Miracle-dz/UniFAR-FTUs huggingface dataset:
Signal Shaping for Generalized Spatial Modulation and Generalized Quadrature Spatial Modulation

This paper investigates the generic signal shaping methods for the multiple-data-stream generalized spatial modulation (GenSM) and the generalized quadrature spatial modulation (GenQSM). Three cases with different channel state information at the transmitter (CSIT) are considered, including no CSIT, statistical CSIT, and perfect CSIT. A unified optimization problem is formulated to find the optimal transmit vector set under size, power, and sparsity constraints. We propose an optimization-based signal shaping (OBSS) approach by solving the formulated problem directly and a codebook-based signal shaping (CBSS) approach by finding the sub-optimal solutions in discrete space. In the OBSS approach, we reformulate the original problem to optimize the signal constellations used for each transmit antenna combination (TAC). Both the size and the entry of all signal constellations are optimized. Specifically, we suggest the use of a recursive design for the size optimization. The entry optimization is formulated as a non-convex large-scale quadratically constrained quadratic programming (QCQP) problem and can be solved by the existing optimization techniques with rather high complexity. To reduce the complexity, we propose the CBSS approach using a codebook generated by the quadrature amplitude modulation (QAM) symbols and a low-complexity selection algorithm to choose the optimal transmit vector set. The simulation results show that the OBSS approach exhibits the optimal performance in comparison with existing benchmarks. However, the OBSS approach is impractical for large-size signal shaping and adaptive signal shaping with instantaneous CSIT due to the demand of high computational complexity. As a low-complexity approach, the CBSS shows comparable performance and can be easily implemented in large-size systems.
Modelling and Synchronization of Wind/PV Hybrid System with the Grid Using PLL

In earlier days, fossil fuel was considered as the main source for the production of electricity. Since it has adverse effect on the environment this fossil fuel has been replaced by renewable energy systems. Renewable energy sources offers clean and efficient energy obtained from sun, wind and some other sources. In this paper, a new model of hybrid PV/WIND system is developed. The synchronization of hybrid system with the grid is done by using DSOGI PLL. Hybridizing solar and wind power produces constant power. It provides power to remote location. The modelling and simulation is done in MATLAB/SIMULINK software. The performance characteristics of hybrid system and synchronization to the grid are also presented.
High performance reconfigurable computing with cellular automata

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Impact of a functional-based exercise program on fatigue, quality of life, and muscular endurance in cancer patients: A pilot study

Background/Purpose: The purpose of this study is to investigate the impact of a functional-based exercise program on fatigue, quality of life, and muscular endurance in cancer patients. Methods: Eleven individuals from a Cancer Recovery & Fitness Program participated in this study. After each individual agreed to participate in the study, baseline measurements were taken for three specific muscular endurance exercises; modified biceps curl, modified sit-to-stand, and a modified chest press. Participants also filled out the Functional Assessment of Cancer Therapy-General (FACT-G) questionnaire on perceived quality of life at baseline testing, and the Fatigue Symptom Inventory (FSI) questionnaire on perceived fatigue every week after one exercise session. After attending the six-week program, the participants were retested using the same methods. Results: Dependent (paired) sample t-tests were used to determine if there were significant differences in ME and FACT-G test scores from pretest to post test. Since multiple t-tests were being analyzed, the Bonferroni correction was used to control for Type I error, which resulted in an adjusted p-value of . 0125. Fatigue was tested using a repeated-measure ANOVA. Significant differences were found in the modified biceps curl (p = .005) and modified chest press tests (p = .004). No significant differences were found for the sit-to-stand test or the FSI and FACT-G questionnaires. Conclusion: A 6-week functional-based exercise program can have a significant impact on muscular endurance with cancer survivors in the area of biceps curls and chest press. *Correspondence to: Matthew S Wiggins, Department of Kinesiology, University of WisconsinEau Claire, 105 Garfield Ave., Eau Claire WI, 54701, USA, E-mail: wigginsm@uwec.edu
The Sound Classification System Based on Neural Networks with Attention Mechanism and Autoencoders

This paper discusses the models and methods of machine learning methods used in environmental sound classification systems. A sound classification subsystem could be implemented in the various Smart City, Smart Farming systems, healthcare etc. An automated sound classification system could be decomposed into following subsystems: the audio representation, the features extraction, the classifier and the accuracy estimation. This paper deals with a convolutional neural network with attention mechanism for sound classification and autoencoder for data augmentation. The objective of the paper is to develop the optimal sound classifier for datasets with lack of observations.
FREQUENCY STEERABLE TRANSDUCERS WITH 360° DIRECTIVITY FOR GUIDED WAVES INSPECTIONS IN PLATE-LIKE STRUCTURES

Directional Transducers for Guided Waves generation and sensing are achieved by patterning the piezoelectric material lay-out and the electrodes. The peculiar electrodes’ shape produces a spatial filtering effect which is frequencydependent, so that a direct relationship can be established between the direction of propagation (wavenumber) and the spectral content of the transmitted/receiv ed signal. This kind of transducer has been named Frequency Steerable Acous tic Transducers (FSATs). FSAT dedicated signal processing algorithms enab le localization of acoustic events in 2D spaces by processing two differential o utput of a single device, i.e. using only two acquisition channel thus allowing for a drastic hardware simplification and cost reduction of Guided wave based systems. I n this work, a new generation of FSATs is proposed, which allows steering the wave direction of propagation in the whole angular range [0°; 360°] with imp roved directivity and sidelobes reduction.
Do Commercial Banks Benefited From the Belt and Road Initiative? A Three-Stage DEA-Tobit-NN Analysis

The data envelopment analysis (DEA) treats decision-making units (DMUs) as black boxes: there is an unknown internal structure and transformation mechanism of input to output. Two-stage models have been proposed to resolve this problem by considering the internal structure of DMUs. However, each DMU has a different structure, and in two-stage models, the poor estimation of sub-models causes conflicts in the intermediate layer. Therefore, it is necessary to use additional tools to extract insight into opportunities to enhance the performance of DMUs. This paper presents a three-stage model employing DEA to evaluate efficiency, a Tobit regression model to identify the determinants, and a neural network (NN) to improve those determinants. Improvement in the determinants of a DMU enhances its efficiency. The developed model is applied to the empirical dataset of commercial banks from the countries that have joined the belt and road initiative (BRI), grouping them based on their economist intelligence unit (EIU) rating. The results provide valuable information on the efficiency enhancement process for banks to benefit from the BRI.
Effect of Core Stability Training on the Endurance and Strength of Core in Basketball Players with Trunk Dysfunction

Background: Core stability is predominantly provided by the dynamic function of musculature. Although poor core stability ultimately leads to injury, a proper training can reduce injury. The purpose of this study was to investigate the effects of core stability training on the endurance and strength of core muscles among basketball players with trunk dysfunction. Methods: The present research was a semi-experimental study. 28 basketball players with trunk dysfunction were voluntarily participated in this study, who were then divided into two groups randomly as experimental (n=14) and control (n=14) groups. At the onset of the study, core strength and endurance were measured using some field-based tests. Dynamometer was utilized for strength and the Sorensen, trunk flexion, right and left bridge, and Prone Bridge were used for endurance measurements as pre-test. Experimental group performed the exercise training in terms of the protocol, three days per week, for a 6week period. By the end of the sixth week, the subjects performed the same core tests as post-test. Results: Some significant differences were observed in Sorensen (p=0.003), trunk flexion (p=0.001), prone bridge (p=0.001), right bridge (p=0.001), left bridge (p=0.001), total score of endurance (p=0.001), hip abduction strength (p=0.001), hip external rotation strength (p=0.001), trunk extension strength (p=0.001), and trunk flexion strength (p=0.001) between these two groups. Conclusion: According to the results, it can be concluded that six weeks of core stability training improved core muscle strength and endurance, which are known as two components that being weak in people with trunk dysfunction. Overall, strength and conditioning coaches and basketball players with trunk dysfunction can incorporate the present study’s core training as a viable strategy to induce a significant improvement in the core suggesting a better trunk function.
Diagnosis with Analytic Model of a Rectifier for Faults of the Rectifier Control

The diagnosis of the electric systems is an actual item for the specialists in domain. Due to the variety of the measurements and multiplicity of faults which can be analyzed, the approach is motivating. The model reproduces the behavior of a system both in normal operation and fault occurrence. The procedure which uses the analytic models compares the system evolution in normal and fault conditions operation. The faults which affect the normal system operation can occur on the supplying side (grid faults), in the rectifier itself (one or more switches in fault), on the load side or in the control circuit of the rectifier. Authors had previously studied different faults within a controlled rectifier-DC motor system. The supplying side faults (broken phase, phase to ground and two phases shortcircuit faults), interrupted or short-circuited switch within the rectifier and excitation disappearance were investigated. The paper deals with the analysis of different faults of the control circuit. The considered faults were the firing pulses lack for one switch or for the two switches on the same arm (phase). The effects on the rectifier operation (waveforms, major values) and on the load behavior are highlighted. As it is shown, the effects on the output waveforms of the two studied faults are quite different. Cuvinte cheie: diagnoza defectelor, comanda redresor, model analitic.
Analysis and Control of Power Electronic Converters Based on a System Zero Locations Approach

This chapter presents a procedure to design and control power electronic converters (PECs), which includes a zero-based analysis as a dynamical system response criterion for dimensioning converter passive elements. For this purpose, a nonideal boost DC-DC converter (converter considering its parasitic losses) is dynamically modeled and analyzed in steady state as an application example. The steady-state model is obtained from the average nonlinear model. The steady-state model allows deducing expressions for equilibrium conversion ratio M D ð Þ and efficiency η of the system. Conditions for the converter conduction modes are analyzed. Simulations are made to see how parasitic losses affect both M D ð Þ and η . Then, inductor current and capacitor voltage ripple analyses are carried out to find lower boundaries for inductor and capacitor values. The values of the boost DC-DC converter passive elements are selected taking into account both steady-state and zero-based analyses. A nonideal boost DC-DC converter and a PI-based current mode control (CMC) structure are designed to validate the proposed procedure. Finally, the boost DC-DC converter is implemented in PSIM and system operating requirements are satisfactorily verified.
Control and management strategies for electric vehicles charging

In our days , there is a big interest of the scientific society on the electric vehicles. Electric vehicles constitute a big load for the transmission and distribution network of electric energy, because they are like mobile batteries. They need to charge. In this paper, we will see some strategies on how to control and manage the way that an electric vehicle may charge.
Blocking Misbehaving Users in Anonymizing Networks Using Client Puzzle

: - Anonymous network such as Tor, is used to protect user’s identity and it hides client’s IP address from server through series of routing. The users can authenticate services anonymously by using some credential systems. Since anonymity can give users the license to misbehave, some variants allow the selective deanonymization (or linking) of misbehaving users upon a complaint to a trusted third party. The misbehaving users are collected in the Blacklist. To address this problem, Nymble with client puzzle system is proposed, a system which consist of the following advantages, (1) honest users remain anonymous and their requests unlinkable; (2) a server can complain about a particular anonymous user and gain the ability to blacklist the user for future connections; (3) this blacklisted user’s access remain anonymous before the server complains; and (4) users are aware of their blacklist status before accessing a service. In proposed system, Nymble with client puzzle eliminate the need for Pseudonym Manager and the users can receive nymbles directly from the Nymble Manager and by using nymbles, user is connected with server for accessing the services .
An Audio-based Sequential Punctuation Model for ASR and its Effect on Human Readability

: Inserting punctuation marks into the word chain hypothesis produced by automatic speech recognition (ASR) has long been a neglected task. In several application domains of ASR, real-time punctuation is, however, vital to improve human readability. The paper proposes and evaluates a prosody inspired approach and a phrase sequence model implemented as a recurrent neural network to predict the punctuation marks from the audio. In a very basic and lightweight modeling framework, we show that punctuation is possible by state-of-the-art performance, solely based on the audio signal for speech close to read quality. We test the approach on more spontaneous speaking styles and on ASR transcripts which may contain word errors. A subjective evaluation is also carried out to quantify the benefits of the punctuation on human readability, and we also show that when a critical punctuation accuracy is reached, humans are not able to distinguish automatic and human produced punctuation, even if the former may contain punctuation errors.
Comparing the Effect of 8 Weeks of Total Body Resistance Exercise and Core Stability Training on Selected Common Abnormalities and Postural Control in Deaf Adolescents

Background: Deafness is the most common sensory-neurological defect in human beings. This study aimed to compare the effect of 8 weeks of Total Body Resistance )TRX( and core stability training on balance and some common abnormalities among deaf adolescents. Methods: This study was conducted with a two-group pretest-posttest quasi-experimental study design. The participants included in this study were 20 hearing-impaired students with a degree of deafness between 71-90 dB in Bandar Abbas city who were purposefully selected and then randomly assigned into two groups, as TRX (N=10) and core stability training (N=10). In this study, static balance, dynamic balance, kyphosis and lumbar lordosis, and forward head were measured before and after eight weeks in both groups using one-leg stance test, Y balance test, flexible ruler, and goniometer, respectively. The core stability training consisted of 10 different exercises in the core in terms of the progressing and the TRX protocols. Moreover, these exercises were performed 3 sessions per week for an 8-week period (1 day in between), and each session lasted for 40 minutes. The dependent and independent t-tests were also used to perform the intra-group and inter-group comparisons, respectively. The statistical significance level was set at p ≤ 0.05. Results: The research results show that the abnormalities in the two methods of static balance with open and closed eyes as well as dynamic balance were equally evaluated based on the independent t-test and there was no significant difference between these two methods (p ≥ 0.05). Also, in the forward head, kyphosis, and lordosis variables, the performances of these two methods to reduce the abnormalities were equally evaluated. In this regard, no significant difference was observed between the performances of these two methods (p ≥ 0.05). However, there was a significant difference between the effects of TRX exercises and core stability training on dynamic balance (p ≤ 0.05). Conclusion: Therefore, to reduce abnormalities and improve balance in deaf children, both methods can be considered as effective with no difference.
Visual Question Answering Through Adversarial Learning of Multi-modal Representation

Solving the Visual Question Answering (VQA) task is a step towards achieving human-like reasoning capability of the machines. This paper proposes an approach to learn multimodal feature representation with adversarial training. The purpose of the adversarial training allows the model to learn from standard fusion methods in an unsupervised manner. The discriminator model is equipped with a siamese combinatin of two standard fusion method namely multimodal compact bilinear pooling and multimodal tucker fusion. Output multimodal feature representation from generator is a resultant of graph convolutional operation. The resultant multimodal representation of the adversarial training allows the proposed model to infer the correct answers from open-ended natural language questions from the VQA 2.0 dataset. An overall accuracy of 69.86\% demonstrates the accuracy of the proposed model.
SYNTHESIS AND CHARACTERIZATION OF POLYMERIC MATERIAL BLENDED WITH VARYING Zn AND C NANOPARTICLES

This study experimentally investigated the addition of zinc (Zn) and graphite (C) nanomaterial into polymeric material by sol-gel technique. The objectives of this paper were to outline our investigations in the evolving process of dispersing nanoparticles into polyvinyl alcohol, propylene glycol and methyl cellulose (PVA/PG/MC) polymeric matrix, to study their versatile properties, and evaluating its performance for different applications. The morphology features and chemical composition of the solgel prepared PVA/PG/MC hybrid polymer loaded with Zn and C of varying mixture deposited on metal substrates samples were studied using scanning electron microscopy (SEM) image analysis and the Fourier Transform Infrared (FTIR). The treatment of the nanoparticles of varying quantities used as inorganic materials in PVA/PG/MC polymeric material, has resulted in the polymeric nanostructured materials presenting high performance and multipurpose characteristics beyond that of the parent material original properties. Improved versatile features attributed to the as-synthesized polymeric are materials resistance to moisture, and sterile properties. Furthermore, the study showed that the Zn and C nanoparticles of equal mass ratio were uniformly dispersed in the polymeric material as the particles retained their original size before blending into the polymeric material. This study shows the prospect of applying these nanoparticles as tones with antibacterial properties in several applications.
Creating value in supply chains : suppliers' impact on value for customers, society and shareholders

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Atomic Appends in Asynchronous Byzantine Distributed Ledgers

A Distributed Ledger Object (DLO) is a concurrent object that maintains a totally ordered sequence of records, and supports two operations:APPEND, which appends a record at the end of the sequence, andGET, which returns the whole sequence of records. The work presented in this article is made up of two main contributions.The first contribution is a formalization of aByzantine-tolerantDistributed Ledger Object(BDLO), which is a DLO in which clients and servers processes may deviate arbitrarily from their intended behavior (i.e. they may be Byzantine). The proposed formal definition is accompanied by algorithms that implementBDLOs on top of an underlying Byzantine Atomic Broadcast service.The second contribution is a suite of algorithms, based on the previous BDLO implementations, that solve the Atomic Appends problem in the presence of asynchrony, Byzantine clients and Byzantine servers. This problem occurs when clients have a composite record (set of basic records) to append to different BDLOs, in such a way that either each basic record is appended to its BDLO (and this must occur in good circumstances),or no basic record is appended. Distributed algorithms are presented, which solve the Atomic Appends problem when the clients (involved in theAtomic Appends) and the servers (which maintain the BDLOs) may be Byzantine.
A Voting Ensemble Approach for Hepatitis Disease Detection

The inflammation of the liver is termed as Hepatitis. Several different types of hepatitis are from A to G. For example, Hepatitis A is caused by the hepatitis A virus. Similarly, other type of Hepatitis virus is formed by the name, say Hepatitis G. Some types of virus will not create any serious problems. Long-lasting and cause scarring of the liver, loss of liver function and in some cases, liver cancer are also caused by this disease. Voting ensemble based approach is proposed in this paper as final phase classification that accepts top two classifier models obtained from first and second phase classification respectively. The reason of using the proposed classifier is to enhance the prediction performance so that patients with hepatitis disease are identified correctly.