nils-herrmann/clean_scirepeval huggingface dataset:
The analysis of the spatial pattern of prehistoric settlement sites based on GIS and spatial data mining

The spatial pattern of prehistoric settlement sites in Henan Province is researched. By analyzing the relationship between prehistoric settlement sites location and regional altitude, terrain slope, rivers and other geographical environment factors, the laws of the distribution of prehistoric settlement sites are found: more than 70% of settlement sites are located at the altitude of from 50 to 400 meters, more than 60% settlement sites are located in the places where the slopes are less than 3 degree, and more than 60% are located in the distance of less than 4km from the river. Through the analysis of settlement sites distribution patterns by using geography information system(GIS) and spatial data mining, the good technology support is provided for the future settlement archaeology, and the references are provided for researchers to understand prehistoric human selection strategy on the environment and the evolution of settlement systems.
The influencing factor analysis of water-saving irrigation technology adopted by farmer: A case study in Heilongjiang

Within the context of increasingly scarce water resources, improving the utilization rate of irrigation water on protecting food safety problems plays an important role. On the basis of the survey data of 364 farmers in Heilongjiang Province, this paper used the cumulative logit model to analyze the factors influencing water-saving irrigation technologies, and the results showed that: the relation among factors such as education level, cultivated area, the proportion of crop income, government support etc. has a positive correlation. Therefore, the water-saving irrigation technology may be properly promoted and implemented if the educational level of farmers is raised, the government subsidies for irrigation technology are increased and the farmers cultivated scale is expanded.
A Hybrid Immune Evolutionary Algorithm for Global Optimization Search

Optimization is an important issue in many kinds of application areas, whereas expediting optimizing process and jumping out of the local optimums are keys in optimization researches. This article presents an immune evolutionary algorithm for optimizing search in continuous space. The proposed algorithm adopts immune network model & evolutionary strategy, adjusts self-adaptively the metrics of evolutionary space on immune affinity, such as the evolutionary steps and directions. The algorithm realizes search diversity by restraining most individuals within one immune shape-space measured in restrain radius. The experimental results on multimodal functions show that the proposed algorithm got the whole optimal solutions and a lot of suboptimal ones in lesser amount of evolutionary generations and minor populations compared with the contrasted algorithms, such as CSA, GA and aiNet, and the effect of global optimizing capability are verified with excellent population diversity.
Learning in an Ambient Intelligent World: Enabling Technologies and Practices

The rapid evolution of information and communication technology opens a wide spectrum of opportunities to change our surroundings into an Ambient Intelligent (AmI) world. AmI is a vision of future information society, where people are surrounded by a digital environment that is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user friendliness, user empowerment, and more effective service support, with an aim to bring information and communication technology to everyone, every home, every business, and every school, thus improving the quality of human life. AmI unprecedentedly enhances learning experiences by endowing the users with the opportunities of learning in context, a breakthrough from the traditional education settings. In this survey paper, we examine some major characteristics of an AmI learning environment. To deliver a feasible and effective solution to ambient learning, we overview a few latest developed enabling technologies in context awareness and interactive learning. Associated practices are meanwhile reported. We also describe our experience in designing and implementing a smart class prototype, which allows teachers to simultaneously instruct both local and remote students in a context-aware and natural way.
Multimedia multicast service provisioning in cognitive radio networks

In this paper, we propose a design framework for achieving efficient multimedia multicast services in cognitive radio (CR) networks. The framework incorporates the characteristics of both heterogeneous network environment and the scalable video content. By adopting cooperative transmissions for the delivery of enhancement layer data, we can not only improve the achieved video quality but also protect the rights of subscribed secondary users. We also utilize network coding and superposition coding to achieve efficient multicast transmissions of the layered video packets in multi-channel CR networks. Numerical examples show the proposed framework can improve the average received data rate by up to 15%. When achieving the same video quality, the proposed framework can save 30% transmission time comparing with the scenario using direct transmission alone.
Joint Source Coding and Data Rate Adaptation for Multi-User Wireless Video Transmission

Much attention has been paid to the problem of optimally utilizing resources such as spectrum, power and time in order to achieve the best video delivery quality in wireless communications system, due to the fueling demand for such applications. In this work, we present a joint source coding and data adaptation scheme for downlink video transmission in a multi-user wireless network. We formulate a rate-distortion optimization problem, where the source coding and data rate are jointly designed according to the changing channel conditions. In addition, transmissions of video packets are optimally scheduled through exploiting the multi-user diversity. We solve the problem using a backward stochastic dynamical programming approach, and the simulation results have shown the advantage of the joint selection of source coding parameter and transmission rate coupled with optimal packet scheduling.
Stochastic Security Performance of Active Cache Based Defense against DoS Attacks in Wireless Mesh Network

Due to its wireless multi-hop feature, Wireless Mesh Network (WMN)is prone to suffer from many attacks, such as Denial of Service attack(DoS). In the DoS attack, when extortionate high-load flows flood to individual Mesh Routers (MR), they can no longer provide normal services to innocent flows. An active cache based defense solution can detect the existence of attacking flows based on thefrequency of incoming packets and eliminate the attacking flows by discarding packets by a Drop Probability(DP). As shown in our simulation study, the selection and variance of DP have a significant impact on the performance of the defense solution to both attacking flows and innocent flows. In this paper, a series of DP selection and variance methods are employed in our simulation studies. From them, we can optimize the DP methods and correspondingparameter setting of the solution against Dos attack by the analysis on the simulation results.
Long-Wavelength Tunable Detector Using High-Contrast Grating

We report a tunable 1550-nm detector using a monolithic high-contrast grating (HCG) vertical-cavity surface-emitting laser. The detector is resonance enhanced, with a responsivity demonstrated as large as 1 A/W. It features a strong wavelength selectivity over a wide tuning range, enabled by the highly reflective microelectromechanically actutable HCG mirror. A tuning range of 33.5 nm and a spectral width of 1.2 nm are demonstrated. We show that it can select a specific data channel with 1 Gb/s data rate and reject adjacent channels 4 nm away. Higher detection speed at 10 Gb/s is also demonstrated. We show three special functionalities of this tunable detector. The first one is dual functionality-not only as a receiver but also a transmitter-with a simple change of its bias polarity. Though long sought after, a tunable bifunctional device had not been realized before. An error-free high-speed link over 25 km single-mode-fiber is demonstrated between two such devices. The second special property is its wavelength-self-tracking configuration, i.e., its resonance wavelength can automatically track the input light's wavelength. Finally, we demonstrate its use as a fast on-chip optical spectrometer, with an operation speed at 200 kHz. This tunable detector would be useful for a variety of wavelength-division-multiplexing network and lab-on-a-chip systems.
Ethernet-Broadcasting-Based Distributed Load Balancing Technology of Server Cluster

The common method to solve performance bottleneck problems of network service nodes is to take use of server cluster systems. At present, the schema which uses centralized load balancer to do management of system load is dominant. But the load balancer used may become a bottleneck of the system. This paper first analyzes and compares the existing load balancing technologies, and then proposes the Ethernet-broadcasting-based distributed load balancing technology.
Power grid vulnerability assement based on energy function

The traditional certainty assessment method of the power system security is difficult to consider its randomness, at the same time it is difficult to provide the safe and health realtime information of power network quantitatively and intuitively. In this paper, the traditional concept of security of the power system is expanded and network vulnerability is introduced. Considering the probability of contingency, transient energy function method is adopted, the indicators of power system vulnerability and thresholds are given. Power system is evaluated in the context of transient security. A large amount of time is saved while the correctness of security analysis is ensured. The rationality and effectiveness of the proposed method is verified by the results of calculation results.
The security deployment of early IMS

3GPP IP multimedia subsystem (IMS) provides IP-based session control capabilities based on the SIP protocol. Although full support to 3GPP TS 33.203 security features is preferred from a security perspective, it is acknowledged that early IMS implementations exists which do not support these features. 3GPP TR 33.978 define some security mechanisms to protect early IMS, but there are still some security issues, e.g. the signaling security, roaming security, NAT and interworking, which need to be resolved in the deployment of early IMS. This paper presents a new deployment of early IMS which focus on the security from the access network to the core network
Video Summarization and Transmission Power Adaptation for Very Low Bit Rate Multiuser Wireless Uplink Video Communication

In this paper we consider the problem of efficiently serving multiple uplink video users in a wideband CDMA wireless communication system with mixed voice and video traffic. Very low available video bit rate (<64 kpbs) and multi-user interference are the major limiting factors in the system performance. Our solution is based on video summarization to achieve reasonable video quality at very low bit rate, and multi-user transmission adaptation/scheduling via summarization distortion-rate profile negotiation between base station and mobiles to meet power control constraints and minimize the interference among voice/video users. The simulation results demonstrate the effectiveness of the proposed approach
Cascade of Box (CABOX) Filters for Optimal Scale Space Approximation

Local image features, such as blobs and corners, have proven to be very useful for several computer vision applications. However, for enabling applications such as visual search and augmented reality with near-realtime latency, blob detection can be quite computationally expensive due to numerous convolution operations. In this paper, we present a sparse convex formulation to determine a minimal set of box filters for fast yet robust approximation to the Gaussian kernels used for blob detection. We call our feature detector as CABOX (CAscade of BOX) detector. Although box approximations to a filter have been studied in the literature, previous approaches suffer from one or more of the following problems: 1) ad hoc box filter design, 2) non-elegant trade-off between filter reconstruction quality and speed and, 3) limited experimental evaluation considering very small datasets. This paper, on the other hand, contributes: 1) an elegant optimization approach to determine an optimal sparse set of box filters, and 2) a comprehensive experimental evaluation including a large scale image matching experiment with about 16 K matching and 170 K non-matching image pairs. Our experimental results show a substantial overlap (89%) between the features detected with our proposed method and the popular Difference-of-Gaussian (DoG) approach. And yet CABOX is 44% faster. Moreover, the large scale experiment shows that CABOX closely reproduces DoG's performance in an end-to-end feature detection and matching pipeline.
Regional Logistics Network Design Problem under the Constraints of Contours of Delivery Time

From investigating the relationship of the size of regional foreign direct invest (FDI) to their accessibility to the main seaports by railway or highway, it is proved that the logistics play a significant impact on regional industry competition. From the point of modern logistics view, the basic regional logistics service system constitutes the fundamental environment of investment. The concept of freight just in time delivery covering circles is defined in this paper. Then a regional logistics network design problem under the constraints of contours of delivery time within the research area is developed together with the generalized method for solving its optimal solution. This model can be used to construct a comprehensively new regional logistics network that will lead to a stronger regional competition and greater exaltation of location advantages.
Visual query compression with embedded transforms on Grassmann manifold

This paper proposes a novel approach for visual query compression with a bank of transforms selected on Grassmann manifold. Instead of using single transform and quantization pipeline for all the features extracted from an image, we group the key point features according to their local embedding subspace geometry and organize them into different leaf nodes of a KD-Tree which was built from a large dataset. We introduce a new method to find the optimal local transforms on Grassmann manifold such that each feature can achieve the best energy compaction possible given the rate-distortion constraint. Experiments results demonstrated that the proposed method outperforms global transform in both reconstruction error and visual query accuracy, especially in high compression ratio circumstances.
Adaptive Fast Inter Mode Decision for Wireless Video Applications Using H.264/AVC

In this paper, we proposed an adaptive fast inter mode decision algorithm to reduce the computation complexity of H.264/AVC encoder. It makes use of spatio-temporal correlation to filter out unlikely modes. Instead of performing all the seven inter prediction modes, only part of them are chosen for motion estimation and rate distortion optimization (RDO) procedure. Adopting a dynamic adjusted threshold makes the proposed method work well in different bit-rate conditions, especially in low bit-rate. Experimental results indicate that the proposed algorithm can achieve 23% time saving in inter mode decision on average while maintaining the similar rate distortion performance
Research on the Key Agreement and Authentication of Cognitive Radio Networks

Identity authentication is one of the key problems to be solved in cognitive radio networks. Current authentication mechanisms for cognitive radio networks are based on PPP Extensible Authentication Protocols. Future cognitive radio network can fusion current wireless standards. However, security requirements of various wireless standards are different which leads to current authentication mechanisms are not suitable for cognitive radio networks. Therefore, an identity authentication mechanism based on Certification Authority (CA) is proposed in this paper. The mechanism adopts SIM authentication for terminal users and secure tunnel +certificates for servers. CA can resolve identity authentication problem of base station, assure security of base station and CA by secure tunnel in core networks. And current Challenge Handshake Protocol is also improved; challenge handshake exists in whole communication process which resolves connection robbing problem.
Enzymatic Synthesis and Study of Novel Ester of Ferulic Acid as a Novel Anti-Carcinogenesis Agent with Free Radical Scavenging Properties

A facile enzymatic synthesis approach to prepare novel ester of ferulic acid through the lipase-catalyzed transesterification reaction of ethyl ferulate (EF) with tributyrin (TB) was investigated. The 1 H NMR, 13 C NMR and EI-MS analysis confirmed the formation of the end product, namely 1(3)-feruloyl-dibutyryl-glycerol (FDB). The influences of different enzyme source, enzyme loading, and water activity on the conversion yield were analyzed systematically. Under the optimal conditions, the total conversion of FDB achieved was 83.6%. There was no evident loss in lipase activity and stability after being repeatedly used for 14 runs. The study of radical scavenging activity of feruloylated structured lipids, with over 90% of radical 2,2-diphenyl-1-picryhydrazyl (DPPH-) scavenging, was found to be higher than ferulic acid.
Spatial and temporal distribution variation and meteorological factors analyzing of algal blooms based on HJ-1 satellites in Lake Dianchi, China, 2009

this paper described an approach used HJ-1 CCD data to monitor algal blooms in Lake Dianchi, China. After the radiometric calibration, atmospheric correction and geometric correction, HJ-1CCD reflectance data were obtained and NDVI threshold values were chosen to separate the bloom and nonbloom water. 148 HJ-1 CCD images were used in which 66 effective images were chosen to monitor algal blooms of Lake Dianchi. 39 times of algal blooms occurred in 2009 and only one time algal bloom area is greater than 15 square kilometers. The algal bloom annual frequency and bloom initial date were analyzed. The paper summarized that the bloom areas in Lake Dianchi are mainly located in northern lake and Caohai, the bloom began on March and ended on December, the most frequency bloom region is northern lake, and the most serious bloom month is September and October.
Design of a decoupled 2-DOF translational parallel micro-positioning stage

In this paper, a new type of decoupled 2-DOF translational parallel micro-positioning stage is designed to realize the 2-DOF ultra-precision linear motion. The stage consists of two piezoelectric actuators (PZTs) and a monolithic compliant mechanism. The monolithic compliant mechanism adopts two types of compound double parallel four-leaf flexures and a mirror symmetric structure to reduce the input and output cross coupling and parasitic motion. Based on the stiffness matrix method and screw theory, a mathematical model is constructed to analyze the compliant mechanism. The optimal design is performed in view of performance constraints. The design results show good static and dynamic performances of the stage, which are well validated by the simulation of finite-element-analysis (FEA) and experimental results. The experimental results show that the proposed stage has a full range of 40µm × 40µm when the full voltage(100V) is applied on the two PZTs. Besides, the stage only has the maximum cross coupling of -50dB between the two axes, low enough to utilize single-input-single-out(SISO) control strategies for positioning and tracking.
Laplacian Affinity Propagation for Semi-Supervised Object Classification

We solve the semi-supervised multi-class object classification problem by a graph-based learning algorithm, called Laplacian affinity propagation (LAP). The idea is to model and train both labeled and unlabeled data by constructing a local neighborhood affinity graph in a smoothness formulation of Laplacian matrix, based on graph mincuts or harmonic energy minimization. The unknown labels for unlabeled data are inferred from an optimized graph embedding procedure subject to the labeled data. Such label-to-unlabel propagation scheme can provide a closed form solution via a learning framework that is flexible for any new design. LAP integrates embedding and classifier together and gives smooth labels with respect to the underlying manifold structure formed by the training data. Object classification experiments on COIL database demonstrate the effectiveness and applicability of such algorithm.
Availability Improvement for WLAN-Based Train-Ground Communication Systems in Communication-Based Train Control (CBTC)

Train-ground communication technology is one of the key technologies for communication-based train control (CBTC), which is an automated train control system for railways that ensures safe operation of rail vehicles using data communications. In CBTC systems, less service availability could cause train derailment, collision or even catastrophic loss of lives or assets. Therefore, the availability of train-ground communication should be carefully considered in designing CBTC systems. In this paper, we propose two WLAN-based train-ground communication schemes with redundancy to improve the availability in CBTC systems. The availability is analyzed using continuous time Markov chain (CTMC) model. Numerical examples illustrate that the proposed schemes with redundancy can significantly improve the availability of WLAN-based train-ground communication in CBTC systems.
Anti-collision algorithm based on the regressive-style RFID of BIBD (4,2,1)

This paper discusses the anti-collision algorithm that can simultaneously identify multiple tags in the RFID system, and analyses the characteristics of two types of anti-collision algorithm: BIBD (4,2,1) and the binary tree. Then we advance a novel and fast anti-collision algorithm based on the regressive-style RFID of BIBD ( 4,2,1). Not only does this anti-collision algorithm methodology have the advantages of BIBD algorithm, but it can also significantly reduce the query time. In this algorithm, segment the labels, and each contains only a subset of BIBD (4,2,1). It will quickly identify tags through return and by-section reading. The results of mathematical analysis and simulating show that the recognition speed of this algorithm is superior to the binary algorithm and dynamic binary algorithm, and it is applicable to the identifying situations of multiple tags and longer UID.
Research on the distance equation of the submillimeter radiometer via Lambert W function

This paper put forward the distance equation for the SMMW radiometer based on the one for the MMW radiometer. In general case, the transmission attenuation was ignored as the detection distance of the radiometer was studied, because of the faint attenuation in some frequency band. But in the SMMW band, the effects of atmospheric attenuation were very significant. So the attenuation coefficient had been introduced into the distance equation. Then the solution of the equation was proposed by using the Lambert W, which is a transcendental function. Finally the simulation and analysis of the solution were given respectively.