nils-herrmann/clean_scirepeval huggingface dataset:
ESD damage by directly arcing to a MR head

Direct arcing to a MR head occurs when the electric field exceeds the dielectric strength of the insulating material. This usually occurs on the air-bearing surface. It can not be prevented by shunting, insulating, or grounding the leads. The most effective solution is to reduce the field strength near the MR head. Two examples from Headway manufacturing experience are described. In the first case, a glass disk is charged by rubbing with the slider. The charged disk causes arcing between the MR head and a magnetic shield. In the second case, a high-voltage electrode for gold-ball-bond arcs accidentally to the MR head. Symptoms, the arcing mechanism, and the solutions are described.
Research on entrepreneurial team members' personality traits influence on group risk decision-making

Group decision making is frequently adopted in entrepreneurial activities. This study explores the influence of entrepreneurial team members' MBTI personality types upon group opportunity perception, risk perception and risk propensity. Through the empirical investigation of 46 entrepreneurial teams of university students, it is discovered that when controlling the influence of team members' involvement, the group with more intuition type members is more likely to make optimistic estimates of entrepreneurial opportunity than the group with more sensing type members; the group with more perceiving type members is likely to detect more entrepreneurial opportunities, lower risks and possess higher risk propensity than the group with more judging type members; the group with more extroverted members perceives lower entrepreneurial risks than the group with more introverted members. This study's results can help the entrepreneurial teams to improve their rationality in the course of decision making based on the full recognition of the members' personality types.
Partner Selection System for Collaborative Design

With the development of the global market, the growth internet technology is changing design style. Collaborative design is a new design style for designers of different places to complete the same design project. However, how to select a suitable partner for the collaborative design project is an important problem. A fuzzy Analytic Hierarchy Process (AHP) methodology is presented for the partner selection, which provide a multi-criteria decision making approach for partner evaluation and selection decision. Firstly, the concept of fuzzy Analytic Hierarchy Process (AHP) is introduced and the framework of system is constructed. Secondly, the criteria weights are calculated by the fuzzy AHP to search for the suitable partner. Then the partner is found by AHP. The system for partner selection is established by means of fuzzy AHP method. XML is applied for the evaluation model to explain the relationship of system.At last, a prototype is presented to demonstrate the methodology.
Chitosan-Based Electrolyte Gated Low Voltage Oxide Transistor With a Coplanar Modulatory Terminal

Indium-zinc-oxide thin-film transistors (TFTs) using chitosan-based bio-polysaccharide electrolytes as the gate dielectric are fabricated. The TFTs show a good electrical performance with a very low operation voltage of ~1.0 V. Specific gate capacitance of the electrolyte film and electrical performance of the TFTs can be effectively modulated by the coplanar modulatory terminal due to synergic proton gating effects. Furthermore, a resistor-loaded inverter is investigated, and balanced noise margin is obtained. Such oxide-based TFTs with additional modulatory terminal may find potential applications in portable electronics.
A risk management strategy for a wind power producer based on bilateral contracts

The integration of renewable energy is increasing rapidly in electric energy systems throughout the world. This paper presents a bilateral contract model for wind power and provides a risk management strategy for a wind power producer to trade energy in spot market and bilateral contract market. It uses long-term wind speed prediction to determine contract volume, and uses short-term wind speed prediction to determine offers submitted to spot market. Autoregressive moving average model and autoregressive model are used to simulate wind farm output and spot price series. Profit-at-Risk index is used as a risk management metric. Simulation results of a case study show that the purposed trading strategy can obviously reduce financial risk of a wind power producer with the expected profit unchanged.
A framework for finding the optimal linear scaling factor of /spl epsi/-approximation solutions

Many works reported in the literature tackle the problem of delay constrained least cost path selection (DCLC) by using /spl epsi/-approximation schemes and scaling techniques, i.e., by mapping link costs into integers or, at least, discrete numbers, a solution that satisfies the delay constraint and has a cost within a factor of (1 + /spl epsi/) of the optimal one can be computed with pseudo polynomial computational complexity. In this paper, having observed that the computational complexities of the /spl epsi/-approximation algorithms using the linear scaling technique are linearly proportional to the linear scaling factors, we investigate the issue of finding the optimal (the smallest) linear scaling factor to reduce the computational complexities and propose a theoretical framework.
Research on Thinking Tendency Prediction Technology of Students Based on Big Data Analysis

In the research of the thinking tendency prediction technology of students, using current methods to predict the feature description of students thinking tendency is not detailed enough. This can not accurately reflect the characteristics of changes in the students thinking tendency. There is a big error in the prediction process. Therefore, this paper proposes a method of thinking tendency prediction technology of students based on large data analysis. This method targeted non-stationary characteristics of students thinking tendency prediction time series, and combined the principle of empirical mode decomposition, decomposing it into several intrinsic mode components. On this basis, we used the large data analysis to set up the corresponding prediction model of college students thinking, and used the information provided by initial data of finding trends for nonlinear combination of the trend parameters and boundary values to be identified in the model. We identified again, predicting the tendency of students thinking. Experimental results show that the using large data analysis to predict the tendency of students thinking has high accuracy and satisfactory result.
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases

Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the frequent subgraphs with a certain topology is of special interest. Thus, the method of mining the complete set of all frequent subgraphs is not suitable for mining these frequent subgraphs of special interest as it wastes considerable computing power and space on uninteresting subgraphs. In this paper we develop a new algorithm, CLAN, to mine the frequent closed cliques, the most coherent structures in the graph setting. By exploring some properties of the clique pattern, we can simplify the canonical label design and the corresponding clique (or subclique) isomorphism testing. Several effective pruning methods are proposed to prune the search space, while the clique closure checking scheme is used to remove the non-closed clique patterns. Our empirical results show that CLAN is very efficient for large dense graph databases with which the traditional graph mining algorithms fail. The novelty of our method is further demonstrated by the application of CLAN in mining highly correlated stocks from large stock market data.
Computationally Efficient Optimal Discrete Bit Allocation for Medium and High Target Bit Rate DMT Transmissions

A computationally efficient optimal discrete bit allocation algorithm is proposed for medium and high target bit rate discrete multitone (DMT) transmissions. Unlike conventional greedy bit-loading algorithms, which compare the incremental transmission power of multicarriers bit-by-bit and allocate one bit at a time, the proposed algorithm is based on parallel bit-loading with reference to a virtual equal power assignment bit allocation. After maximum bit rate allocation, the algorithm achieves the target bit rate by two types of parallel bit- loading. If the target bit rate allocation is not optimal, bit swapping is performed to obtain the optimal solution. Simulation results using the standard asymmetric digital subscriber line (ADSL) test loops demonstrate the reduced computational load of the proposed algorithm compared to the existing optimal discrete bit allocation algorithm when the target rate is between 60% and 99% of the loop's maximum bit rate.
Humidity-Dependent Synaptic Plasticity for Proton Gated Oxide Synaptic Transistor

Indium-tin-oxide synaptic transistors using proton conducting nanogranular phosphorosilicate glass as gate dielectric are fabricated. Humidity-dependent proton gating behaviors are observed. Moreover, synaptic plasticities are mimicked on the proton gated oxide synaptic transistors. Interestingly, enhanced synaptic facilitation is observed at higher relative humidity originated from the strengthened proton gating. An oxide synaptic transistor with humidity-dependent synaptic plasticities may find potential applications in neuromorphic platforms.
The moving detection algorithm based on clustering technology

Moving detection algorithms are very popular and widely applied. However, the algorithms may have lower accuracy or higher time complexity. To improve that, a moving detection algorithm based on clustering technology is proposed in the paper. It divides an image differences into some clusters. A minimum spanning tree is generated based on those clusters. Compare the average shortest path of minimum spanning tree and a threshold to detect the differences. The algorithm inherits the high accuracy of clustering technology and shows high detection performance.
Two Types of Attacks against  Cognitive Radio Network MAC Protocols

Some typical MAC protocols have been proposed for multi-hop CR network recently. In a multi-hop MAC protocol, a node uses the common control channel to perform channel negotiation before data transmission. Recent research findings indicate that insecure transmission of control channels open vulnerable holes for the Denial of Service attacks. This paper makes a security analysis for CR network MAC protocols. There are two types of attacks against CR network MAC protocols. Firstly, we study how denial of service (DoS) attack is launched in multi-hop CR network MAC protocols. Then, we explore MAC layer greedy behaviors in CR networks. Our analysis and simulations indicate that such attacks can greatly affect the performance of CR networks. And the key factors for attack efficiency are presented in this paper.
A Dynamic Cell Resource Reserving Handoff Control Algorithm

Handoff block rate is a very important QoS (Quality of Service) indicator in mobile communication. In hard handoff, the conventional method of reducing handoff block is to reserve some channels especially for handoff mobile terminals in the cell or cell group. This is a static method. It can guarantee the handoff successful rate, but in the meantime, some resource of wireless channel is wasted. In this paper, a dynamic reserving channel resource algorithm has been put forward on accessing instantaneous process. It can improve the utility of wireless network resource. In the paper, this algorithm also is tested in simulating experiment. The results show that the algorithm is available.
Handoff performance improvement in a network virtualization based integrated train ground communication system

In this paper, we propose a network virtualization based integrated train ground communication system for urban rail transit systems. In order to improve the CBTC subsystem performance during handoff, we propose a novel handoff scheme to support handoff between virtual networks. The application layer QoS parameter of the CBTC, PIS and CCTV subsystems is used as the performance measure in the handoff design. The proposed integrated train ground communication system QoS optimization problem is formulated as a Approximate Dynamic Programming (ADP) problem. Extensive simulation results show that the proposed integrated train ground communication system QoS can be improved substantially with our ADP based optimization model.
Impact of T/R module performance on tradeoff design of airborne AESA radar

Transmit/Receive (T/R) modules are key components in Active Electronically Scanned Array (AESA) for advanced airborne radar, and their performance affects the capability of airborne AESA radar in several aspects. In this paper, a procedure is proposed with the tradeoff design of an AESA radar between the power-aperture product (PAP) and the peak-to-side lobe ratio (PSLR) of its antenna. While the PAP decides the maximum detection range, the PSLR is desired for low probability of intercept (LPI) radars as well as for alleviating clutter interference. The analysis results indicate that both high PAP and PSLR can not be achieved simultaneously based on the state-of-art performance of Ku-band T/R modules.
Radar HRRP recognition based on discriminant deep autoencoders with small training data size

A novel radar high resolution range profile (HRRP) recognition method based on discriminant deep autoencoders is proposed to enhance the classification performance with limited training samples. Compared with the conventional models, the proposed method not only extracts high-level feature which can reflect physical structure of HRRP, but also trains HRRP samples globally to reduce the requirement of the training data. The experiment based on the measured data demonstrates the physical meanings of the extracted feature. Moreover, the recognition performance of the proposed method consistently outperforms the conventional models, and the improvement become more significant with smaller training data size.
Using Wavelet Support Vector Machines to Generate Expected Outputs

A test case consists of a set of inputs and a list of expected outputs. To automatically generate the expected outputs for the test case is rather difficult. An approach based on wavelet support vector machines (WSVM) is proposed to overcome it. After training, WSVM is used to automatically generate the expected outputs, which approximate the correct outputs. Actual outputs of the application under testing (AUT) are then compared with expected outputs in an interval to determine if there is a failure. Experiment and comparison show that the method is effective and can save a lot of time and labor in software testing
Degradation of Hemicelluloses of Cottonseed Coat by Xylanase

The hemicelluloses were separated from the cottonseed coat and degraded with Pulpzyme HC. The digestion degree value was calculated by the equation depended on the release of reducing sugars concentration which was determined from DNS fitting curve equation. The optimum enzyme reaction temperature was 60&#8451; and pH was 5.5. The duration of 80 min was chose as the most suitable enzymolysis time. The degradation degree value was 57.5% when 0.24 ml pure Pulpzyme HC was added with one milligramme hemicelluloses powder. The K+ content substrate (0.5 mmol L-1) enhanced the enzymic degradation of hemicelluloses. The other metal ions were found to be some inhibitors of Pulpzyme HC. The effects of chelating agent (EDTA) were complex and no trend was observed.
Research on data query technology of hierarchical storage for electric power dispatching system

This paper presents a unified dispatching management data query architecture of hierarchical storage in smart grid. With the concept of cloud computing, we take into account the integration IT infrastructure resources, to achieve the effective organization of different data resources. By dispatching data network located in the control center, we provide efficient data sharing, interactive, retrieval of various services for dispatching management business applications. In order to achieve with data-sharing target, we focuses on the analysis of integrated cloud data query architecture for the hierarchical storage management. The architecture can provide a theoretical basis for the overall design and application of the data query prototype system of dispatching management.
Reliability analysis of the usual loop network structure for regional power supply systems based on state space method

In this paper, a regional power supply system is taken as a radial system with redundancy reservation and a spinning reserve system. Reservation types are defined and described. Furthermore, a new reliability analysis method for the simple loop network structure of the regional power supply system is developed. The reliability analysis model for a simple loop network's power supply system is built up based on the state-space analysis technique by considering failure and repair rates of wires. In the proposed model, through drawing the state transfer chart of the redundancy reservation system, the corresponding transfer density matrix and linear equation group are put forward, and the solution of placidity state probability is obtained. The power supply unreliability degree and reliability degree of the substation and the average time of the power supply lines in all different states are calculated. The conclusion is extended to state of the complex loop network. It is the first time that the state space method is applied to the power supply reliability evaluation of the regional power supply systems with higher calculation accuracy. The effectiveness of the proposed method is verified by an example.
Fast Inter Mode Selection Algorithm in MPEG-2-to-AVS Transcoder

AVS (the advanced audio video coding standard), established by audio video standard working group of China, achieves higher coding efficiency than MPEG-2. In contrast to MPEG-2, where only inter prediction mode with 16times16 block size is used, AVS also supports inter modes with 16times8, 8times16, 8times8 block size. This presents a challenge to MPEG-2-to-AVS transcoder for a good balance between the complexity and performance. In this paper, we propose a fast inter prediction mode selection algorithm including inter-inter and intra-inter mode selection. Reusing the inter prediction errors from the MPEG-2 bit stream and intra prediction errors between blocks, we select the best inter prediction mode. The simulation results of many test sequences show that the proposed algorithm reduces the computation cost while maintaining similar PSNR and bit rate. This idea also can be used in other standards to AVS/H.264 transcoding
Adjustable Bandwidth Filter Design Based on Interdigital Capacitors

In this letter, we explore a general-purpose microstrip coupling model for computer aided design of new bandpass filters. The J-inverter topology of the model facilitates the study of coupling behaviours of different microstrip structures leading to a quick comparison of their coupling strengths. Based on such comparison, microstrip filters with interdigital capacitors and etched slots yielding relatively higher coupling coefficients are designed, fabricated and tested. The filters exhibit relatively wider bandwidths which are easily adjustable by way of changing the geometrical parameters of interdigital capacitors and slots.
Miniaturised microstrip dual-band bandpass filter using novel symmetric double-spiral resonators for WLAN application

A miniaturised dual-band bandpass filter (DB-BPF) centred at 2.45/5.70 GHz using novel symmetric double-spiral resonators is proposed. The measured and simulated results of the proposed DB-BPF are in good agreement with each other except for a slight frequency shift downwards in the measurement. According to the measurements, the measured 3 dB bandwidths are 6.53% (2.35–2.51 GHz) at 2.45 GHz and 4.2% (5.61–5.85 GHz) at 5.70 GHz; the insertion losses including the loss from SMA connectors are <0.8/1.2 dB and the isolation between these two passbands is better than 20 dB from 2.54 to 5.59 GHz. The circuit area of the fabricated prototype is very compact, being only 7.7 × 9.4 mm.
Image Re-Ranking Based on Topic Diversity

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.
The Comparative Research of Solving Problems of Equilibrium and Optimizing Multi-Resources with GA and PSO

Genetic algorithm and particle swarm optimization both belong to the evolutionary algorithms; they have much in common, but also have some differences. The paper set out from optimizing many resources, discussed the method of utilizing GA and PSO in detail, in order to equilibrium and optimize the problem of scheduling resources which are limited separately. Through analysis of comparative experiment, two kinds of intelligence-optimizing methods made very good results when solved a same problem, but in most cases, PSO has a faster rate of convergence than GA.
A Support Vector Machine-Based Method for Predicting Chemokine Receptors Types

Chemokine receptors represent a prime target for the development of novel therapeutic strategies in a variety of disease processes. The prediction of interesting proteins types by computational methods can provide new clues in functional studies of uncharacterized proteins without performing extensive experiments. Support vector machine (SVM) is a new kind of approach to supervised pattern classification that has been successfully applied to a wide range of computational biology fields. In this study, a SVM classifier was implemented to predict two main types of chemokine receptors based solely on amino acid composition and associated physicochemical properties. The performance on the tree kernel method we developed is comparable to that of other kernels while giving distinct advantages when evaluated through 10-fold cross-validation technique, indicating the current approach may serve as a useful tool for further investigating the processes of cell molecular mechanism of this important family. The experimental results also show that the features and the classifiers in detecting chemokine receptors types are effective.