Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear suppression scheme employing transmit power control for MIMO-OFDM systems

This paper proposes a deterministic nonlinear distortion suppression scheme employing transmit power control for MIMO-OFDM systems. The feature of the proposed scheme is to suppress the nonlinear distortion by adjusting the transmit power level of each transmit antenna to be the maximum signal-to-noise-plus-distortion ratio (SNDR) and to perform MIMO signal detection using the appropriate transmit power levels notified to the receiver. In the proposed scheme, since the transmit power tends to be lowered to satisfy the maximum theoretical SNDR, the transmit power as well as the bit error rate (BER) can be fortunately reduced in comparison with the traditional constant power transmission scheme, which consequently leads to alleviating the out-of-band radiation. The effectiveness of the proposed scheme is demonstrated compared with the traditional scheme with constant transmit power by means of computer simulations.
The Effect of Perception of Complaint Management System on Purchase Intention: The Mediating Role of Cognitive Dissonance

Traditionally, purchase intention has been a very popular dependent variable among the marketers and researchers. A very important antecedent of purchase intention is cognitive dissonance (CD). CD, in turn, is affected by a number of factors. One such factor is the risk of the consumer of not getting a proper redress solution in case he faces any problem with the product after its use. This risk is termed ‘the perceived recourse and redress risk (PRRR)’. It is used as a measure to analyse the efficiency of complaint management systems (CMSs). The study aims to analyse how consumers perceive the CMS of companies and its effect on the perception of CD with its subsequent effect on purchase intention. The study was carried out in the pre-purchase context on a sample of 600 respondents across five cities. The structural equation modeling (SEM) was used to analyse the data. The results indicated that among the eight dimensions of PRRR, only four dimensions affected the CD of customers, namely: no response, rudeness, extended delay and no action from customer care. The study leaves an implication for marketers to work on these dimensions and make the CMS more effective in order to increase the purchase intention of consumers.
A model for the Z-track phenomenon in GX 5-1 and observational evidence for the physical origins of the kHz QPO

We present the results of a combined investigation of the spectral and kHz QPO evolution around the Z-track in GX 5-1 based on high-quality Rossi-XTE data. In spectral analysis, we find that the Extended ADC emission model provides very good fits to all of the spectra, and the results point clearly to a model for the nature of the Z-track in this source, in agreement with previous results for the similar source GX 340+0. In this model, at the soft apex of the Z-track, the mass accretion rate u M is at its minimum and the neutron star has its lowest temperature; but as the source moves along the normal branch, the luminosity of the Comptonized emission increases, indicating that u M increases and the neutron star gets hotter. The measured flux f of the neutron star emission increases by a factor of ten becoming super-Eddington, and we propose that this causes disruption of the inner disk and the formation of jets. In flaring, the luminosity of the dominant Comptonized emission from the accretion disk corona is constant, while the neutron star emission increases, and we propose for the first time that flaring consists of unstable nuclear burning on the neutron star, supported by the agreement between the measured mass accretion rate per unit area u m at the onset of flaring and the theoretical critical value at which burning becomes unstable. There is a striking correlation between the frequencies of the kHz QPO and the ratio of the flux to the Eddington value: f /fEdd, suggesting an explanation of the higher frequency QPO and of its variation along the Z-track. It is well known that a Keplerian orbit in the disk at this frequency corresponds to a position some distance from the neutron star; we propose that the oscillation always occurs at the inner disk edge, which moves radially outwards on the upper normal and horizontal branches as the measured increasing radiation pressure increasingly disrupts the inner disk.
Recovery Mechanism for Diff-based Reprogramming in WSNs

Reprogramming remote sensor nodes on wireless sensor networks (WSNs) allows the software on them to be dynamically updated or enhanced for adapting to changed environmental conditions or application requirements. Many researches use diff-based approaches to transmit only the code difference to sensor nodes for updating, but failure of diff-based reprogramming may cause extra problems. Because sensor node's storage is limited, the older version of patch files may be overwritten by the next one. Then after many times of update, reprogramming recovery mechanism will lack the intermediate version of patch files for incremental recovery. To recover from this situation, extra data retransmission is needed and the host machine should issue recovery commands, but both of them will also affect all other normal nodes in WSN. The data retransmission is especially unacceptable in a resource-limited WSN environment. To solve these problems, we have proposed two new diff-based recovery mechanisms named N and N-1 Incremental Recovery to recover sensor nodes from reprogramming failures. We implement the proposed mechanism in TinyOS and choose Two-Stage Diff as our diff-based dynamic update mechanism for updating the software on sensor nodes. Experiments with the modified TinyOS show that our N and N-1 Incremental Recovery compared with the Deluge default recovery mechanism can greatly reduce the amount of retransmitted data and the processing time can be significantly reduced as well.
Needs, Expectations, and Experiences of International Students in Pathway Programs in the United States

This research assesses the first cohort of pathway students’ needs and their academic and sociocultural experiences at a U.S. university. A needs analysis survey, individual student interviews, and a follow-up survey were used for data collection. Understanding lectures, completing assignments, and building social relationships with domestics were among the challenges faced by pathway students due to linguistic and cultural barriers. An additional unique challenge for this particular population of international students centered around the fact that undergraduate and graduate students tackle discipline-related courses while still refining their English skills. Additional support services to help students in pathways academically and socio-culturally are crucial.
Impulsive noise of partial discharge and its impact on minimum distance-based precoder of MIMO system

Impulsive interference has been measured recently in some wireless communication environments. By using measured data of partial discharge, we show in this paper that the Middleton Class A model can approximate the impulsive noise in an electricity substation better than the Gaussian noise. The measured data was obtained from Hydro-Québec's Research Institute in cooperation with ETS (École de technologie supérieure of Montreal). We derive an extension of Middleton Class A model for multi-antenna systems. Using this model with estimated parameters from measured data, we evaluate the performance of two linear MIMO precoders with two spectral efficiencies (4 bit/s/Hz and 8 bit/s/Hz). The max-dmin precoder optimizes the minimum Euclidean distance of the received constellation and the max-SNR or single beamforming maximizes the received SNR.
Semantic clustering-based cross-domain recommendation

Cross-domain recommendation systems exploit tags, textual descriptions or ratings available for items in one domain to recommend items in multiple domains. Handling unstructured/ unannotated item information is, however, a challenge. Topic modeling offer a popular method for deducing structure in such data corpora. In this paper, we introduce the concept of a common latent semantic space, spanning multiple domains, using topic modeling of semantic clustered vocabularies of distinct domains. The intuition here is to use explicitly-determined semantic relationships between non-identical, but possibly semantically equivalent, words in multiple domain vocabularies, in order to capture relationships across information obtained in distinct domains. The popular WordNet based ontology is used to measure semantic relatedness between textual words. The experimental results shows that there is a marked improvement in the precision of predicting user preferences for items in one domain when given the preferences in another domain.
PENGARUH MINAT DAN KREATIVITAS BELAJAR MATEMATIKA TERHADAP HASIL BELAJAR MATEMATIKA SISWA KELAS X SMA

Penelitian ini merupakan penelitian ex – post facto yang bersifat koresional.Masalah yang diselidiki dalam penelitian ini adalahketerkaitan variabel minat dan kreativitas terhadap hasil belajar matematika.Data dikumpulkan diolah dengan menggunakan analisis statistik “SPSS dan Minitab”. Hasil analisis menunjukkan bahwa minat belajar matematika diperoleh skor rata-rata 73,14 dari skor ideal 125 dengan standar deviasi 13,613. Kreativitas belajar matematika dengan skor rata-rata 63,35 dari skor ideal 100 dengan standar deviasi 7,183 dan hasil belajar matematika dengan skor rata-rata 15,73 dari skor ideal 25 dengan standar deviasi 2,933. Selanjutnya pengujian hipotesis dengan menggunakan analisis regresi linear ganda diperoleh kesimpulan bahwa (1) minat belajar matematika mempunyai pengaruh terhadap hasil belajar matematika siswa kelas X SMA (2) kreativitas belajar matematika tidak mempunyai pengaruh terhadap hasil belajar matematika siswa kelas X SMA (3) minat belajar dan kreativitas belajar matematika secara bersama-sama mempunyai pengaruh terhadap hasil belajar matematika siswa
A New Sequential Covering Strategy for Inducing Classification Rules With Ant Colony Algorithms

Ant colony optimization (ACO) algorithms have been successfully applied to discover a list of classification rules. In general, these algorithms follow a sequential covering strategy, where a single rule is discovered at each iteration of the algorithm in order to build a list of rules. The sequential covering strategy has the drawback of not coping with the problem of rule interaction, i.e., the outcome of a rule affects the rules that can be discovered subsequently since the search space is modified due to the removal of examples covered by previous rules. This paper proposes a new sequential covering strategy for ACO classification algorithms to mitigate the problem of rule interaction, where the order of the rules is implicitly encoded as pheromone values and the search is guided by the quality of a candidate list of rules. Our experiments using 18 publicly available data sets show that the predictive accuracy obtained by a new ACO classification algorithm implementing the proposed sequential covering strategy is statistically significantly higher than the predictive accuracy of state-of-the-art rule induction classification algorithms.
Investigation of Academic Staff in Gastronomy in Terms of Their Satisfaction Level and Adverse Experience

This paper analysis was conducted to determine job satisfaction levels and problems of the instructors employed in gastronomy programs of the universities. The research was structured through qualitative research methods. The research population was constituted with the instructors teaching in gastronomy departments in Turkey and a purposeful sampling strategy was used to determine the research sample. Interview forms were used to collect data and resultant data were subjected to content analysis with the aid of NVIVO software. Kappa analysis was executed to test the data reliability. Present findings revealed that participants were mostly satisfied with the departments or programs, but experienced various problems at work place. Insufficient academic staff, improper curriculums, insufficient budgets, equipment and material supply and poor university-private sector cooperation were indicated as the primary problems experienced by the culinary instructors. The findings cannot be generalized to a larger population because the study is conducted with a case study approach.
Employing Virtual Lecturers' Facial Expressions in Virtual Educational Environments

This research began with a preliminary exploratory study that observed the relationship between the facial expressions of three human lecturers in a real academic lecture theatre and the reactions of the students to those expressions. Results informed the design of the first experiment that aimed to investigate the effectiveness of a virtual lecturer’s expressions on the students’ learning outcomes in a virtual pedagogical environment. A second follow-up experiment then focussed on the effectiveness of a single facial expression (the smile) on student performance. Both experiments involved virtual lectures, with virtual lecturers teaching real students. Results indicated that students performed better (by 86%) in the lectures where the virtual lecturer performed facial expressions compared to the results of the lectures that did not use facial expressions. However, this applied only for reasonably complex instructional material; when simple or basic instructional material was used the facial expressions of the virtual lecturer had no substantial effect on the students’ learning outcome. Finally, it was demonstrated that the appropriate use of smiling increased the interest of the students and consequently their performance.
Data Inversion for Over-Resolved Spectral Imaging in Astronomy

We present an original method for reconstructing a 3-D object having two spatial dimensions and one spectral dimension from data provided by the infrared slit spectrograph on board the Spitzer Space Telescope. During acquisition, the light flux is deformed by a complex process comprising four main elements (the telescope aperture, the slit, the diffraction grating, and optical distortion) before it reaches the 2-D sensor. The originality of this work lies in the physical modeling, in integral form, of this process of data formation in continuous variables. The inversion is also approached with continuous variables in a semi-parametric format decomposing the object into a family of Gaussian functions. The estimate is built in a deterministic regularization framework as the minimizer of a quadratic criterion. These specificities give our method the power to over-resolve. Its performance is illustrated using real and simulated data. We also present a study of the resolution showing a 1.5-fold improvement relative to conventional methods.
Adaptive robust nonlinear design of course keeping ship steering autopilot

This paper develops an adaptive robust control design strategy for automatic steering of ships with unknown parameters under unknown environmental disturbances induced by wave, wind, and ocean current. Based on the incorporation of the Nussbaum-type function into backstepping design and some technical lemmas, the proposed design method does not require a priori knowledge of the sign of the unknown coefficient. It is proved that the designed adaptive robust controller can guarantee the uniform ultimate boundedness of the resulting closed-loop system signals. The control performance can be guaranteed by an appropriate choice of the design parameters. Simulation results on a 45 meters long ship are presented to validate the proposed controller.
Exploring the Trisection of Software, Hardware, and ISA in Memory Model Design

The ISA is a multi-part specification of hardware behavior as seen by software. One significant, yet often underappreciated, aspect of this specification is the memory consistency model (MCM) which governs inter-module interactions in a shared memory system. This paper makes a case for MCM-aware ISA design, and provides a toolflow to support it. Our primary contribution is a methodology for evaluating and refining an ISA’s MCM to ensure a correct and complete specification. We also apply our framework to the open source RISC-V ISA [51], focusing on the goal of accurate, efficient, and legal compilations from C/C++. We uncover under-specifications and potential inefficiencies in the current RISC-V ISA documentation and identify possible solutions for each. As an example, we find that a RISC-V-compliant microachitecture allows 144 outcomes forbidden by C/C++ to be observed out of 1,701 litmus tests examined. Overall, this paper demonstrates the effectiveness of our methodology for pinpointing MCM-related issues early in the ISA design process.
PERFORMANCE ENHANCEMENT OF SHUNT ACTIVE POWER FILTER WITH FUZZY AND HYSTERESIS CONTROLLERS

This paper proposes fuzzy and hysteresis controllers based three phase Shunt Active Power Filter for current harmonic compensation to improve the performance of 3 ɸ supply system feeding non-linear loads. The Shunt Active Power Filter is used to eliminate current harmonics. The dc link control strategy is based on the fuzzy logic controller. Gating pulses for the Shunt Active Filter is generated using Hysteresis current controller based Pulse width modulation technique. The proposed model is simulated in MATLAB/SIMULINK. Simulation results show that the dynamic behavior is better than the conventional Proportional-Integral (PI) controller and is found to be more robust for changes in load.
Streamed watershed transform on GPU for processing of large volume data

Since its introduction the watershed transform became a popular method for volume data segmentation. A range of various algorithms for its computation were developed, including parallel algorithms for computation on different architectures. Recently also algorithms for consumer graphical accelerators were developed. Neither of these, however, are able to process data larger than the available memory as the whole data has to be present in the memory of the device. In this paper we present two versions of a streamed multi-pass algorithm for watershed computation on a GPU. As the slice-based streaming approach is used both variants are capable of processing data exceeding the size of the available graphics accelerator memory.
Adaptive feedback scheduling of incremental and design-to time tasks

This paper discusses an approach for adaptive feedback scheduling in resource insufficient environments. In particular, we examine the problem of maximizing the utilization of the CPU for a collection of periodic incremental and design-to-time tasks with variations in actual execution times. CPU allocation beyond a minimum is performed according to a Quality-of-Service (QoS) based utility function. Schedulability analysis results are utilized to determine guaranteed execution time limits (worst-case schedulability boundary). Past history based on actual task execution times is used to identify the actual schedulability boundary and execution time allocations are adjusted accordingly. This feedback control approach to scheduling supports opportunistic resource allocation beyond the analytic limits, while minimizing deadline misses and limiting them to optional execution increments.
Semi-autonomous teleoperation in task space with redundant slave robot under communication delays

Bilateral teleoperation systems have been extensively utilized for implementing tasks in remote or hazardous environments. However, due to the cognitive limitations of the human operator, efficient teleoperation of complex robotic system operating in cluttered environments has been difficult to achieve. In this paper, we study the control problem of a semi-autonomous teleoperation system, where the redundant slave robot can autonomously satisfy several constraints while tracking the position of the master robot in the task space. Considering heterogeneous master and slave robots, we first develop a control algorithm to ensure task space position and velocity tracking between the master and slave robots in the presence of dynamic uncertainties and communication delays. The redundancy of the slave robot is then utilized for achieving sub-task control, such as singularity avoidance, joint limits, and collision avoidance. The control algorithms for the proposed semi-autonomous teleoperation system are validated using numerical simulations on a non-redundant master and a redundant slave robot.
CORN: Correlation-driven nonparametric learning approach for portfolio selection

Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications. In this article, we propose a novel learning-to-trade algorithm termed CORrelation-driven Nonparametric learning strategy (CORN) for actively trading stocks. CORN effectively exploits statistical relations between stock market windows via a nonparametric learning approach. We evaluate the empirical performance of our algorithm extensively on several large historical and latest real stock markets, and show that it can easily beat both the market index and the best stock in the market substantially (without or with small transaction costs), and also surpass a variety of state-of-the-art techniques significantly.
Social Information Transmission in Animals: Lessons from Studies of Diffusion

The capacity to use information provided by others to guide behavior is a widespread phenomenon in animal societies. A standard paradigm to test if and/or how animals use and transfer social information is through social diffusion experiments, by which researchers observe how information spreads within a group, sometimes by seeding new behavior in the population. In this article, we review the context, methodology and products of such social diffusion experiments. Our major focus is the transmission of information from an individual (or group thereof) to another, and the factors that can enhance or, more interestingly, inhibit it. We therefore also discuss reasons why social transmission sometimes does not occur despite being expected to. We span a full range of mechanisms and processes, from the nature of social information itself and the cognitive abilities of various species, to the idea of social competency and the constraints imposed by the social networks in which animals are embedded. We ultimately aim at a broad reflection on practical and theoretical issues arising when studying how social information spreads within animal groups.
Notice of RetractionA new Web Service Structure of Combining P2P and CDN Technologies

Nowadays, streaming media and web pages have occupied the most bandwidth on the Internet. And it's important to remain the scalability, performance, fairness and resources management potential while providing the Web Service. In this paper, we have proposed a new Web Service Structure of Combining P2P and CDN Technologies. By building a P2P Content Distribution Network (CDN), peers collaborate to distribute the content of under provisioned websites and to serve queries for larger audiences on behalf of the websites. This can reveal very challenging, given the highly dynamic and autonomous participation of peers. And it also can be used to implement in Cloud Computing and Cloud Storage.