nils-herrmann/clean_scirepeval huggingface dataset:
Phase characteristics of a new element for design of a single-layer microstrip reflectarray

The microstrip reflectarray is composed of each phase-shifting element, so the ability of the element greatly affects the capability of the microstrip reflectarray. In this paper, we put forward a new single-layer phase-shifting element which is developed from the crossed-dipole, and then we do investigations into the phase characteristics of the new element structure using the equivalent waveguide approach method. The simulation results show that the new element can offer a slow phase slope while the phase rang is over 360°.
Extension of fuzzy c-means algorithm

Clustering is a procedure through which objects are distinguished or classified in accordance with their similarity. The fuzzy c-means method (FCM) is one of the most popular clustering methods based on minimization of a criterion function. However, the FCM method is sensitive to the presence of noise and outliers in data. This paper introduces a new clustering algorithm by extending the criterion function. As a special case, this algorithm includes the well-known fuzzy c-means method. Performance of the new clustering algorithm is experimentally compared with the FCM method using synthetic data with different clusters and outliers.
A Lagrangian formulation of Zador's entropy-constrained quantization theorem

Zador's (1963, 1966) classic result for the asymptotic high-rate behavior of entropy-constrained vector quantization is recast in a Lagrangian form which better matches the Lloyd algorithm used to optimize such quantizers. The equivalence of the two formulations is shown and the result is proved for source distributions that are absolutely continuous with respect to the Lebesgue measure which satisfy an entropy condition, thereby generalizing the conditions stated by Zador under which the result holds.
Excessive reaction, noise and asset price bubble

According to the actual situation in Chinese stock market, under the hypothesis condition that noise traders have excessive reaction, this paper studies the influence mechanism of noise traders and their excessive reaction to the asset price bubble by Setting up the stock market risk asset pricing models and the asset price bubble. The research results show that noise trader cognitive deviation and its proportion to asset price bubble formation are positive correlation. And the noise trader excessive reaction to asset price bubbles effects are not the same. When the noise traders have excessive reaction on the dividend of mean value, the influence on excessive reaction to asset price bubbles is very limited, but not to further expansion impact of the asset bubble. In contrast, when excessive reaction expand to a certain degree, excessive reaction restrain the bubbles rise. When the noise traders have excessive response on the mean of cognitive dividend mean, noise traders excessive reaction to asset price bubble was a significant positive correlation.
Compact UWB bandpass filter with triple notched bands using parallel U-shaped defected microstrip structure

A novel compact ultra-wideband (UWB) bandpass filter (BPF) with triple sharply notched bands and good selectivity is proposed using a parallel U-shaped defected microstrip structure (UDMS). The initial UWB BPF comprises interdigital coupled lines and an E-shaped multiple-mode resonator to achieve two transmission zeros on both sides of the passband, thus improving skirt selectivity. Then, three parallel UDMSs are introduced, which have the properties of achieving the triple band-notched characteristics and providing a high degree of adjusting freedom. To validate the design theory, a microstrip UWB BPF with three notched bands centred at 5.2, 5.8 and 8.0 GHz, respectively, is designed and fabricated. Both the simulation and the experimental results are provided which have good agreement.
Cuboids detection in RGB-D images via Maximum Weighted Clique

Cuboid detection is an essential step for understanding 3D structure of scenes. As most of indoor scene cuboids are actually objects, we propose in this paper an object-based approach to detect 3D cuboids in indoor RGB-D images. The proposed approach is learning-free and can handle general object classes rather than a limited pre-defined category set. In our approach, we first apply an extended version of the CPMC framework to generate a set of segment hypotheses, and fit a set of cuboid candidates. Given the candidate set, we select several cuboids that can provide plausible interpretations of the images by solving a Maximum Weighted Clique (MWC) problem. With this formulation, a set of ranked mid-level representations of the input image is obtained, and are further re-ranked by Maximal Marginal Relevance (MMR) measure to improve their diversity. Experimental results on NYU-V2 dataset shows that our method significantly outperforms the state-of-the-art, and shows impressive results.
High-Gain Wideband Leaky-Wave Antenna Excited by Bowtie Element

A leaky-wave antenna with wideband and high-gain characteristics, excited by a rhombic bowtie element with round corners, is derived from a rectangular resonant cavity operating in TM111 mode. In the design procedure, a few particular techniques are used to enhance the antenna impedance bandwidth and gain, such as utilization of bowtie exciter and differentially-fed mechanism. The antenna is fed by a coaxial line, and a transition from microstrip line to parallel strip line (PSL) is utilized to achieve a good differentially-fed structure. With a tradeoff between large impedance bandwidth and high gain, the antenna presents an impedance bandwidth of 41.2% for SWR les 2, a gain of 14 dBi and stable unidirectional radiation patterns. For practical applications, the parametric studies and design guideline are given in the end.
Major-auxiliary cooperative two-way relay scheme in the ground wave transmission of high-frequency communication

Due to the high flexibility and the large communication coverage of the high-frequency (HF) communication, it is widely used in the fields of military and civil. In view of the ground wave transmission of HF communication, the paper proposes the major-auxiliary cooperative two-way relay scheme. Its main idea is that adopting the auxiliary relay to assist the major relay for receiving two independent signals, then the major relay may decode-and-forward (DF) the information. Thus the outage performance can be improved. In this paper, we not only analysis the outage probability of the scheme which this paper proposed, but also discuss the effect of power allocation on the outage performance. Theoretical research and simulation results show that the scheme can reduce the outage probability of the ground-wave communication. And the more pairs of relay nodes in the scheme, the outage probability is lower.
DfT optimization for pre-bond testing of 3D-SICs containing TSVs

This paper proposes to provide testability for the breaking point produced by the Through-Silicon-Vias (TSVs) of 3D-Stacked ICs (3D-SICs) during pre-bond testing with low Design-for-Testability (DfT) cost. Different from prior solutions which utilize two additional wrapper cells for the breaking point at each TSV, this paper proposes to provide the testability of two ends of the TSVs respectively by reusing the existing Primary-Inputs (PIs)/ Primary-Outputs (POs) and Pseudo-PIs/Pseudo- POs (PPIs/PPOs). To further reduce the hardware overhead and enhance the efficiency of the proposed method, this paper has also proposed the metrics and algorithm on deciding the selecting order of the TSVs and the PIs/PPIs (POs/PPOs) to be reused. The experimental results on larger ITC'99 benchmark circuits validate the effectiveness of the proposed method.
Parameter estimation of autoregressive processes by solving eigenvalue problem

In this paper, the identification of AR processes whose measurements are corrupted by additive noise is considered. An approach to consistent estimation of AR processes is proposed that is based on solving eigenvalue problem. A nonlinear bias compensation equation (BCE) is derived via forward and backward LS predictors. By theoretical analysis, it becomes clear that unbiased estimate of the AR process is one of eigenvectors of a matrix, which consists of stochastic quantities of the output measurements. A method is presented for choosing the estimate from eigenvectors. The proposed algorithm is a batch processing form, it avoids some existing problems in on-line or iterative algorithms such as stability or convergence problems. Simulation results are given to verify the proposed method.
Neigh-Shrink de-noising based on Bayes-Shrink in monocular visual navigation

In view that the noise of image in monocular visual navigation, a Neigh-Shrink de-noising method based on Bayes-Shrink is proposed. First, the method uses Bayes-Shrink adaptive threshold replace common threshold as the contraction threshold of Neigh-Shrink, and then eliminate the high frequency sub-band of image obtained by monocular visual system after non-subsample Contourlet transform (NSCT) decomposition. Experiment results show that the improved Neigh-Shrink method in de-noising performance and visual effects have been improved, with better anti-noise performance and excellent edge protection, and can effectively be used in monocular visual navigation.
Data Analysis on Health Management Systems for Improving Doctor's Advice on Patients

Health management systems (HMS) have turned health management center into a network with huge storage so that health records, from different kinds of systems in hospital, can be shared. Based on this, variety of information about patients from different function modules can be inquired for further research. However, there is a lot of potential information which may be useful but still remain in original data level. In this paper, we focus on how to integrate heterogeneous data, optimize data features, and make further data analysis on HMS, which can be a significant reference for doctors to give proper advices towards different patients. As an assisted diagnostic method, the relationships about some unknown abnormal items with special diseases can be discovered by analyzing the data based on HMS.
Notice of RetractionResearch on energy performance contracting based on consumer psychology

The energy consumption of buildings from construction to operation accounts for nearly 45% of the total energy consumption, so the energy saving and emission reduction in building field has a long way to go. Taking consumer demand as the starting point combined with current energy consumption and management situation of commercial housing in our country, this article explores ways to realize energy saving and emission reduction effectively by contract energy management in civil building field with the purpose to promote the concept of green consumption and the implementation of green building.
An integrated model predictive control strategy for batch processes

A novel integrated model predictive control (MPC) strategy with model identification for batch processes is proposed in this paper. It systematically integrates batch-axis information and time-axis information into one uniform frame. The control law is obtained through the solution of a MPC optimization with time-varying prediction horizon, which leads to superior tracking performance and robustness against disturbance and uncertainty. Moreover, the model identification with online updated parameter algorithm is employed to eliminate the model-plant mismatch and match the real plant better. Next, the convergence analysis of the proposed integrated model predictive control system is given rigorous description and proof. Lastly, the effectiveness of the proposed method is verified by an example.
Diffusion of Information Technology: An Extension of the Bass Model

Successful diffusion of information technology is the key point for IT firms to gain competitive advantages. Compared with other types of technology, most of information technology is characterized by significant network externalities, coherent cross-product interaction and high knowledge barriers. As the main impetus underlying diffusion modeling methods, the Bass model provides a general framework on depicting the diffusion process of technology while failing to capture the distinctive characteristics of IT innovation diffusion. This paper extends the Bass model by relaxing some assumptions and incorporating into it three additional variables to reflect the natures of IT innovations. Centering on the influence that characteristics of IT innovations exert on the willingness of potential users to adopt new technology, the paper redefines the coefficients of innovators and imitators in the Bass model so that the refined model is tailored to information technology diffusion. At the end of the paper, several implications are obtained from the extended model to give some useful suggestions for IT researchers and practitioners.
High-fidelity data transmission of multi vital signs for distributed e-health applications

Developing a portable e-health system based on mobile devices such as smart phone or iPad etc. to monitor and diagnose cardiovascular diseases (CVDs) easily, timely and flexibly is attractive and flourishing with the benefit of vigorous development of embedded-link technology and e-health. Yet, confronting the numerous CVDs, complicated medical diagnosis and users' increasing requirements, these source-limited portable devices are rather restricted to handle such emerging issues. Thus, a remote backyard on-line support and assistance center in such a distributed e-health system is necessitated to perform instant feedback upon users' help requests. To ensure prompt and reliable communication between thousands mobile devices and support center, fast and accurate multi vital signs transmission using high efficient compression/decompression technique becomes the kernel of success or failure. This paper tackles such a bottleneck problem, presents a versatile and high-fidelity multi vital signs compression method using adaptive Fourier decomposition to decompose signal beat into weighted orthogonal components. An intelligent signal type detection and automatic parameter adjustment scheme is designed and implemented, thus compress different bio-signals with compression ratio (CR) > 5.6 and normalized percentage relative difference (PRDN) <; 7.3%. Validated by transmitting various vital signs, such as electrocardiography (ECG), sphygmography (SPG) and heart sound (HS) signals, the proposed method exhibits universal and robust applicability for multi vital signs and achieves competitive performance compared with prior works, making distributed e-health applications be realistic.
Designing of particle system architecture by using multi-agent modeling

In this paper, we present a new architecture (called multi-agent-particle-system, MAPS) to controlling the running of particle system. The MAPS consisted of external-senor-agent (called ESA, perceive external environment situation such as wind direction, humidity and altitude), initial-particle-agent (called IPA, finishes initial working for particles), update-particle-agent (called UPA, updating properties for particles) and render-particle-agent (called RPA, rendering particles on the displays). Also, the initial parameter can be specified by external command. Making use of the agent, our system is autonomy in that the particle can change attributes on the fly in order to react to the real-time situation. Our approach is also authorable and scalable for users can easily define particle system for different objects simulation. Finally, the objects produced by our system are visually convincing. We demonstrate our architecture with fireworks and fountain simulation.
A predictive controller with self-renewal model observer for continuous sterilization of biochemical process

Continuous sterilization is conducted on medium before fermentation processes, and the aim of sterilization is effective destruction of microorganisms while less that of the fermentable substrate. Problems exist in control process of continuous sterilization for the system variety and strong disturbances, bringing out bad control accuracy and performance of sterilization. In this paper, a predictive controller with self-renewal model observer is proposed to obtain high control accuracy. An approximation model is obtained based on industrial data, and model predictive control strategy is implemented to overcome the bottleneck of complex precise modeling, at the same time guarantee the control accuracy. Besides, a model observer is designed to deal with strong disturbances in industrial conditions. The parameters of the model observer is updated as the sterilization process goes on, so as to follow the system variety well. Simulations are carried out, and results show the effectiveness of the proposed strategy in theory. The strategy is applied in a fermentation workshop in Yantai, Shandong province, and operating results show that it proves good control accuracy, high tolerance for variety and disturbance in practice.
Geospatial Sensor Web Resource Management System for Smart City: Design and Implementation

It is a needful and challenging work to integratedly manage the massive, distributed and heterogeneous sensor resources for a cooperative observation task in smart city context, especially for the cooperative task of dynamic environment monitoring, timely emergency response and citizen safety guarantee. Regarding the heterogeneous sensor resources that immersed in the cities, there lacks an open and comprehensive platform for the management of this sensing infrastructure of the smart cities. In this paper, a Geospatial Sensor Web Resource Management System (Geo-SWRMS) is designed and implemented to tackle this issue. With the requirement investigation of the resources management of the Geospatial Sensor Web for the smart city, four main functions including resource modeling and registry, resource query and discovery, resource visualization and resource access and control are considered and implemented leveraging the standard Sensor Web Enablement information model and service interface of Open Geospatial Consortium. The proposed system is flexible, accommodating heterogeneous sensor resources and can be utilized in multiple application fields in the smart cities such as sensing resource management, cooperative observation task for emergency and so on. The Geo-SWRMS promotes the sharing and interoperability of the sensor resources, and facilitates to provide a solid information base for observing task scheduling and decision making in the smart city application.
Compact dual-mode dual-band bandpass filter with inside–outside–reversed dual-ring topology

A compact dual-mode dual-band bandpass filter is proposed based on the inside–outside–reversed dual-ring topology. Different from the traditional design, the total size of the filter is limited by the second passband with shorter wavelength at higher frequency, instead of the first passband with longer wavelength at lower frequency. By loading four square patches in the inner ring, the degenerate modes of the inner ring move down and form the first passband, whereas the second passband is constructed by the outer ring. By utilising the coplanar-waveguide feeding at ground plane, a prototype of the dual-band filter with two operating frequencies at 0.92 and 1.47 GHz is designed and verified experimentally.
Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation

This paper presents a cost-sensitive rank learning approach for visual saliency estimation. This approach avoids the explicit selection of positive and negative samples, which is often used by existing learning-based visual saliency estimation approaches. Instead, both the positive and unlabeled data are directly integrated into a rank learning framework in a cost-sensitive manner. Compared with existing approaches, the rank learning framework can take the influences of both the local visual attributes and the pair-wise contexts into account simultaneously. Experimental results show that our algorithm outperforms several state-of-the-art approaches remarkably in visual saliency estimation.
L-band directly modulated laser for 10G PONs

Among a variety of techniques for broadband access, the infrastructure based on Passive Optical Network (PON) is one of the most viable solutions. In 10- and 40-Gigabit capable PON, the downstream wavelength in optical line terminals (OLTs) has been set in L-band. The electroabsorption modulated laser (EML) is a popular lasing source in such PONs due to its low chirp and high modulation speed. However, its complicated epi-growth technology of active layers poses a serious reliability issue and causes a substantial increase of the fabrication cost. The conventional DFB laser has advantages of compact structure, reliable operation, low cost and power consumption. It has been well recognized that the major obstacle of implementing the L-band DFB laser in such system is its relatively large parasitic frequency chirp when directly modulating the injection current. This chirp broadens the linewidth of the output spectrum, aggravating the dispersion power penalty seriously, especially when the operation wavelength is far away from the zero-dispersion wavelength for the standard single mode fiber (SMF). Gain detuning is an effective method to reduce the linewidth enhancement factor (LEF). Based on this idea, this paper aims at investigating the potential design to reduce the LEF of the L-band InAlGaAs DFB laser through the optimization of the strained layer multiple quantum well active region, including the layer thickness, strain and band-gap energy, etc. The band structure is obtained by solving the Schrodinger's equation where the valence band structure is described by 6 × 6 Luttinger-Kohn Hamiltonian with spin-orbit coupling taken into consideration. The optical material gain of a quantum well derived from Fermi's golden rule is applied. The differential gain and the refractive index change are then calculated, followed by the LEF. The calculated change of LEF with the lasing wavelength detuning is shown in Fig. 1, in which each dot presents a design achieved by a certain combination of active region parameters when they are scanned within their respective reasonable range of variation. The laser chip with the optimized design is then fabricated and tested in a system shown in Fig. 2. The lasing wavelength is approximately 1589 nm. After the standard uncooled transistor-outlet (TO) packaging, such device is directly modulated under 10 Gbps, and the output optical signal is transmitted over the standard SMF for 20 km. The eye-diagram after the transmission is shown in Fig. 3, which suggests that the optimized design could be a promising candidate in PON system where the L-band lasing source is needed.
Multichip LED Modules With V-Groove Surfaces for Light Extraction Efficiency Enhancements Considering Roughness Scattering

Although multichip light-emitting diode (LED) modules are becoming popular in high-power lighting applications, better light extraction efficiency is always desirable in the industry. In this paper, V-grooves fabricated by the low-cost dicing process have been utilized on the top face of the multichip LED module to enhance the output power. An analytical model including the consideration of surface has been established by using a fractal theory. The combined finite difference time domain and ray tracing method has been used to simulate the light extraction enhancement considering the surface roughness scattering effects. The results show 12% enhancements in the experiments when the measured surface roughness of the V-groove has RMS roughness of 0.25 μm, which is in good agreement with the simulation result of 13.7%. The multichip LED models have been applied in indoor downlight systems and it is found that the luminous efficiency has been enhanced by 9.6% under a current of 350 mA (5.8 W) when compared with multichip LED modules without V-grooves.