging yet highly demanded for different applications. The technology for automated grasping a single object is mature, but some conventional gripping modules operation for grasping objects with different dimensions via tele-operation is ineffective and infeasible in some circumstances like high altitude or hazardous environment. To tackle these concerns, we have designed a gripping module comprising a four-bar linkage dual-finger gripper and arrays of tactile sensors on the gripping surface. The gripper has been integrated with force feedback control to monitor the gripper-object interaction during their movements. In this paper, we will discuss the mechanical design of the gripper, the work flow and the feedback control mechanism.
A new contour tracing automaton in binary image

A new contour tracing automaton for four-connected binary images is presented in this paper. The algorithm adopts a unique contour labeling method to trace contour of image. While traversing the image, the inner contour and outer contour can be distinguished. Connectivity information also can be preserved simultaneously. Furthermore, it is capable of generating the three traditional types of chain code. Experiments after prove that the new algorithm increases the coding efficiency for binary image.
A novel two-way TM01 mode combiner for high power microwave applications

In this paper, we propose a novel two-way coherent TM01 mode combiner that combines the two-way TM01 mode to a one-way TM01 mode with high power capacity and combining efficiency. It is mainly composed of two two-way TM01 mode to TE10 mode power dividers, one four-way TE10 mode to TM01 mode power combiner and four H-plane bend rectangular waveguides. Simulation shows that, at center frequency 9.3 GHz, the isolation between two input ports is -19 dB, return loss for the input port the output ports is -22 dB and -26 dB respectively, the insertion loss is less than -0.1 dB. From 9.1 to 9.5 GHz, the isolation and single port return loss are both better than -10 dB, and the insertion loss is better than -0.3 dB. Its power capacity can be predicted to be approximately 5GW with the breakdown threshold 100 MV/m. The novel TM01 mode combiner has the merits of high power capacity and low insertion loss and high isolation between the input ports. Further experiments will be carried out to verify the simulations.
An Average Current Modulation Method for Single-Stage LED Drivers With High Power Factor and Zero Low-Frequency Current Ripple

Conventional single-stage light-emitting diode (LED) drivers with a high power factor (PF) contain a significant LED current ripple at twice the ac line frequency, and would require large energy storage capacitors to limit the effect on LED light. Conventional designs and novel control techniques aim to power LED loads with a dc voltage to ensure a limited low-frequency LED current ripple. This paper proposes an average current modulation method that is designed to operate in conjunction with single-stage PF correction (PFC) circuits that contain significant ac voltage ripple, while maintaining zero low-frequency current ripple. This allows the energy storage capacitance of the PFC stage to be reduced, avoiding the need for electrolytic-type capacitors and prolonging the life of the LED driver. The average current modulation circuit requires a single low-voltage MOSFET, a current sense resistor, and a simple control circuit. By requiring no additional magnetic components, the cost of the current modulation circuit is very low and has minimal impact on the efficiency of the overall LED driver. Two experimental prototypes, an 8.75-W system with a buck-boost PFC converter and a 25-W system with a flyback PFC converter, have been built to verify the capability and excellent performance of the proposed driving technique.
A Framework for Efficient Data Analytics through Automatic Configuration and Customization of Scientific Workflows

Data analytics involves choosing between many different algorithms and experimenting with possible combinations of those algorithms. Existing approaches however do not support scientists with the laborious tasks of exploring the design space of computational experiments. We have developed a framework to assist scientists with data analysis tasks in particular machine learning and data mining. It takes advantage of the unique capabilities of the Wings workflow system to reason about semantic constraints. We show how the framework can rule out invalid workflows and help scientists to explore the design space. We demonstrate our system in the domain of text analytics, and outline the benefits of our approach.
Adaptive controller decomposition bumpless transfer for switching control

Bumpless transfer allows smooth switch between two different controllers. An innovative approach for bumpless transfer is put forward in this paper. It is a data-driven scheme that can enhance the transient performance of swithed system. Controller state initialization method is used to minimize the performance of the closed-loop switching system outputs. In this paper, the bumpless transfer of the switching controller under the tracking control is simulated and verified.
Behavioral modeling and EMC analysis for Tacan system

Tacan is a military omnibearing and distance measurement system, and it is an important system in L-Band. As there are so many equipments work in L-Band, the electromagnetic environment is very complex and EMC problems affect the function of Tacan. In-band narrowband noise is the noise that leads to EMC problem usually. In order to analysis the effect of in-band narrowband noise to Tacan, behavioral modeling is used in this paper. The distance measurement system part of Tacan (Tacan/DME) is modeled, and the simulation result shows that behavioral modeling can be used to analysis the existing EMC problems. After suitable EMC measures taken, the performance of Tacan/DME is turned back to normal. The method of behavioral modeling and EMC analysis shown can be used to the EMC pre-evaluation of other airborne electronic systems.
An Architectural Approach to Composing Reputation-Based Trustworthy Services

In SOA, Reputation-Based Trust (RBT) mechanism is applied to achieve trust management. RBT enables services to assess the trust level of other services based on the reputation accumulated from user recommendations. A key challenge to apply RBT is to prevent the strategic behavior of users when they provide recommendations -- they might give unfair ratings to benefit themselves. In this paper, we propose a novel architectural approach to integrating auction mechanisms into the trust framework to prevent benefits from untruthful incentives. In this architecture we define an auction-based trust negotiation protocol and realize it in the trust framework. The contribution of our architecture is that it scales and produces accurate results to achieve protection against untruthful incentives, especially when a majority of ratings are unfair, without the potential increase in a computation overhead. An example on a travel agent scenario is devised to collect empirical evidence.
A new smoothing particle filter for tracking a maneuvering target

A new smoothing particle filter is presented for applications in maneuvering target-tracking problems. In practical, these stochastic dynamic systems are usually nonlinear and incompletely observed, and the main difficulty of maneuvering target-tracking problem lies on the fact that the maneuverability at every step is of highly uncertainties. We propose here a new smoothing particle filter algorithm, which combines the particle filter, which tackles the non-linear and non-Gaussian peculiarities of the problem, and smoothing of the PDF of system modes, which settles the maneuverability of the target. In a simulation comparison with the auxiliary particle filters, we show that our approach has superiority and yields performance improvements when tracking a maneuvering target.
An Empirical Study of Large Shareholder Infringe on the Interest of Minority Shareholder during Post-Share Reform Era

As China's share reform came into the "post-share reform era", has the situation of large shareholder infringe on the interest of minority shareholder changed? This paper analyzes the factors that affect large shareholder infringe on the interest of minority shareholder in post-share reform era, by selecting 85 bulk share transfer issues from year 2007 to 2010 as sample data with an empirical study method. The results show that: the private benefits of control of shareholder among China listed company is on a relatively high level; Large shareholders infringe on the interests of minority shareholders did not significantly improve, the proportion of transfer shares is positively related with private benefits of control, and debt ratio is negatively related with private benefits of control. All of these findings are important for further study.
A New Method of Pefetching I/O Requests

Prefetching is one of the most important method to improve storage system performance. Without knowing any I/O semantics in device layer, it is not easy now for storage system to exploit semantic information and then to prefetch the data. Many prefetching policies have to relay on simple patterns such as sequentially, temporal locality and loop references to improve storage system performance. Therefore, according to characteristic of storage system, this paper not only introduces a new sequence degree-based clustering algorithm to find the storage areas which will be accessed frequently, but also adopts ARMA time series model to forecast the storage areas on which data will be read frequently later, and their corresponding request time. Moreover, to improve the forecast accuracy, this paper adopts dynamic parameter estimation policy to ARMA model. The results of a large number of simulations validate the accuracy of the clustering algorithm and the preciseness of the ARMA time series model of dynamic parameter estimation policy, and indicate that efficiency of cache prefetching can be greatly improved through applying the clustering algorithm and ARMA time series model.
Correlation-based system identification of digitally controlled SMPS

This paper presents a design procedure using the correlation-based identification to determine the compensation coefficients. A method for verifying the compensation coefficients is also proposed. That solved the open-loop frequency response of digitally controlled switched-mode power supply is difficult to accurately measure and provided a method to test the function of digital compensators. Experimental results show that the open-loop and closed-loop frequency responses obtained using the correlation-based identification method are close to the measured frequency responses.
An algebraic multi-class classification method

An algebraic multi-class classification method AHSC, i.e., algebraic hyper surface classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers, which are used for labeling the classes of samples. The problem that multi-class data cannot always be separated by a single polynomial is solved by AHSC. Moreover, using an adaptive method can choose the order of polynomial. The experimental results show that the new method can efficiently and accurately classify multi-class and high dimension data.
A solar powered long range real-time water quality monitoring system by LoRaWAN

In order to maintain the quality of water resources in the global environment, we must conduct water quality monitoring. With the evolution of technology, we can improve the management of water quality by the IoT(Internet of Things) system. Therefore, this paper provides a real-time water quality monitoring system by the Internet of Things system. We selected Dong Lake in National Dong Hwa University as a test field to monitor water temperature, turbidity, conductivity, and pH. After that, the various water quality data will be transmitted to the database via wireless transmission. Finally, these data will be displayed on the web page immediately. And, it is very important to select what kind of wireless communication technique. For the long-range application in the field, we used Low-Power Wide-Area Network (LPWAN)-Long Range Wide Area Network (LoRaWAN) for data transmission. To extend the system life, a solar panel is adapted to recharge battery.
Analysis of Neurodynamics on Phase Neural Coding in the Presence of Inhibitory Neurons

The paper studies the phase coding in the neural networks composed of neural oscillator populations through the theory of the stochastic phase dynamics under the presence of inhibitory neurons, builds a stochastic nonlinear phase dynamic model subject to coupling action of inhibitory neurons, and numerically analyses the process of dynamic evolution and spontaneous behavior under the condition of simulation according to the model. The results prove that inhibitory neurons can reduce the amplitude of the average number density in excitatory neural oscillator population, and trend of the synchronization motion of excitatory neural oscillator population can be controlled through increasing coupling coefficient of inhibitory neurons. Firing density of population of neural oscillator and evolution of average number density is studied through variety of the stimulation intensity.
Architecture-Based Adaptivity Support for Service Oriented Scientific Workflows

Adaptivity is the ability of a program to change its behavior automatically according to its context. Programs over multiple scientific workflows and analytic domains have similar needs of adaptivity to handle data intensive computing. These include dynamically selecting analytical models or processes according to data sets at runtime, handling exceptions to make long running workflows reliable, and reducing large volumes of data to a suitable form for visualization. Architecture support to reuse these adaptive techniques across different scientific domains helps to enhance the workflows' efficiency, extensibility and reliability. In this paper, a service oriented architecture framework is presented to compose adaptive scientific workflows. This framework has a core of service components and mechanisms that eases the interoperation between disparate workflows and programs that encapsulate the adaptive control logic. The uses of this framework are demonstrated by scientific workflow scenarios.
Design of a Novel Dual-Frequency Antenna for Wireless Communication Applications

The purpose of the paper is to develop a microstrip patch designed for dual frequencies of 2.45GHz and 4.75GHz. A new design of two circular patches with a small ring slot in the middle to get the dual band operation is proposed in this paper. It is a multiple patch method for getting dual frequency operation with a single feed point. The simulation and measurement were performed and the dual-frequency bands with a return loss less than -10dB were achieved. This design aims to develop a novel design for achieving a dual band operation for ISM band, RFID(2.4GHz), and radar systems(4.75GHz) applications.
A method of turbulence measurements from a moored reciprocating vertical profiler based on buoyancy-driven

Turbulence plays a crucial role in ocean dynamics and global biogeochemical cycles through redistributing heat, salt and nutrients across isodensity surfaces. Conventionally, most of microstructure measurements were conducted with vertical freefall profilers. In order to provide both a very high resolution vertical distribution of turbulent quantities and the long term series, a novel instrument MRVP (moored reciprocating vertical profiler) is developed in this paper. Recently, the instrument was deployed in the South China Sea (SCS) at 20° 55.490' N 118° 09.830' E for ocean turbulence measurements. The Profiler equipped with shear sensors, standard CTD sensors, and an attitude sensor measuring heading, pitch, roll, and three-axis acceleration, so that the Profiler is capable of measuring ocean microstructure. By changing the relationship between buoyancy and gravity, MRVP can make reciprocating sink and rise measurements along a moored smooth cable. Therefore, the MRVP can be moored at one place and autonomously acquires long-term microstructure series. The maximum measuring depth of the profiler can reach to 3000 meters. The dissipation rate in this experiment is between 10-9 and 10-7 W/kg, and matches well with Nasmyth spectrum in both shape and level. In general, the moored reciprocating vertical profiler (MRVP) offers a low-noise platform and a novel method suitable for multi-scale and longterm vertical ocean turbulence measurements.
A New Six-Switch Five-Level Active Neutral Point Clamped Inverter for PV Applications

Multilevel inverters are one of the preferred solutions for medium-voltage and high-power applications and have found successful industrial applications. Five-level active neutral point clamped inverter (5L-ANPC) is one of the most popular topologies among five-level inverters. A six-switch 5L-ANPC (6S-5L-ANPC) topology is proposed. Compared to the conventional 5L-ANPC inverters, the 6S-5L-ANPC reduces two active switches and has lower conduction loss. The proposed modulation enables the 6S-5L-ANPC inverter to operate under both active and reactive power conditions. The flying-capacitor capacitance is designed under both active and reactive power conditions. The analysis shows the proposed topology is suitable for photovoltaic grid-connected applications. A 1 KVA single-phase experimental prototype is built to verify the validity and flexibility of the proposed topology and modulation method.
Data Mining of Inspection-Time Rules in HIS with DeepSee

Inspection department is an important sector in the hospital as one of the most visited sectors. Thus the arrangement of manpower in inspection sector and reservation of enforced-time for inspections are very important. This study analyze Inspection-time in Hospital Information System (HIS) by data mining approach in order to help hospital managers improve efficiency. We first build a model based on Inspection-time theme, and then analyze the factors that influence the access number and waiting-time for the inspections in radiology sector in three aspects: the weekdays, the hours and the vocations. The knowledge discovery and data analysis is based on Intersystem embedded real-time business intelligence (BI) tool DeepSee.
A Cost-Based Resource Scheduling Paradigm in Cloud Computing

Infrastructure as a Service (IaaS) is the most common and fundamental type of cloud computing. It provides on-demand rent and access to virtual machine and storage. In this type of cloud computing, infrastructure service suppliers and users form a resource market. In this paper, we present a cost-based resource scheduling paradigm in cloud computing by leveraging market theory to schedule compute resources to meet user's requirement. The set of computing resources with the lowest price are assigned to the user according to current suppliers' resource availability and price. We design an algorithm and protocol for cost-based cloud resource scheduling. This scheduling paradigm is implemented and evaluated in Java Cloud ware, the pure Java based private cloud platform.
Adjustable gamma correction reference voltage source for LCoS

In this paper, an adjustable gamma correction reference voltage source for Liquid Crystal on Silicon (LCoS) is proposed. The reference voltage source is taped out by Chartered 0.35µm CMOS 2P4M Mixed-mode process, and the chip was tested. The test results indicate that the output of the chip can completely meet requirements of the common electronic field-inversion field sequential LCoS display system, and the setup time and accuracy of output voltage achieve the expected target.