nils-herrmann/clean_scirepeval huggingface dataset:
Integration on supply chain of technology-motivated mergers and acquisition based on the cost synergy

Technology-motivated M&A (Mergers and acquisition) and supply chain management have been viewed as the main direction of modern business management in the 21'st century. How to realize coordination by restructuring and integrating supply chain in technology-motivated M&A is very important for improving competition and reaching the strategic goal. Through studying the effect of technology-motivated M&A on supply chain, this paper establishes the cost synergy model of supply chain, gives solution methods and offers an example that is being analyzed. Reference value of the studies is given to those enterprises which are going to practice or consider on this topic.
Percentile performance analysis of infrastructure-as-a-service clouds with task retrials

Performance evaluation of cloud infrastructures and cloud-based applications is required to evaluate and quantify the cost-benefit of a strategy portfolio and the quality of service (QoS) experienced by end-users. For this purpose, we introduce an analytical framework to percentile-based performance analysis of unreliable Infrastructure-as-a-Service clouds with faulty and retrial tasks. The performance measured in a certain level percentile of the instantiation time predicted given variable load intensities, fault frequencies, multiplexing abilities, and instantiation processing delays. A case study based on a real-world campus cloud is carried out to show the correctness of the proposed theoretical model.
Preparation of Cellulose Acetate Fibers Loaded with Naproxen Ester Prodrug through Wet-Spinning

Cellulose acetate (CA) fibers loaded with naproxen ester prodrug, naproxen methyl ester, were prepared through a wet-spinning technique by using N, N-dimethylacetamide (DMAc) as a solvent. The chemical and morphological characterizations of the medicated fibers were investigated by means of scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR), as well as the studies of the drug release properties. It was observed that the surface and the cross section of the fibers were quite smooth and cylindrical respectively, whereas microcracks were present on the surface of the fibers. Naproxen methyl ester was successfully encapsulated into a monofilament fiber, and this system was stable in terms of high loading capacity and effectiveness in release. The in vitro release experiment indicated that constant drug release from the fiber was observed for a long duration of time. These findings demonstrate that controlled release of drugs from cellulose acetate fibers could be potentially useful in drug delivery systems.
Global supply chain equilibrium network dynamics with stochastic exchange rate volatility

Fluctuant exchange rate has impact on global supply chain network equilibrium transactions. In this paper, by modeling various fluctuation trends of exchange rate, different exchange rate levels are used to characterize the advantageous or disadvantageous influence on transaction costs and risks between every pair of decision-makers, which is more practical for real-life global supply chain scenarios. Based on the idea of network integration, a global supply chain network equilibrium model with stochastic exchange rate volatility can be transformed into a supernetwork that integrates a supply chain transaction network with a currency network. With a two-stage prediction-correction method, we perform numerical simulation and sensitivity analysis to demonstrate the effectiveness of our equilibrium model.
Modeling and Control of Piezo-Actuated Nanopositioning Stages: A Survey

Piezo-actuated stages have become more and more promising in nanopositioning applications due to the excellent advantages of the fast response time, large mechanical force, and extremely fine resolution. Modeling and control are critical to achieve objectives for high-precision motion. However, piezo-actuated stages themselves suffer from the inherent drawbacks produced by the inherent creep and hysteresis nonlinearities and vibration caused by the lightly damped resonant dynamics, which make modeling and control of such systems challenging. To address these challenges, various techniques have been reported in the literature. This paper surveys and discusses the progresses of different modeling and control approaches for piezo-actuated nanopositioning stages and highlights new opportunities for the extended studies.
Embedded Image Compression Using Differential Coding and Optimization Method

Embedded zerotree (EZW) and SPIHT coding, introduced by J.M.Shapiro and Amir Said, are very effective and being used in many fields widely. Embedded zero-tree wavelet encoding is currently the most advanced image coding methods, In this paper, brief explanation of the principles of SPIHT was first provided, and then, some improvement of SPIHT algorithm according to experiments was introduced. For redundancy among the coefficients in the wavelet-region, we propose differential method to reduce it during coding. Meanwhile, In the uniform quantization of wavelet coefficients, the sub-band depending on the context of modeling the probability of the statistical characteristics based on characteristic of the coefficients' distribution in sub-band, we adjust sorting pass and optimize differential process, in order to reduce the redundancy coding in each sub-band. The image coding result, calculated by certain threshold, showing that through differential optimization, the rate of compression get higher, and quality of reconstructed image have been get raised greatly, when bpp=0.5, PSNR of reconstructed image exceeds that of SPIHT by 0.07~0.12db.
Distribution characteristics and performance simulations of rain attenuation at Ka band for satellite communications

In satellite communication system, rain attenuation is one of the most important reasons for the signal fading transmitted at Ka band (30/20GHz). In this paper, based on the ITU recommendation rainfall attenuation prediction model, we obtain the rainfall attenuation value of one specific area in satellite communication systems at Ka band, in premise of knowing that rain attenuation value of a certain area follows lognormal distribution, then statistical distribution parameters are derived in detail by a method of the least squares curve fitting. After QPSK modulation, signal is polluted by additive noise in AWGN channel. We analyze and simulate the effect of light rain and heavy rain on signal propagation. The simulation results indicate that rain attenuation makes the signal-to-noise ratio and the bit error rate worse.
A modified visual simulation method based on LOD

LOD visual simulation method which can make battle-simulation visualization, is an important method for building view-scene model. In this paper, a modified visual simulation method based on LOD is proposed. The master idea is generating initial triangle grids for view-scene using LOD method, and subdividing them using iterative fractal technology. The method not only resolves visual transition problem for different detail regions, and gets more vivid 3D view-scene by means of visual rendering, but also improving the capability of view simulation system in total. Simulation result shows the improvement performance is 3.86%.the result has been important military value in battle command.
A Pricing Strategy Model Based on Economy Theory in Mobile Grids

Millions of laptops ,PDAs and other mobile devices remain unused most of the time and this huge resource repository can be potentially utilized in the Grid environment. We are working on a system for constructing a auction-bargaining theoretic pricing model to address load balancing and optimization issues in mobile grids. In the model, first a auction protocol is to select the cheapest one among n mobile devices and then a two player alternating-offer bargaining game between the wireless Access Point Server (APS) and the cheapest mobile device to determine the pricing strategy which is then maximizing the profits and minimizing the costs of data resource management. In this paper we give an overview of our model and present some evaluation required to support this desired marketplace interaction model.
An Efficient Parallel Implementation for Three-Dimensional Incompressible Pipe Flow Based on SIMPLE

SIMPLE (Semi-Implicit Method for Pressure-Linked Equations) algorithm is important in the simulation of steady flows. As the traditional 3-D SIMPLE algorithm is time-consuming, we propose a parallel SIMPLE algorithm based on a novel tiling strategy -- alternate tiling, through replacing the original linear system and reordering the iteration space tiles. The novelty of our parallel algorithm lies in the introduction of the sequence of iteration space tiles as the sequence of execution, the time skewing technique to partition the iteration space, update operations of the grids from two directions alternately, and the improvement of the data locality. The effectiveness of the parallel algorithm and serial model of finite difference stencil algorithm are validated. Numerical experiments on distributed clusters show that the cache misses and the cost of communication and synchronization are reduced by reordering the tiles of iteration space, and the parallel SIMPLE algorithm based on alternate tiling has a good data locality and parallel efficiency in the three-dimensional incompressible pipe flow project.
Complementary hashing for approximate nearest neighbor search

Recently, hashing based Approximate Nearest Neighbor (ANN) techniques have been attracting lots of attention in computer vision. The data-dependent hashing methods, e.g., Spectral Hashing, expects better performance than the data-blind counterparts, e.g., Locality Sensitive Hashing (LSH). However, most data-dependent hashing methods only employ a single hash table. When higher recall is desired, they have to retrieve exponentially growing number of hash buckets around the bucket containing the query, which may drag down the precision rapidly. In this paper, we propose a so-called complementary hashing approach, which is able to balance the precision and recall in a more effective way. The key idea is to employ multiple complementary hash tables, which are learned sequentially in a boosting manner, so that, given a query, its true nearest neighbors missed from the active bucket of one hash table are more likely to be found in the active bucket of the next hash table. Compared with LSH that also can exploit multiple hash tables, our approach is more effective to find true NNs, thanks to the complementarity property of the hash tables from our approach. Experimental results on large scale ANN search show that the proposed method significantly improves the performance and outperforms the state-of-the-art.
Statistical Weight Kinetics Modeling and Estimation for Silica Nanowire Growth Catalyzed by Pd Thin Film

This work intends to understand and model the kinetic aspect or the change of substrate weight over time in the selective growth of silica nanowires (NWs) catalyzed through Pd thin film. Various adsorption-induced, diffusion-induced, or unified vapor-liquid-solid (VLS) growth models have been developed to describe the NW length varying with time. Since NW length has been difficult to be measured, substrate weight change is therefore used as an alternative in this study to investigate growth kinetics of NWs. We investigate six different weight kinetics models in predicting weight changes during growth. Model estimation and comparison are conducted using both maximum-likelihood estimation (MLE) and Bayesian approaches. Owing to the embedded kinetics information in the nonlinear growth models, the Bayesian hierarchical model is shown to be more desirable when process data is limited.
Chinese firms' R&D “Going Out”: Determinants for location choice

Based on a dataset on 1500 Chinese firms, which established overseas R&D subsidiaries in the recent 5 years (2010–2014), we investigate the development trends of the Chinese firms' overseas R&D investment, whether and how it differs from the overseas R&D investment peak led by the Multinational Corporations (MNCs) in the developed countries in the past century. Drawing on Dunning's eclectic paradigm, we establish a theoretical framework: the locational advantage of host countries are analyzed in their effect on Chinese firms' establishment of overseas R&D subsidiaries. We also consider how the interaction between the host countries and China, which consists of geographic and cultural distance, moderate the relations between the host countries' advantages and Chinese firms' locational choice, integrating Uppsala model and Geert Hofstede's National Cultural theory into Dunning's eclectic paradigm. A dataset consisting 49 representative host countries and the multiple regression method are employed to test the related hypothesis. We find that the Chinese firms' R&D “Going Out” is strongly oriented by the overseas market; although the “knowledge seeking” is also a major incentive, this orientation is comparatively less strong, and is further weakened by the barriers created by geographic and cultural distance.
Robust control for uncertain T-S systems with Pre-specified sector regional pole constraints

In this paper, the design of a global state feedback controller is designed for a class of uncertain T-S fuzzy systems by means of parallel distributed compensator technique and linear matrix inequality technique. The pole of closed-loop system can be placed in a Pre-specified sector region so that the systems satisfy prescribed dynamic performance. At last the existent conditions of solution are expressed via LMI. So the feedback gain matrix can be obtained easily by solving the LMI. The example shows that the method is feasible and effective.
Forest hashing: Expediting large scale image retrieval

This paper introduces a hybrid method for searching large image datasets for approximate nearest neighbor items, specifically SIFT descriptors. The basic idea behind our method is to create a serial system that first partitions approximate nearest neighbors using multiple kd-trees before calling upon locally designed spectral hashing tables for retrieval. This combination gives us the local approximate nearest neighbor accuracy of kd-trees with the computational efficiency of hashing techniques. Experimental results show that our approach efficiently and accurately outperforms previous methods designed to achieve similar goals.
Improving the Stability of Cellulase by Immobilization on Chitosan-Coated Magnetic Nanoparticles Modified alpha-Ketoglutaric Acid

The application of cellulases in various industries demands highly stable enzymes, able to perform at extreme pH values and temperatures. In this study, the cellulase, which was immobilized on the chitosan-coated magnetic nanoparticles modified with alpha-ketoglutaric acid (alpha-KA-CCMNPs), exhibited a broader pH range of high activity and the loss of the activity of immobilized cellulase was lower than that of free cellulase. And the optimal temperature for immobilized cellulase was 50degC, whereas that for free cellulase was 40degC. Meanwhile, the immobilized cellulase showed better thermal stability than free cellulase at high temperature range. In addition, the storage stability of the cellulase was improved greatly after it was immobilized on the surface of alpha-KA-CCMNPs.
Research on Ontology Matching Method Based on Description Logics Reasoning Mechanism

Nowadays the utility of domain ontologies is widely acknowledged in many area, such as information systems¿software engineer¿natrue language processing¿artificial intelligence¿electronic commerce and so on. Ontologies are enable to fulfill knowledge appearance, information retrieval and search. However, there still exists several drawbacks that must be resolved before ontologies become practical and useful tools. A critical issue is the ontology mapping. This matching process will directly influence the precision and recall of information retrieval among several different ontologies. In this paper, we propose an approach of ontology matching and an ontology matching algorithm based on description logic system through analyzing the characteristic of description logics, including definitions of syntax, semantics and basic reasoning services. and finally demonstrate the practicality of this ontology matching method between two concrete Book-System ontologies.
Selective paging schemes for LEO satellite network based on dynamic location area

Location management is one of the key points of movement management in low orbit satellite. Comparing with static location area, dynamic location area can reduce the cost of movement management, which is determined by the characteristic of user movement. In fact, each user only keeps two counters, one is the distance moved and another is the time passed. A location update is performed when this counter exceeds a predefined threshold value. Selective paging strategy is an optimized one which can significantly reduce the paging cost and time delay. In this paper, we propose 3 different selective paging strategies and compare these strategies by analysis and simulation.
Study of transmission effects of millimeter wave through fog and haze

With the decline in air quality, China has frequently appeared foggy and hazy weather. It would have a negligible impact on the detection performance of millimeter wave systems. In this paper, the physical characteristics of fog and haze are discussed in detail. The mechanism of millimeter wave attenuation through fog and haze will be introduced as well. Calculation model of fog scattering and atmospheric absorption attenuation during millimeter wave propagation are established in this paper. Based on the above analysis, it works out the total attenuation consists of the haze scattering and atmospheric absorption, and further analysis the performance of the millimeter-wave systems working at non-atmospheric windows emphatically. The result shows that it has superior anti-reconnaissance performance and anti-jamming performance at non-atmospheric windows.
Supervised Learning of Motion Style for Real-time Synthesis of 3D Character Animations

In this paper, we present a supervised learning framework to learn a probabilistic mapping from values of a low-dimensional style variable, which defines the characteristics of a certain kind of 3D human motion such as walking or boxing, to high-dimensional vectors defining 3D poses. All possible values of the style variable span an Euclidean space called style space. The supervised learning framework guarantees that each dimension of style space corresponds to a certain aspect of the motion characteristics, such as body height and pace length, so the user can precisely define a 3D pose by locating a point in the style space. Moreover, every curve in the Euclidean style space corresponds to a smooth motion sequence. We developed a graphical user interface program, with which, users simply points mouse cursor in the style space to define a 3D pose and drags mouse cursor to synthesis 3D animations in real-time.
Understanding users' continuance intention in online social networks

This study explores users' continuance intention in online social network by synthesizing Bhattacherjee's IS continuance theory as basis with flow theory, the unified theory of acceptance and use of technology (UTAUT), and social capital theory. The integrated model was empirically tested with 260 online social network users. The results indicate that all hypothesized paths are supported by our data. Based on the research findings, we offer discussions.
EOQ and Optimal Credit Time Under Conditions of Permissible Delay in Payments

This paper analyzes a simple supply chain consisting of a retailer and a supplier, the latter permits the former a certain fixed period to settle the amount owed to him for the items supplied. Many researches have developed various economic order quantity (EOQ) for the retailer under the assumption that the resale price is equal to the wholesale price. We establish the retailer's EOQ model when considering the difference between the resale price and the wholesale price. We then characterize the optimal credit time for the supplier under these conditions.
Fractional lower order statistics based generalized constant modulus algorithm for blind multi-user detection in DS/CDMA systems

Blind adaptive multi-user detection (MUD) is one of the key technologies in CDMA systems, and there are lots of optimal and suboptimal detection algorithms during which constant modulus algorithm (CMA) is widely used. All these existing detection algorithms are based on the assumption of Gaussian ambient channel noise, however, more and more researches in recent years show that the actual ambient noise is non-Gaussian distributed. So it is necessary to investigate the problem of multi-user detection in the environment of non-Gaussian noise. While α-stable distribution is a typical statistical model of non-Gaussian signal, its fractional lower order statistics (FLOS) theory is a useful tool in non-Gaussian signal processing. Motivated by the above reasons, we propose a FLOS based generalized constant modulus algorithm (FLOS-GCMA). FLOS-CM algorithm which has been proposed by some researchers for blind equalization can also be used for blind multi-user detection and FLOS-CM algorithm is a special case of FLOS-GCMA. Theoretical analysis and simulation results show that FLOS-GCMA can effectively suppress the non-Gaussian noise.
Weighted Network Evolution with Transfer Behavior

This paper presents a general model of weighted networks evolution in which the structural growth and weight dynamics are both induced by transfer behavior which is an obvious and important phenomenon in technological networks and social networks, e.g. passengers often transfer from a third airport instead of flying directly to the destination in airline networks. In this model we assume at each time step there emerges a new node with m destinations. The new node either connects the destination directly with the probability p or transfers from a third node with the probability 1-p. The analytical result shows degree, weight and strength all obey power-law distribution with the exponent depending on the parameter p. The clustering coefficient and degree assortatively coefficient are high under small p indicating transfer behavior contributes to clusters formation and hierarchal structures.
Low delay MPEG DASH streaming over the WebRTC data channel

Dynamic Adaptive Streaming over HTTP (MPEG-DASH) is becoming the de-facto data format and streaming solution for over-the-top (OTT) video on-demand streaming. The underlying HTTP transport has its limitations and known penalties in slow start, under-utilization, and other inefficiency. An alternate approach to DASH is the new transport schemes like HTTP/2.0 and WebSocket. In this work, we explore WebRTC as a streaming transport to carry DASH data and demonstrate that it is competitive in serving low delay streaming applications with fast channel switching, with proper video data coding and streaming signaling/control solutions.
Design of microstrip mini-antenna on X-band

In order to meet the calibration of the TT&C system on X-band, the corresponding beacon antenna needs to be designed. According to the requirement of antenna design, the high-order mode microstrip antenna is used for the design. By simulation and optimization of the HFSS, miniaturization antenna structure requirements have been met. The antenna is designed with light weight, low profile, low cost, easy to manufacture packaging and so on. After testing antenna meet the design requirements.