Miracle-dz/UniFAR-FTUs huggingface dataset:
Differences in Regional Brain Activities during Memory Acquisition Depending on Individual Working Memory Capacity

Individual capacity of recall memory varies greatly even among healthy young adults. Nevertheless, the difference in brain circuitry underlying varied memory capacity has yet to be fully investigated. We acquired electroencephalographic measurements from 43 healthy young adults while performing a demanding working memory task and studied the changes in regional cortical activity in relation to different levels of memory performance. The memory task involved sequentially presenting seven arrow pictures to a participant during the encoding period, who was then asked to recall the direction of one of the arrows in the sequence within the retrieval period. We divided the participants into three groups of high, intermediate, and low performance based on the weighted hierarchical grouping method. Regional brain activities were source-localized using multiple sparse priors method in the highand low-performance groups, and group differences were determined by non-parametric permutation tests. Our ndings showed that participants with higher memory performance exhibited wider distribution of cortical activity including the prefrontal and parieto-posterior cortices, whereas lower performance participants only exhibited stable activations across occipital regions. The results implied the importance of selective attention in order to attain optimal individual working memory performance. Furthermore, we suggest the potential role of the angular gyrus as an interplay between the prefrontal and posterior regions for the management of stimulus ow and signal control. Future works should focus on conducting more thorough connectivity analysis to investigate the relationship of cortical activations with individual working memory performance.
Power MOSFET Intrinsic Diode as a Highly Linear Junction Temperature Sensor

The characteristics of a thermo-sensitive electrical parameter used to estimate the junction temperature of power MOSFETs are presented. In particular, the dependence on temperature of the voltage appearing across the forward-biased body-diode at fixed currents is carefully investigated experimentally in order to optimize linearity and sensitivity. Error, resolution and repeatability are also discussed. The intrinsic diodes have been characterized in a wide working temperature range, namely between 25 °C and 175 °C, and for 1000 fixed probe currents between 10 $\mu \text{A}$ and 10 mA. The results show that the temperature sensor has high sensitivity and high linearity. It is shown that the best trade-off between sensitivity and linearity can be obtained in a particular bias current range. Finally, the sensor long-term stability has been tested.
Wear-Out Condition Monitoring of IGBT and mosfet Power Modules in Inverter Operation

In this article, a condition monitoring system for the degradation assessment of power semiconductor modules under switching conditions is presented. The proposed monitoring system is based on the online measurement of two damage indicators: the on-state voltage of the semiconductor and the voltage drop in the bond wires. The on-state voltage of a semiconductor can be employed for temperature estimation, in order to anticipate failures in the solder joints that increase the thermal resistance of the cooling path. Moreover, by measuring the voltage drop in the bond wires, the degradation of the bond wires can be detected. The described monitoring system has been implemented in an inverter prototype, and tests have been performed in different scenarios to verify its capabilities in healthy and degraded states. Furthermore, a monitoring routine has been proposed in order to perform the required measurements in high switching frequency applications.
Application of Nature-Inspired Algorithms for Sensing Error Optimisation in Dynamic Environment

Spectrum sensing errors in cognitive radio may occur due to constant changes in the environment like changes in background noise, movements of the users, temperature variations, etc. It leads to under usage of available spectrum bands or may cause interference to the primary user transmission. So, sensing parameters like detection threshold are required to adapt dynamically to the changing environment to minimise sensing errors. Correct sensing requires processing huge data sets just like Big Data. This chapter investigates sensing in light of Big Data and presents the study of the nature inspired algorithms in sensing error minimisation by dynamic adaptation of the threshold value. Death penalty constrained handing techniques are integrated to the genetic algorithm, particle swarm optimisation, the firefly algorithm and the bat algorithm. Based on them, four algorithms are developed for minimizing sensing errors. The reported algorithms are found to be faster and more accurate when compared with previously proposed threshold adaptation algorithms based on a gradient descend.
Work and Family-The Timing of Childbearing and Women''s Wages

A luminescent tube filled with a temperature responsive liquid which causes the tube to glow as the liquid moves up and down the tube is encased within an opaque expansible sleeve which is aligned with graduations on the tube to indicate a critical temperature to be sensed when the tube is mounted on an object, so that if the tube glows above the sleeve the temperature is readily discernable. The tube and sleeve may be permanently mounted on the object or removably mounted by a magnet or clip on the sleeve.
Heat Pipe Thermal Management Based on High-Rate Discharge and Pulse Cycle Tests for Lithium-Ion Batteries

A battery thermal management system (BTMS) ensures that batteries operate efficiently within a suitable temperature range and maintains the temperature uniformity across the battery. A strict requirement of the BTMS is that increases in the battery discharge rate necessitate an increased battery heat dissipation. The advantages of heat pipes (HPs) include a high thermal conductivity, flexibility, and small size, which can be utilized in BTMSs. This paper experimentally examines a BTMS using HPs in combination with an aluminum plate to increase the uniformity in the surface temperature of the battery. The examined system with high discharge rates of 50, 75, and 100 A is used to determine its effects on the system temperature. The results are compared with those for HPs without fins and in ambient conditions. At a 100 A discharge current, the increase in battery temperature using the heat pipe with fins (HPWF) method is 4.8 °C lower than for natural convection, and the maximum temperature difference between the battery surfaces is 1.7 °C and 6.0 °C. The pulse circulation experiment was designed considering that the battery operates with a pulse discharge and temperature hysteresis. The depth of discharge is also considered, and the states-of-charge (SOC) values were 0.2, 0.5, and 0.8. The results of the two heat dissipation methods are compared, and the optimal heat dissipation structure is obtained by analyzing the experimental results. The results show that when the ambient temperature is 37 °C, differences in the SOC do not affect the battery temperature. In addition, the HPWF, HP, and natural convection methods reached stable temperatures of 40.8, 44.3, and the 48.1 °C, respectively the high temperature exceeded the battery operating temperature range.
Direct Torque Control for Three-Phase Open-End Winding PMSM With Common DC Bus Based on Duty Ratio Modulation

This article introduces the classical direct torque control (DTC) to a three-phase open-end winding permanent magnet synchronous motor with common dc bus for the first time. The electromagnetic torque and the stator flux are controlled at the same time. However, the zero-sequence current is not suppressed, and the ripples of the electromagnetic torque and stator flux are large. To improve the operation performance of this drive system, a DTC based on a duty ratio modulation (DRM-DTC) is proposed. First, a deadbeat zero-sequence current controller is proposed in the DRM-DTC to suppress the zero-sequence current. Second, another strategy, which is based on a graphical analysis method and a simple deadbeat direct torque and flux controller, is proposed to optimize the duty ratio of the active voltage vector. Thus, the electromagnetic torque and stator flux ripples can be reduced. Finally, an optimized pulsewidth modulation implementation strategy is proposed in the DRM-DTC to further reduce the switching frequency of inverters. The classical DTC and the proposed DRM-DTC are compared through simulation and experiment, and the results verify the effectiveness of the proposed strategy.
A 0.5 V 10-bit 3 MS/s SAR ADC With Adaptive-Reset Switching Scheme and Near-Threshold Voltage-Optimized Design Technique

This brief presents a 10-bit ultra-low power energy-efficient successive approximation register (SAR) analog-to-digital converter (ADC). A new adaptive-reset switching scheme is proposed to reduce the switching energy of the capacitive digital-to-analog converter (CDAC). The proposed adaptive-reset switching scheme reduces the average switching energy of the CDAC by 90% compared to the conventional scheme without the common-mode voltage variation. In addition, the near-threshold voltage (NTV)-optimized digital library is adopted to alleviate the performance degradation in the ultra-low supply voltage while simultaneously increasing the energy efficiency. The NTV-optimized design technique is also introduced to the bootstrapped switch design to improve the linearity of the sample-and-hold circuit. The test chip is fabricated in a 65 nm CMOS, and its core area is 0.022 mm2. At a supply of 0.5 V and sampling speed of 3 MS/s, the SAR ADC achieves an ENOB of 8.78 bit and consumes $3.09~{\boldsymbol{\mu }}\text{W}$ . The resultant Walden figure-of-merit (FoM) is 2.34 fJ/conv. -step.
A Novel Configuration of Cross-Switched T-Type (CT-Type) Multilevel Inverter

This article introduces a novel configuration of multilevel inverter (MLI) with low number of power electric components. The inverter is a combination of two back to back T-type modules using two cross-connected switches. This inverter can operate using dc sources having either same or different voltage ratings. The proposed inverter can also be extended using cascaded connection to obtain higher voltage levels. This MLI and its extensions are suitable for other applications where high voltage is required. The major feature of this MLI is the formation of negative voltage levels without using any H-bridge circuit. Some other advantages of this MLI are low total harmonic distortion and highly efficient output voltage. A low-frequency modulation technique known as nearest level control is applied to produce the high-quality output voltage. The simulation was done using MATLAB/Simulink, while the hardware prototype is build using TMS320F28335 digital signal processor. The performance of the proposed MLI is validated by obtaining the accurate simulation and experimental results.
A Traffic Prediction Enabled Double Rewarded Value Iteration Network for Route Planning

Effective route planning is the key to improving transportation efficiency. By leveraging the in-depth knowledge of road topology and traffic trends, experienced drivers (e.g., taxi drivers) can usually find near-optimal routes. However, existing online route planning services can hardly acquire this domain knowledge, so they just provide the fastest/shortest route based on current traffic conditions. These seemingly optimal routes may attract numerous vehicles and then become extremely congested. To solve this problem and actually improve transportation efficiency, we propose a double rewarded value iteration network (VIN) to fully learn the experienced drivers’ routing decisions, which are based on their implicitly estimated traffic trends. First, the global traffic status and routing actions are chronologically extracted from large-scale taxicab trajectories. Then, to model the knowledge of traffic trends, a long short-term memory network is trained. Being expert at learning long-term planning involved functions, the VIN is utilized to model the policy function from both current and predicted future traffic status to an experienced driver's routing action. Finally, the performance of our proposed model is evaluated on real map and taxicab trajectories in Beijing, China. The experimental results demonstrate that the proposed model can achieve human like performance in most cases, with high success rate and less commuting time.
Examination of The Influence of Leadership Integrity Provision of Holistic Training on Student-Teachers in Public Primary Teachers Training Colleges

Leadership practices influence the education system in any society. Integrity being a core value in leadership has a great effect on educational issues that influence people and their environmental interactions. The study examined influence of leadership integrity on provision of holistic training on student-teachers in public Primary Teachers Training Colleges (PTTCs). The study adopted a mixed methodology and an explanatory design. Out of a target population of 2061 participants, a sample size of 633 respondents ( 30% of two groups -student-teachers and lecturers and a total of 21 respondents of other groups drawn from the offices as whole independent units: principals, Deputy principals, BOM chairmen, Deans and the student-leaders) participated in the study. The study revealed that there is indeed lack of leadership integrity on provision of holistic training on studentteachers in the public PTTCs leading to the lack of inculcation of transparency and accountability skills into the graduates. This led to reduced ethics and poor performance on duty performances of the teacher-students. The study therefore recommended that the student-teachers be trained as teachers of integrity who would prepare pupils in the primary schools as conscious and cohesive national citizens capable of facing global challenges courageously.
A Comparison Study on Coupling Effects in Balance Control Methods of Humanoid Robots through an Extended Task Space Formulation

Even though several control methods on the task space dynamics of humanoids have been proposed, they cannot cover the entire dynamics of the system since there are hidden null space dynamics due to kinematic redundancy. Besides, there are few studies on the coupling effects between task space and null space dynamics. Through an extended task space formulation, the coupling effects between each space are manifested because this form allows representing the entire system dynamics. Moreover, by using an adequate selection of weighting matrices, the coupling effects can be inertially decoupled. Regarding the effectiveness of the decoupling process, two whole-body control approaches and provide their mathematical comparisons is proposed. A kinematically decomposed control approach without the decoupling process is first introduced, and its extension to an inertially decoupled control approach is then developed. Furthermore, conventional operational space-based control is discussed to compare the above control approaches. This paper constructs a mathematical analysis of their relationships. Finally, simulation results are given in this paper to demonstrate the validity of the mathematical analysis.
Understanding online review helpfulness in omnichannel retailing

Purpose As retailers have increasingly embraced an omnichannel retailing strategy, explaining and predicting the helpfulness of online review should consider both online-based and offline-based reviews. The paper aims to discuss this issue. Design/methodology/approach Based on the signaling theory, this study intends to examine the impacts of review-related and reviewer-related signals on review helpfulness in the context of omnichannel retailing. The proposed research model and corresponding hypotheses were tested by using negative binomial regression. Findings The results shown that both review-related (review rating and review sentiment strength) and reviewer-related (reviewer real name and reviewer expertise) signals positively affect review helpfulness. Contrary to the authors’ expectations, review length negatively affects review helpfulness. Specifically, when the review submitted from an omnichannel retailer’s offline channel, the positive impacts of reviewer real name on review helpfulness will be stronger, and the positive impacts of reviewer expertise on review helpfulness will be weaker. Originality/value Unlike many previous studies tend to explore the antecedents of review helpfulness in a single-channel setting, the study examined the factors that affect review helpfulness in an omnichannel retailing context.
Designing an Advanced Electrical Motor for Propulsion of Electric Aircraft

A prototype motor rated for 500 kW 3,000 rpm has been developed for aircraft electric propulsion. The design of the motor was optimized using a coupled parameter problem of electromagnetic, mechanical and thermal performances. A high power density of over 5 kW/kg is demonstrated without resorting to intensive direct liquid cooling. The design process considered variables including the winding conductor type, pole/slot combination, dimensions, winding layout and power electronics requirements. The final chosen design is a $3\times 3$-phase 30-pole 36-slot surface permanent magnet motor with Cobalt-Iron laminations, Sm2Co17 Halbach array magnets and litz wire for an optimum performance.
Utilizing Upper Arm Images in Determining Body Mass Index and Nutritional Status

Body mass index (BMI) is the most widely used index for determining the fitness status of an individual. Midd-upper arm circumference (MUAC) is another commonly used anthropometric index, providing a simple measurement widely used for nutrition level screening. However, building a massive population database based on both BMI and MUAC measurements is time-consuming and may introduce errors due to instrumentations and different operators. In this paper, a measurement technique of BMI from photographic images of the upper arm is presented. Three parameters are measured from the subject photos with a scale attached, and these are upper arm length, sagittal plane middle arm thickness (SMT), and frontal plane middle thickness (FMT). Different parameters are derived from the SMT and the FMT. These parameters are used to study the correlation and measurements agreements with the BMI. It is found that all parameters related to SMT correlate very well with the BMI with correlation coefficients of more than 90%. In addition, the SMT measurement limits (both upper and lower) are acceptable and within the clinical significance range. Finally, the receiver operating characteristics analysis of both SMT and MUAC has been evaluated. The findings show that SMT is slightly better than MUAC since it gives excellent sensitivity (94.7%) without compromising the specificity (88.5%) when compared to the MUAC results.
The Relationship between Fitness and Marksmanship in Police Officers

Police officers may be required to discharge their weapon under physical duress. The purpose of this study was to investigate the relationship between fitness and marksmanship to facilitate future strategies to improve marksmanship. Retrospective data were provided for thirty-four police officers (mean age = 40.48 ± 6.66 years: mean weight = 100.60 ± 19.82 kg: mean height = 180.42 ± 6.87 cm) from a US-based law enforcement agency. Data included four different fitness measures and three different shooting scenarios. No significant relationship was observed between the three different shooting scenarios. There was a significant relationship between shuttle run and static shoot (r = 0.528, p = 0.002), grip strength and the dynamic scenario (r = −0.367, p = 0.035) and leg strength and the positive identification scenario (r = 0.344, p = 0.050). This study demonstrated that a high variety of fitness training and marksmanship practice, under various occupational scenarios, may be required to ensure optimal police shooting accuracy whilst in the field.
Fast Emotion Recognition Based on Single Pulse PPG Signal with Convolutional Neural Network

Physiological signals contain considerable information regarding emotions. This paper investigated the ability of photoplethysmogram (PPG) signals to recognize emotion, adopting a two-dimensional emotion model based on valence and arousal to represent human feelings. The main purpose was to recognize short term emotion using a single PPG signal pulse. We used a one-dimensional convolutional neural network (1D CNN) to extract PPG signal features to classify the valence and arousal. We split the PPG signal into a single 1.1 s pulse and normalized it for input to the neural network based on the personal maximum and minimum values. We chose the dataset for emotion analysis using physiological (DEAP) signals for the experiment and tested the 1D CNN as a binary classification (high or low valence and arousal), achieving the short-term emotion recognition of 1.1 s with 75.3% and 76.2% valence and arousal accuracies, respectively, on the DEAP data.
A New Synchronous DG Model for Unbalanced Multiphase Power Flow Studies

This paper describes a new steady-state model to represent the synchronous machines, generators or motors, in unbalanced power flow studies. Also some power and voltage controls, which can be applied in the machines, are modeled. The groundings of the synchronous machines can be represented. Most power flow studies represents the synchronous machines in a very simplified way, such as conventional fixed power injections in a bus (PQ bus) or as a voltage controlled bus (PV bus). This representation can present good results for power flow studies in balanced electrical systems, but in unbalanced electrical systems can lead to considerable errors due to particularities of the electromechanical behavior of the machine. In the proposed model, it is possible to represent the internal losses of the machines, an internal voltage source in phase-domain, defining the internal voltage module and a fixed angular difference between phases. The controls developed allow to specify the three-phase active and reactive power demanded or consumed by the machine and to control the voltage in a bus in different ways, dependent on how the control systems are in practice. The model was applied to the IEEE13, IEEE34, IEEE123, and IEEE8500 test feeders, and proved to be robust and more accurate than conventional models in situations of imbalance.