Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of multiple frequency slopes waveform based on genetic algorithm for MIMO radar

Design of orthogonal waveforms with good correlation property is crucial for implementing multiple input multiple output (MIMO) radar. Firstly, a waveform set design using multiple frequency slopes (MFS) is presented. Secondly, for getting an optimization result, genetic algorithm (GA) is proposed to numerically search optimal frequency slope sequences for MFS waveforms. Finally, the simulation results and comparisons show that the optimal method proposed in this paper can make the MFS waveforms have good orthogonal performance.
TDOA based geolocation using IRLS algorithm

The geolocation method using the wireless signal processing system is widely used in many industrial areas. The time difference of arrival (TDOA) method is one of the most commonly used geolocation methods. The TDOA signal based geolocation system can estimate the position of a mobile object by using at least three base stations in two dimensional space. In geolocation problem, the precise estimation of mobile's position is the most significant issue. The measurement noise that is contained in measured TDOA data causes the estimation inaccuracy in a mobile geolocation. In this paper, the objective function that represents the scalar error of position estimation is formulated using the concept of L -norm approximation. Also we suggest the iterative reweighted least square (IRLS) scheme for minimizing of the objective function. The optimal solution can be obtained using the limited measurement data through the reweighted iteration process of the IRLS scheme.
A 5V CMOS chip for interpolation of sine/cosine signals

This paper describes an analog/digital CMOS chip for interpolation of sine /cosine signals coming from optoelectronic sensors used in incremental primary elements. The presented chip contains the current to voltage converters for sine, cosine and reference channel, the nonlinear network interpolator and the digital circuitry for serial pulse output and absolute position output. Peak to peak differential input currents in the range of 6µA to 16µA are processed with a 500 kHz signal bandwidth and an interpolation factor IF of 5 to 50. The interpolation is done by a special 30 MHz tracking scheme which is insensitive to signal noise so that wrong count errors are impossible. The chip is fabricated in a 1.2-micron double-poly/double-metal process.
Factors for the Adoption of E-Finance and other E-Commerce Systems

The development of e-commerce relies upon customer usage intentions, and IS researchers have examined usage intentions toward various online e-commerce systems. However, these systems have been studied in prior works independently rather than comprehensively. In order to pursue better measures for predicting and explaining B2C e-finance and some other major e-commerce adoptions for customers, we conducted a comparison analysis across different online systems to advance the understanding of the adoption factors and their linkage to customer behavior. Refining from Perceived Risk Theory and existing studies, specific risk facets, customer characteristics and system characteristics were operationalized and integrated within the Technology Acceptance Model (TAM) resulting in a proposed e-finance and other e-commerce system adoption model.
A Mathematical and Sociological Analysis of Google Search Algorithm

Abstract : Google search algorithm for finding relevant information on-line based on keywords, phrases, links, and webpages is analyzed in the mathematical and sociological settings in this article. We shall first survey mathematical study related to the Google search engine and then present a new analysis for the convergence of the search algorithm and a new update scheme. Next based on sociological knowledge, we propose to use in- and out- linkages as well as use the second order linkages to refine and improve the search algorithm. We use the sociology to justify our proposed improvements and mathematically prove the convergence of these two new search algorithms.
Data-Driven Analysis of Database-Assisted Spectrum Access for Mobile Users

White space databases (WSDB) have relieved the mobile devices from the challenge of spectrum sensing at low signal levels by introducing sensing-as-a-service approach. On the other hand, the regulations for WSDB-based spectrum access have asserted very strict constraints for mobile secondary users (SU). According to the US regulations, a mobile SU must query the WSDB anew each time as it relocates 100 meters. This requirement is problematic for mobile users, since car moving at moderate speed will hardly have a chance to access the spectrum at all, because of average latency of a WSDB query. In this paper, we analyze the spatiotemporal changes in the TV white spaces (TVWS) to develop more insights on the current regulations and performance enhancements for mobile scenarios. More particularly, we simulate realistic usage of mobile devices and analyze spatiotemporal accessibility variations of TVWS using a large data set of observations. Using a publicly-available geolocation database, we monitor the TVWS spectrum for about 6 months for 9 routes in different locations across the US. We report on the change in number of free channels on a route, the variations in the availability of a particular channel over a time period, maximum permitted transmission powers, WSDB response time, and channel lease times. Studying spatiotemporal changes in TVWS, we find that current TVWS ecosystem is inherently static and displays minimal temporal variations. This observation supports the criticism that current regulations are very conservative especially for mobile usage and suggests that spectrum information caching would be efficient.
Regional Inequality in China, 1978-2006

Using the most recent statistical data, two U.S.-based geographers document the changes and level of regional inequality in China for the period 1978-2006, in order to shed light on whether recent government efforts toward inequality reduction have had observable effects. The paper reveals the spatial dynamics that underlie regional inequality by decomposing interprovincial inequality into its interregional and intraregional components, and investigating the growth trajectories of regions and provinces. The authors demonstrate that interprovincial inequality declined during the 1980s, increased in the 1990s, was relatively stable from the late 1990s to 2004, and has declined thereafter. Through closer analysis, they show how the trend in interprovincial inequality up to 2004 has been shaped by countervailing patterns in (declining) intraregional inequality and (increasing) interregional inequality. Since 2004, however, the study reveals that both interregional and intraregional inequalities have declined, reflecting convergence in growth rates among provinces and among regions. Journal of Economic Literature, Classification Numbers: I31, O18, R12. 9 figures, 1 table, 77 references, 1 appendix.
A Reversible Data Hiding Scheme Using Segmentation Strategy and Histogram Adjustment

Because a stego medium is easier to cheat an unexpected user’s observation, Steganography technique is more suitable for delivering secret data. Histogram adjustment is a good way for concealing secret data into a cover image with small distortion. The proposed method is to increase the height of peak in difference histogram as many as possible.
Near-Infrared Interferometric Images of the Hot Inner Disk surrounding the Massive Young Star MWC 349A

We present images of the massive young star MWC 349A at 1.65, 2.16, and 2.27, and 3.08 μm, reconstructed from complex visibility data obtained with an aperture-masking interferometric technique on the Keck I telescope. These images have an approximately elliptical appearance and are consistent with the expected shape of a nearly edge-on disk. Visibility data at 1.65, 2.27, and 3.08 μm were fitted with uniform ellipses with major axes 36 ± 2, 47 ± 2, and 62 ± 1 mas in length, respectively. The major axis is at a position angle of 100° ± 3°, consistent with the position angle of the dark lane observed previously in VLA radio continuum maps at 8 and 22 GHz. This axis is also perpendicular to the symmetry axis of the bipolar lobes of H66α recombination line emission and is consistent with positions of the recombination line maser spots at 1.3 mm. At an assumed distance of 1.2 kpc, the linear sizes of the disk are 44 and 57 AU at 1.65 and 2.27 μm, respectively. These images are consistent with a dust disk having an angle between the symmetry axis of the disk and the plane of the sky of 15° and thickness of 6 AU, or an angle of 20° and thickness of 1.4 AU, giving an upper bound to the mass of the disk of Md < 5.7 M☉ or Md < 1.3 M☉, respectively.
Novel Memristive Charge- and Flux-Based Sensors

The fourth fundamental circuit element, memristor, is characterized by its electrical memory resistance (memris- tance), which is a function of the charge/flux. In this paper, using the unique ability of a memristor to record the historic profile of the applied current/voltage via its memristance, we propose novel memristive charge- and flux-based sensing schemes. Using a memristor, the capacitance, inductance, and power measurements are reduced to a resistance measurement. The proposed method seeks a memristive behavior with a constant modulation of the memristance (memductance) with respect to the charge (flux). We further demonstrate a charge-based capacitance sensor using a TiO2 memristor. To have the possibility of both charge- and flux- based sensing, we suggest spintronic memristors based upon the current-driven dynamics of magnetic domain walls. Index Terms? Memristive sensing, domain wall-based memris- tor, spintronic
Expectations, Asset Prices, and Monetary Policy: The Role of Learning

This paper studies the implications of financial market imperfections represented by a countercyclical external finance premium and the gradual recognition of changes in the drift of technology growth for the design of an interest rate rule. Asset price movements induced by changes in trend growth influence balance-sheet conditions that determine the external finance premium. Such movements are magnified when the private sector is imperfectly informed regarding the trend growth rate of technology. The presence of financial market imperfections provides a motivation for responding to the gap between the observed asset prices and the potential level of asset prices in addition to responding strongly to inflation. This is because the asset price gap represents distortions in the resource allocation induced by financial market imperfections more distinctly than inflation. The policymaker's imperfect information about the drift of technology growth renders imprecise the calculation of the potential and thus reduces the benefit of responding to the asset price gap. A policy that responds to the level of asset prices which does not take into account changes in potential tends to be welfare reducing.
A geometrical method for finding the image charges for two orthogonally conducting spheres

The image charges for a given charge distribution in the presence of two orthogonally conducting spheres is found with a pure geometrical method. The paper starts with an original solution of the classical problem of image charges for an electric point charge in a presence of a conducting sphere. The result is applied for the two orthogonally conducting spheres in all the possible situations: spheres with zero potential, isolated spheres with and without electrical charges and spheres with imposed potential.
Compression of Deep Convolutional Neural Networks under Joint Sparsity Constraints

We consider the optimization of deep convolutional neural networks (CNNs) such that they provide good performance while having reduced complexity if deployed on either conventional systems utilizing spatial-domain convolution or lower complexity systems designed for Winograd convolution. Furthermore, we explore the universal quantization and compression of these networks. In particular, the proposed framework produces one compressed model whose convolutional filters can be made sparse either in the spatial domain or in the Winograd domain. Hence, one compressed model can be deployed universally on any platform, without need for re-training on the deployed platform, and the sparsity of its convolutional filters can be exploited for further complexity reduction in either domain. To get a better compression ratio, the sparse model is compressed in the spatial domain which has a less number of parameters. From our experiments, we obtain $24.2\times$, $47.7\times$ and $35.4\times$ compressed models for ResNet-18, AlexNet and CT-SRCNN, while their computational cost is also reduced by $4.5\times$, $5.1\times$ and $23.5\times$, respectively.
Title Cleavage of calnexin caused by apoptotic stimuli : Implication for theregulation of apoptosis

*KURAに登録されているコンテンツの利用については,著作権法に規定されている私的使用や引用などの範囲内で行ってください。 *著作権法に規定されている私的使用や引用などの範囲を超える利用を行う場合には,著作権者の許諾を得てください。 ただし,著作権者 から著作権等管理事業者(学術著作権協会,日本著作出版権管理システムなど)に権利委託されているコンテンツの利用手続については ,各著作権等管理事業者に確認してください。 Title Cleavage of calnexin caused by apoptotic stimuli: Implication for the regulation of apoptosis Author(s) Takizawa, Takenori; Tatematsu, Chizuru; Watanabe, Kimi; Kato, Kanefusa; Nakanishi, Yoshinobu Citation Journal of Biochemistry, 136(3): 399-405
An accelerated coupled feed-radiator-frequency selective surface model for the next generation active phased array systems

Thales Naval Nederland (TNN) has a great history in developing phased array radar systems for naval applications. The most recent innovative examples are the SMART-L long range 3D volume search radar and the APAR multi-function search/track and missile guidance radar. Recent activities include developments of active phased array antennas consisting of multilayer structures designed for a large scanning range, with a relatively large bandwidth and with low radar cross-section (RCS). Within this context and in collaboration with the Eindhoven University of Technology, we studied these design properties by analysing the electromagnetic behaviour of so-called combined feed-radiator-frequency selective surface type array antennas. More specific, but expressed in more general terms, a numerical model is developed for the analysis of a stratified periodic electromagnetic field problem. In a previous paper [BJ Morsink, et al., 2002], this model is compared and benchmarked against available commercial tooling such as HFSS. An arbitrary structure is analysed for its reflection and transmission properties. The emphasis in this paper however is on a new type of acceleration technique that is presented and implemented to reduce the computation time while maintaining accuracy.
Input voltage pumping control for a multi-level switching amplifier

The paper describes energy pumping among dc busses in a multilevel inverter with isolated power supplies driving a passive load, and an algorithm to eliminate it. In the current switching amplifier application, the output current waveforms are required to be of almost arbitrary shape. Modulation techniques are known to be well suited for conventional inverter operation, however when driving some output current waveforms, they can produce dc bus over voltages due to an undesired energy transfer between busses. The specific cases that cause the pumping are described and an algorithm is proposed that eliminates the effect without disturbing the correct operation of the inverter. The algorithms have been tested in a prototype to verify the expected performance.
Topic and sentiment model applied to the colloquial Arabic: a case study of Maghrebi Arabic

Recently, the multiplication of communication and sharing platforms such as social networks, personal blogs, forums, etc., has facilitated the expression of views and opinions about products, personalities, and public policy. However, gathering these points of view is a complex task that requires resolution of many problems in different disciplines, especially issues related to our language. Among the research areas, topic modeling and sentiment analysis stimulates interest and curiosity of the scientific community. Lately, the current economic, geo-political and geostrategic trends have made researchers specifically more interested in Arabic language, except that the majority of these studies focus on the classical Arabic; nevertheless it is a language of the elites which is different from what is mainly used on the Web. Our paper focuses on Maghrebi colloquial Arabic since the little research that exists in this area is limited to East colloquial Arabic. On a corpus extracted from different Facebook pages we implemented a supervised approach to extract the sentiments, and an unsupervised approach to extract topic, then we proposed a new, semi-supervised, approach in the Arabic language that combines the topic and the sentiment in a single model, in order to join each topic to a specific sentiment.
Paternal Depression and Infant Cognitive Development: Implications for Research and Intervention

Although the negative impact of maternal depression on infants' affective and cognitive development is well-documented, the contribution of paternal depression is often overlooked in the research literature and in early intervention practices. This review examines research on the link between paternal depression and infant cognitive outcomes. Although some disagreement exists, studies indicate that paternal depression limits father involvement, which, in turn, influences cognitive development. These findings have implications for research and early intervention programming that address fathers and young children. Further research on paternal depression is needed to understand how paternal depression specifically influences infant cognitive development and to clarify its implications for early intervention. The authors discuss ways that programs, including Early Head Start, have begun to address this issue, by intervening with fathers and children, building partnerships with mental health service agencies, and increasing staff members' abilities to identify and support parents who are experiencing depression. Finally, discussion focuses on directions for future research and ways to support fathers who struggle with depression.
A quantum-inspired classical algorithm for recommendation systems

We give a classical analogue to Kerenidis and Prakash’s quantum recommendation system, previously believed to be one of the strongest candidates for provably exponential speedups in quantum machine learning. Our main result is an algorithm that, given an m × n matrix in a data structure supporting certain ℓ2-norm sampling operations, outputs an ℓ2-norm sample from a rank-k approximation of that matrix in time O(poly(k)log(mn)), only polynomially slower than the quantum algorithm. As a consequence, Kerenidis and Prakash’s algorithm does not in fact give an exponential speedup over classical algorithms. Further, under strong input assumptions, the classical recommendation system resulting from our algorithm produces recommendations exponentially faster than previous classical systems, which run in time linear in m and n. The main insight of this work is the use of simple routines to manipulate ℓ2-norm sampling distributions, which play the role of quantum superpositions in the classical setting. This correspondence indicates a potentially fruitful framework for formally comparing quantum machine learning algorithms to classical machine learning algorithms.
Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

Abstract. This paper is devoted to the experimental quantitative characterization of the shape and orientation distribution of ice particles in clouds. The characterization is based on measured and modeled elevation dependencies of the polarimetric parameters differential reflectivity and correlation coefficient. The polarimetric data are obtained using a newly developed 35 GHz cloud radar MIRA-35 with hybrid polarimetric configuration and scanning capabilities. The full procedure chain of the technical implementation and the realization of the setup of the hybrid-mode cloud radar for the shape determination are presented. This includes the description of phase adjustments in the transmitting paths, the introduction of the general data processing scheme, correction of the data for the differences of amplifications and electrical path lengths in the transmitting and receiving channels, the rotation of the polarization basis by 45°, the correction of antenna effects on polarimetric measurements, the determination of spectral polarimetric variables, and the formulation of a scheme to increase the signal-to-noise ratio. Modeling of the polarimetric variables is based on existing back-scattering models assuming the spheroidal representation of cloud scatterers. The parameters retrieved from the model are polarizability ratio and degree of orientation, which can be assigned to certain particle orientations and shapes. The developed algorithm is applied to a measurement of the hybrid-mode cloud radar taken on 20 October 2014 in Cabauw, the Netherlands, in the framework of the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign. The case study shows the retrieved polarizability ratio and degree of orientation of ice particles for a cloud system of three cloud layers at different heights. Retrieved polarizability ratios are 0.43, 0.85, and 1.5 which correspond to oblate, quasi-spherical, and columnar ice particles, respectively. It is shown that the polarizability ratio is useful for the detection of aggregation/riming processes. The orientation of oblate and prolate particles is estimated to be close to horizontal while quasi-spherical particles were found to be more randomly oriented.
Decentralized algorithms for netcentric force protection against antiship missiles

We model a decentralized network of decision makers charged with optimally deploying hardkill and/or softkill weapons (countermeasures (CMs)) to defend a task group from antiship missiles. Each platform (decision maker) observes missile threats using a combination of shipboard sensor measurement data and data from other ships, but acts independently when controlling its own weapon systems to cooperatively pursue the defensive objectives of the task group in a decentralized fashion. The main results are a formulation of the missile deflection problem as a stochastic shortest path Markovian game with constraints, a characterization of the Nash equilibrium solution, and a decentralized algorithm for computing the Nash equilibrium when the stochastic game is collaborative. Numerical examples are given to demonstrate the equilibrium policies and illustrate their sensitivity to the missile dynamics.
Web personalization to build trust in E-commerce: A design science approach

— With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer’s trust. For new or unknown Internet business, consumers’ lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer’s trust in new or unknown online store.