Miracle-dz/UniFAR-FTUs huggingface dataset:
Underwater Acoustic Signal Classification Based on Sparse Time–Frequency Representation and Deep Learning

For classification of underwater acoustic signals, we propose a novel sparse anisotropic chirplet transform (ACT) to reveal fine time–frequency structures. The signal features in the form of a time–frequency map are fed into a deep convolutional neural network, referred to as a time–frequency feature network (TFFNet), which brings flexibility to signal classification. The TFFNet is based on a novel efficient feature pyramid enhancing feature (EFP) maps by aggregating the context information at different scales. To remove the gridding artifacts on enhanced feature maps, a form of aggregating transformation, a forward feature fusion, is utilized to merge the forward feature maps. Main contributions of this work are a novel sparse ACT, a TFFNet classifier, and an EFP with forward feature fusion. Experimental results demonstrate that the sparse ACT provides a high-resolution time–frequency representation of underwater signals and the TFFNet improves the classification performance compared to known networks and two machine learning methods (random forest and support vector machine with radial basis function kernel) on two real data sets, an underwater acoustic communication signal data set and whale sounds data set.
Research Article Peach phenological characters: heritability, maternal effect and correlation with brown rot

Peach is a temperate fruit species that is cultivated under various edaphoclimatic conditions all over the world. In Brazil, in the early 1950s, peaches were planted only in Sao Paulo state and in the Southern states, and the harvest period was restricted to 15 days. Currently, mainly due to peach breeding programs, it is cultivated in subtropical areas and even in high altitude tropical areas, with a harvest period of over 100 days. Knowledge of genetic, phenotypic and environmental parameters that influence characters of economic importance is crucial for guiding breeding programs. The objectives of this study were to estimate the heritability of phenological characters, to evaluate their distribution within populations, to test the possible existence of maternal effect and to evaluate the relationship of these traits with brown rot incidence (Monilinia fructicola). The study was performed in Pelotas, RS, Brazil during 2015-2016 to2017-2018 seasons. Sixteen first generation (F1) progenies were evaluated, 10 of them being reciprocal crosses. All genotypes were cultivated in the same area, under the same cultural practices (without fungicide application). Full bloom was considered when more than 50% of flowers were open, and the harvest, when more than 10 fruits reached commercial maturity, the fruit development period being calculated by the difference between full bloom and harvest dates. Brown rot incidence was estimated by the percentage of fruits with symptoms. Broad-sense heritability estimates for full bloom date, harvest date, and fruit development period were high (95 to 98%), and narrow-sense heritabilities were medium to high (65 to 72%). A segregation study of these traits suggests a maternal effect on their heritability, mainly for full bloom and harvest date. The three phenological characters were significantly correlated, and only harvest date had a negative and significant correlation (-0.12) with brown rot incidence.
Fixed-time consensus of heterogeneous multi-agent systems based on distributed observer

Fixed-time consensus of the heterogeneous multi-agent system, which consisting of first-order and second-order agents with a leader, is studied in this paper. A new control algorithm based on the distributed observer is proposed. By adopting the graph theory, matrix theory, control theory and Lyapunov stability method, some sufficient conditions for the fixed-time consensus and an upper bound of settling time are given. An example is presented to illustrate the potential correctness of the main results.
K-means clustering combined with principal component analysis for material profiling in automotive supply chains

At a time where available data is rapidly increasing in both volume and variety, descriptive Data Mining (DM) can be an important tool to support meaningful decision-making processes in dynamic Supply Chain (SC) contexts. Up until now, however, scarce attention has been given to the application of DM techniques in the field of inventory management. Here, we take advantage of descriptive DM to detect and grasp important patterns among several features that coexist in a real-world automotive electronics SC. Concretely, Principal Component Analysis (PCA) is employed to analyze and understand the interrelations between ten quantitative and dependent variables in a multi-item/multi-supplier environment. Afterwards, the principal component scores are characterized via a K-means clustering, allowing us to classify the samples into four clusters and to derive different profiles for the multiple inventory items. This work provides evidence that descriptive DM contributes to find interesting feature-patterns, resulting in the identification of important risk profiles that may effectively leverage inventory management for superior performance.
A Survey on Neuromarketing Using EEG Signals

Neuromarketing is the application of neuroscience to the understanding of consumer preferences toward products and services. As such, it studies the neural activity associated with preference and purchase intent. Neuromarketing is considered an emerging area of research, driven in part by the approximately 400 billion dollars spent annually on advertisement and promotion. Given the size of this market, even a slight improvement in performance can have an immense impact. Traditional approaches to marketing consider a posteriori user feedback in the form of questionnaires, product ratings, or review comments, but these approaches do not fully capture or explain the real-time decision-making process of consumers. Various physiological measurement techniques have been proposed to facilitate the recording of this crucial aspect of the decision-making process, including brain imaging techniques [functional magnetic resonance imaging (fMRI), electroencephalography (EEG), steady state topography (SST)], and various biometric sensors. The use of EEG in neuromarketing is especially promising. EEG detects the sequential changes of brain activity, without appreciable time delay, needed to assess both the unconscious reaction and sensory reaction of the customer. Several types of EEG devices are now available in the market, each with its own advantages and disadvantages. Researchers have conducted experiments using many of these devices, across different age groups and different categories of products. Because of the deep insights that can be gained, the field of neuromarketing research is carefully monitored by consumer and research protection groups to ensure that subjects are properly protected. This article surveys a range of considerations for EEG-based neuromarketing strategies, including the types of information that can be gathered, how marketing stimuli are presented to consumers, how such strategies may affect the consumer in terms of appeal and memory, machine learning techniques applied in the field, and the variety of challenges faced, including ethics, in this emerging field.
Employee Motivation in Light Oncial, Non-Financial Rewards and Employee Commitment among Pharmaceutical SMEs of Indonesia

This paper aim to assess the effect of financial and non- financial rewards on employees’ motivation along with mediating effect of employee’s commitment on relati onship of financial and non- financial rewards with employees’ motivation in pharmaceutical industry of Indonesia. For achieving the purpose, structural equation modeling was performed on collected data from 235 employees through self-administered questionnaires from pharmaceutical industry in Indonesia. This research found significant and positive effect of non-financial payments with employee motivation in results of direct relationship, current study found positive but insignificant effect of financial rewards on motivation during direct relationship. This study also found significant results of effect of financial and non-financial rewards on employee commitment. Furthermore current study found positive significant results during mediation by employees’ c ommitment between financial rewards, non-financial rewards with motivation, and employee commitment proved as good mediator. Implication and recommendations were also discussed in current research. This study has contributed in extension of literature on both financial and non financial rewards’ importance in employee motivation. Further to this, this is one of the few studies conducted in Indonesia, especially in pharmaceutical industry .
Development and Validation of a Scale to Explore Pre-Service Teachers’ Sense of Preparedness, Engagement and Self-Efficacy in Classroom Teaching

Raising the quality of initial teacher education can make an important contribution to raising the overall quality of the school system. In Australia, the National Framework for Professional Standards for Teaching is used as a common framework to set standards for the accreditation of teacher education programs. However, institution-wise assessments need to be carried out regularly to explore the quality of preparation pre-service teachers receive and to what extent they feel well prepared to enter teaching. This will enable teacher education programs to implement strategies to strengthen the link between university coursework and professional practice of pre service teachers. This paper discusses the development and validation of a scale to measure preservice teachers’ perceptions of preparedness to teach, readiness to engage with the teaching profession and self-efficacy in teaching. The study also proposes a model describing the relationship among these variables. Data was collected from 235 final year pre-service teachers using a newly developed questionnaire at an Australian university. Data shows that the Pre service Teacher Professional Experience (PTPE) scale is a theoretically sound, gender invariant and psychometrically valid instrument. The implications of using the scale in teacher education programmes are discussed in the context of the findings.
Peer Coaching and Health Science Practicums: Best Practices of Experienced Clinical Educators

The health sciences sector uses work integrated learning to prepare professionals for practice and has done so predominately using a traditional apprenticeship model. Over the past two decades there has been an increasing focus on integrating peer coaching into this learning environment. While peer coaching can occur informally, failure to formalize the process and train participants can negatively impact rapport-building, trust and learning outcomes. Hence, clinical educators often need some guidance in supporting this placement model. As a result, this research examines the best practices of 31 highly experienced clinical educators within a peer coaching placement model by capturing their explicit and tacit supervisory knowledge.
Introducing Patents with Indirect Connection (PIC) for Establishing Patent Strategies

A patent system requires novelty and progressiveness so that new patents do not infringe on the rights of prior art. Patent investigation including a prior art search is essential to the process of commercialization of technology. In general, patent investigation has been conducted by experts based on their qualitative judgement. However, the number of patents has increased so fast that it has become difficult to handle the quantitative burdens of the search with a conventional approach. There have been previous studies dealing with patent investigation to find similar technologies. They had limitations as they did not utilize the citation relationship and similarity between patents in a comprehensive way. In addition, they could not properly reflect the sequential citation relationship of patents though this is effective in discovering similar patents. In this study, we propose an efficient methodology to discover similar technologies by comprehensively considering the similarity and citation relationship between patents. In particular, we intended to reflect the citation sequence and indirect citation relationship in the process of searching for similar patents. For this, we introduced the concept of “patents with indirect connections” (PICs) and devised an algorithm to efficiently detect patent pairs having such a relationship. The proposed methodology of this study contributes to preventing patent litigation in advance by discovering patents with such potential risks. It is expected that this method will provide patent applicants with the opportunity to establish appropriate strategies against competitors with similar technologies. In order to examine the practical applicability of the proposed method, Korean patents related to machine learning and deep learning were collected. As a result of the experiment, it was possible to identify 24 pairs of similar patents without a direct citation relationship and derive appropriate counter strategies.
Discrete‐time systems with slope restricted nonlinearities: Zames–Falb multiplier analysis using external positivity

This article exploits positive systems theory in the search for Zames–Falb multipliers for the analysis of discrete‐time Lurie systems, where the nonlinearity is assumed to be slope‐restricted. Although a similar problem has been tackled in a continuous time context, the results in discrete‐time take a different form and require a somewhat different approach to overcome certain technical problems. The work has two compelling features: (i) the arising algorithms are completely convex; and (ii) numerical results compare well with the state‐of‐the‐art in some cases, providing the least conservative result in one instance.
Design and experimental investigation of a novel spiral microfluidic chip to separate wide size range of micro-particles aimed at cell separation

Graphical abstract Isolation of microparticles and biological cells on microfluidic chips has received considerable attention due to their applications in numerous areas such as medical and engineering fields. Microparticles separation is of great importance in bioassays due to the need for smaller sample and device size and lower manufacturing costs. In this study, we first explain the concepts of separation and microfluidic science along with their applications in the medical sciences, and then, a conceptual design of a novel inertial microfluidic system is proposed and analyzed. The PDMS spiral microfluidic device was fabricated, and its effects on the separation of particles with sizes similar to biological particles were experimentally analyzed. This separation technique can be used to separate cancer cells from the normal ones in the blood samples. These components required for testing were selected, assembled, and finally, a very affordable microfluidic kit was provided. Different experiments were designed, and the results were analyzed using appropriate software and methods. Separator system tests with polydisperse hollow glass particles (diameter 2–20 µm), and monodisperse Polystyrene particles (diameter 5 & 15 µm), and the results exhibit an acceptable chip performance with 86% of efficiency for both monodisperse particles and polydisperse particles. The microchannel collects particles with an average diameter of 15.8, 9.4, and 5.9 μm at the proposed reservoirs. This chip can be integrated into a more extensive point-of-care diagnostic system to test blood samples.
The Mediation Role of Organizational Commitment in the Relationship between Strategic Human Resources Management and Individual Performance

The aim of this research is to examine the mediating role of organizational commitment in the relationship between strategic human resource management and individual performance. For this purpose, data were collected from SME businesses operating in Aksaray through convenience sampling method in the period covering February-March 2019. The questionnaire prepared to collect data consists of four parts. The first part of the questionnaire includes questions about the demographic characteristics of the survey participants. The second part of the questionnaire is about the strategic human resources management scale. In the second part of the questionnaire, a scale consisting of 9 statements, which was developed by Huselid (1995) and rearranged by Batram et al. (2007), was used. For the organizational commitment scale in the third part of the questionnaire, the scale consisting of 7 statements developed by Katsikea et al. (2011) was used. For the individual performance scale in the last part of the questionnaire, a scale consisting of 6 statements developed by Green et al. (2006) was used. The collected data were analyzed with the help of SPSS and SmartPLS statistics program, and the data were analyzed by frequency, reliability analysis, confirmatory factor analysis and structural equation modeling. According to the results of this study, it was determined that organizational commitment has a full mediating role in the relationship between strategic human resources management and individual performance. As strategic human resources management increases the organizational commitment of the employees, it has been concluded that it also positively affects their individual performance.
Transformational Leadership and Employee Innovation: A Moderated Mediating Effect Model

How to motivate employees' innovative behavior is a constant concern of enterprise innovation management. At present, the research on the superior leadership and employee innovation behavior only reflects the direct relationship between the two, but the "black box" of the mechanism of the effect between the two has not yet been opened up. Based on individual motivation theory, this paper constructs a mediated model with regulation effect. The results show that transformational leadership is conducive to motivating employees' innovative behavior, and employees' psychological ownership plays a mediating role in the mechanism of the effect, and task complexity plays a regulatory role between psychological ownership and innovative behavior.
NPSCS: Non-Preemptive Stochastic Coflow Scheduling With Time-Indexed LP Relaxation

Coflows model a scheduling setting that is commonly found in a variety of applications in distributed and cloud computing. A stochastic coflow task contains a set of parallel flows with randomly distributed sizes. Further, many applications require non-preemptive scheduling of coflow tasks. This article gives an approximation algorithm on the weighted expected completion time for non-preemptive stochastic coflow scheduling. The proposed approach uses a time-indexed linear program relaxation, and uses its solution to come up with a feasible schedule. This algorithm is shown to achieve an approximation ratio of <inline-formula> <tex-math notation="LaTeX">$(2\log {m}{+}1)(1{+}\sqrt {m {\Delta }})(1{+}m\sqrt {{\Delta }}){(1{+}{\Delta })}$ </tex-math></inline-formula> for zero-release times, and <inline-formula> <tex-math notation="LaTeX">$2(2\log {m}{+}1)(1{+}\sqrt {m{\Delta }})(1{+}m\sqrt {{\Delta }})(1{+}{\Delta })$ </tex-math></inline-formula> for general release times, where <inline-formula> <tex-math notation="LaTeX">${\Delta }$ </tex-math></inline-formula> represents the upper bound of squared coefficient of variation of processing times, and <inline-formula> <tex-math notation="LaTeX">${m}$ </tex-math></inline-formula> is the number of servers.
Hierarchical global fast terminal sliding‐mode control for a bridge travelling crane system

The bridge crane system is a typical under-actuated system that is widely used in production and life. Although various scholars have conducted extensive research on the bridge crane system in recent years, there are still many problems, such as the trajectory planning of the cart and the anti-sway control of the cargo. In order to tackle the problem of the anti-sway control of the cargo, a hierarchical global fast terminal sliding-mode control (H-GFTSMC) is developed in this work. First, the Lagrange equations are used to model the system dynamics. Then, an appropriate hierarchical global fast terminal sliding-mode controller is designed to achieve anti-sway control of the cargo, and it is proved that each sliding-mode surface is progressively stable. A series of simulations were implemented to verify the effectiveness of the control method. The simulation results show that the H-GFTSMC has better control performance compared with the proportional–integral–derivative control method. When changing the cable length or adding non-negligible noise to the system, the H-GFTSMC still has good robustness.
Detection of invasive shrimpPalaemon sinensis (Sollaud, 1911) using environmental DNA

̶ The nonnative freshwater shrimp Palaemon sinensis (Sollaud, 1911) has been reported at various locations in Japan. This study compared environmental DNA (eDNA) analysis with conventional capturing and investigation as a method to detect P. sinensis in the Tama River. We developed species-specific primers to amplify a 225-bp fragment of the cytochrome c oxidase subunit I gene for eDNA analysis. The invasive shrimps were detected using eDNA analysis in all areas where they were observed using the capture and investigation method. Thus, eDNA analysis can be applied to detect sparsely distributed P. sinensis in the Tama River, making it a useful method to detect invasive shrimps and to help prevent ecological disruption.
Photonic scheme for implementing quantum square root controlled Z gate using phase and intensity encoding of light

University Grants Commission Abstract Quantum logic gate operates on a number of qubits, where a controlled Z gate operates on two qubit data. Similarly, the square root of controlled Z (SRCZ) operates also on two qubit data. The SRCZ gate is very much advantageous in quantum computing. Different quantum gates are implemented by using the physical properties of light such as phase, polarization, intensity, and frequency. Here, the authors propose a photonic scheme for implementing quantum SRCZ logic gate using phase as well as intensity encoding. The non‐linear property of Pockels material with proper external biasing voltage is used to develop the scheme.
Überwachung und Steuerung von Granulationsprozessen mit Hilfe der Nah-Infrarot-Spektroskopie

To meet the degree of rising automation of granulation and drying processes in single-pot systems a technique for the in-process control was developed. A sensor probe was constructed to record near-infrared spectra during the running process. The first step was to determine the solvent content. A placebo formulation was used for calibration batches. Samples of the granulates were taken during production. The solvent contents of the samples were determined with a suitable reference method. The results were correlated to the spectra with help of chemometrical methods. Thus, a calibration could be established allowing the control of the solvent content during the whole process. The practicability of this method could be verified for several commercial granulates. Preliminary investigations to supervise particle growth during granulation or particle size during drying were also succesful.