Деякі життєві навички баскетболісток на візках

Purpose: the current study aimed to know the level of life skills of female wheelchair basketball players and statistical differences in the life skills of female wheelchair basketball players according to team affiliation. Material & Methods: the study was conducted on female wheelchair basketball players, where the study sample amounted to 30 players. The life skills scale prepared by Al-Sutri (2007), which contains four dimensions, was adopted; the skill of communication, the skill of teamwork and cooperation, the skill of taking personal responsibility, and the skill of physical and technical. Results: the results showed that the mean values of the life skills dimensions ranged between (3.40 and 4.18), and the mean value of the total score of the scale amounted to (3.80), which indicates there were a high degree of life skills. And there were no significant differences between female wheelchair basketball players according to team affiliation in the life skills. Conclusions: it was found that the level of life skills of female wheelchair basketball players is high. It is very important to develop special sports programs that enhance the life skills of persons (male/female) with disabilities, considering the type and severity of the disability.Мета: дане дослідження спрямоване на вивчення рівня життєвих навичок баскетболісток-візочниць та статистичних відмінностей у життєвих навичках баскетболісток-візочниць залежно від взаємодії в команді. Матеріал та методи: дослідження проводилося на баскетболістках-візочницях, вибірка складала 30 спортсменок. Було прийнято шкалу життєвих навичок, підготовлену Al-Sutri (2007), яка містить чотири виміри: вміння спілкуватися, вміння працювати в команді та співпрацювати, вміння брати на себе особисту відповідальність, фізичні та технічні вміння. Результати: отримані результати продемонстрували, що середні значення параметрів життєвих навичок перебували в діапазоні від (3,40 до 4,18), а середнє значення загального балу за шкалою становило (3,80), що вказує на високий рівень життєвих навичок. При цьому суттєвих відмінностей між баскетболістками-візочницями залежно від взаємодії у команді у життєвих навичках виявлено не було. Висновки: встановлено, що рівень життєвих навичок у баскетболісток-візочниць високий. Отримані результати дослідження продемонстрували необхідність розробити спеціальні спортивні програми, які покращують життєві навички людей з особливими фізичними потребами (чоловіки/жінки) з урахуванням типу та групи інвалідності

Wideband Endfire Antenna Array for 5G mmWave Mobile Terminals

In this paper, a compact endfire antenna array with low-profile, small clearance, and wideband operation is proposed for millimeter-wave (mmWave) fifth-generation (5G) mobile terminals. The wideband operation is achieved by exciting two identical bow-tie dipoles inserted on both sides of a multilayer substrate fed by an asymmetric open-end stripline to slotline transition. The antenna performance is significantly improved by introducing a set of vertical metallic vias. The proposed antenna element can achieve 29 % from 24.2 GHz to 32.4 GHz with a peak realized gain that varies from 3.5 dBi to 4.5 dBi. A linear 4-element antenna array is arranged and fabricated to verify the proposed antenna beamforming capabilities. The simulated and measured bandwidth achieves a wide range of 34.4 % (24-34 GHz) to support 26, 28, and 30 GHz 5G mmWave bands with an isolation level better than 20 dB and a peak realized gain over the interested bands ranging from 7.56 to 8.14 dBi. The simulated array scanning angle is ± 68 • at 28 GHz within 3-dB gain deterioration. Furthermore, the simulated spherical coverage has met the requirements of 3GPP standards which make the proposed antenna array a promising candidate to be integrated within mmWave 5G mobile devices. INDEX TERMS 5G, antenna array, beamforming, endfire, mmWave bands, mobile terminal, wideband

Effects of harmonics and voltage unbalance on the behavior of a five-phase permanent magnet synchronous machine

The development in industrial systems leads to the augmentation in the consumption of the power. Therefore, this development makes use of multiphase machines. The use of multiphase machines caused several problems and defects. Electrical energy is mainly distributed in a three-phase system to provide the electrical power necessary for the electrical engineering equipment and materials. The sinusoidal aspect of the required original voltage primarily preserves its essential qualities for transmitting useful power to terminal equipment. When the voltage waveform is no longer sinusoidal, perturbations are encountered, which generate malfunctions and overheating of the receivers and the equipment connected to the same electrical supply network. The main disturbing phenomena are harmonics, voltage fluctuations, voltage unbalances, electromagnetic fields, and electrostatic discharges. This present work aims to study the effects of harmonic pollution and voltage unbalance on the five-phase permanent magnet synchronous machine using spectrum current analysis and wavelet transform

Zgodnje odkrivanje okvar na zobniških prenosnikih z Morletovo valčno transformacijo

In recent days, supervision task of industrial systems is vital and the prediction of damages avoids many problems. If any system\u27 defects are not detected in early stage, this system will continue in degradation and may be causing serious economic loss. In the industrial systems, the defects change the behavior and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for early defect detection of a gear system is proposed. This approach is based on vibration analysis by trying to find defect\u27s signature in the vibration signal. This approach has used the Autocorrelation of Morlet Wavelet Transforms (AMWT). Firstly, the simulation validation is introduced. The validation of the approach on real system is given in the second validation part

Evaluation of Radio Communication Links of 4G Systems

Radio communication systems are very widely present in our current smart lifestyles. It consists of two ends, which can carry the transmitter’s information to the receptor. Before installing any radio communication system, it is necessary to analyze the link resources. Hence, this analysis allows the determination of the received radio communication strength to prove if it is sufficient for the link to work correctly and assure a high quality of service. For this reason, new services and technologies are integrated. The objective of the present work is to improve the performance of the radio communication link of 4G systems. The study is based on real measurements using the drive test. The data collected by the drive test are analyzed to increase the performance of the radio communication. Based on this data analysis, recommendations and suggestions are issued for improving the radio communication link. The obtained results indicate a significant amelioration in the performance of the radio communication link

Optimizing condition monitoring of ball bearings: An integrated approach using decision tree and extreme learning machine for effective decision-making

This article presents a study on condition monitoring and predictive maintenance, highlighting the importance of tracking ball bearing condition to estimate their Remaining Useful Life (RUL). The study proposes a methodology that combines three algorithms, namely Variational Mode Decomposition (VMD), Decision Tree (DT), and Extreme Learning Machine (ELM), to extract pertinent features and estimate RUL using vibration signals. To improve the accuracy of the method, the VMD algorithm is used to reduce noise from the original vibration signals. The DT algorithm is then employed to extract relevant features, which are fed into the ELM algorithm to estimate the RUL of the ball bearings. The effectiveness of the proposed approach is evaluated using ball bearing data sets from the PRONOSTIA platform. Overall, the results demonstrate that the suggested methodology successfully tracks the ball bearing condition and estimates RUL using vibration signals. This study provides valuable insights into the development of predictive maintenance systems that can assist decision-makers in planning maintenance activities. Further research could explore the potential of this methodology in other industrial applications and under different operating conditions