Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of driver behaviour's influence in urban traffic flows

Urban traffic is generally getting more congested every passing year. Failure to implement sustainable measures in many cities leads to increased congestion and huge delays, causing drivers' nervousness and tendency to disobey traffic rules. This may have an influence on general traffic, as, for example, a car that force the entrance in a junction may cause other vehicles to be in the impossibility of continuing their travel, even when having priority of passage. In this article the behaviour of drivers is analysed, while estimating the probability of aggressive behaviour occurrence in different scenarios. Measurements have been made in the city of Bucharest, both in signalized and unsignalized road junctions, during peak hours or in light traffic, to be able to compare different patterns and estimate the probability of occurrence.
An Adjustable Magnetic Preloading and Stepping Controlled Piezoelectric Traveling-Wave Ultrasonic Micromotor

A piezoelectric traveling-wave ultrasonic micromotor at the millimeter scale with adjustable magnetic preloading and precise stepping control is proposed. This micromotor consists of a well-designed annular stator of 4 mm in diameter and an innovative rotor preloading mechanism using magnetic attraction, which is first achieved in such a small system. With adjustable magnetic preloading and 10-V AC actuating voltage, the maximum speed reaches 9900 rpm and a maximum torque of $37.0~\mu $ Nm is obtained. Stable startup characteristic and accurate stepping control are also achieved. The minimum stepping angle of the micromotor is 10°, and the deviation is less than 7%. An approximately linear relationship between the stepping angles and preloading forces is proved as well. Therefore, the adjustable magnetic preloading provides a completely new access for the increased torque generation and precise motion control for the micromotor.
Hubungan self efficacy dengan pencapaian akademik mahasiswa Fakultas Kedokteran Universitas Tarumanagara

Self efficacy adalah hasil proses kognitif berupa keputusan, keyakinan, atau pengharapan seorang individu terhadap kemampuannya untuk melakukan suatu tindakan atau mencapai hasil kinerja tertentu. Self efficacy merupakan salah satu faktor penting yang dapat mempengaruhi pencapaian akademik mahasiswa. Belum banyak ditemukan studi tentang hal ini di Indonesia terutama di Fakultas Kedokteran. Tujuan studi ini untuk mengetahui hubungan antara self efficacy dengan pencapaian akademik pada mahasiswa Fakultas Kedokteran Universitas Tarumanagara. Studi ini merupakan studi analitik dengan metode potong lintang pada 93 mahasiswa Fakultas Kedokteran Universitas Tarumanagara. Data diperoleh dengan menggunakan kuesioner Academic Self Efficacy Scale yang telah tervalidasi dan di analisis dengan uji Fisher Exact. Hasil studi didapatkan tingkat self efficacy sedang pada 78 (38,9%) mahasiswa dan tinggi 15 (16,1%) mahasiswa. Pencapaian akademik (IPK) 14 dari 15 mahasiswa (93,3%) yang memiliki IPK baik dengan self efficacy tinggi, sementara 69 dari 78 (88,4%) mahasiswa dengan IPK yang baik dengan self efficacy sedang, dengan p = 0,494 (p>0,05). Kesimpulan studi ini adalah tidak terdapat hubungan bermakna antara self efficacy dengan pencapaian akademik pada mahasiswa Fakultas Kedokteran Universitas Tarumanagara.
Low-Latency K-Means Based Multicast Routing Algorithm and Architecture for Three Dimensional Spiking Neuromorphic Chips

As the scale of Spiking Neural Networks (SNNs) grows, the inter-neuron connection problem becomes one of the major design considerations of SNN-based hardware. To deal with this issue, many researchers have studied Network-on-Chips (NoCs) with tree-like topologies to easily support one-to-many communication method in SNNs. However, such network suffers from high congestion, especially under the bursting activity of SNNs. In this paper, we introduce a novel multicast routing algorithm and 3D-NoC architecture for spiking neuromorphic chips. The proposed routing method alleviates the congestion of the overall SNN system by adopting a K-means clustering scheme, which divides the network into balanced partitions. The proposed algorithm, named KMCR, is integrated into our 3DNoC-SNN1 system and was validated based on an RTL-level implementation, while the area/power analysis is performed using 45-nm CMOS technology. The experimental results show that the proposed algorithm achieves about 14.43% lower latency and 24.5% higher throughput when compared to the XYZ-unicast multicast for 3D-NoC configuration. Furthermore, the system achieves 8.7% higher spike injection rate when compared to other exiting works.
Optimization algorithm for passive source localization

This paper proposes and evaluates by numerical simulation a hybrid algorithm that combines global and local optimizations for the problem of localizing an unknown source. Coherent observations of the signal at distributed sensors result in a highly multimodal function. The algorithm is designed to find the global peak of this function efficiently and accurately. The algorithm starts as a deterministic global optimization algorithm known as DIRECT (DIviding RECTangles). With DIRECT, a lower bound is found to the unknown function over increasingly smaller intervals. When the search interval reaches the scale of the carrier wavelength, the global search switches to a local search. It is shown that this approach speeds up convergence by a factor of two compared to DIRECT, and by many orders of magnitude compared to an exhaustive grid search.
A Compact V-Band Upconversion Mixer With −1.4-dBm OP1dB in SiGe HBT Technology

This letter presents a compact and linear V-band upconverting double-balanced Gilbert cell mixer implemented in a <inline-formula> <tex-math notation="LaTeX">$0.13-\,\mu \text{m}$ </tex-math></inline-formula> SiGe BiCMOS technology. The detailed design procedure for the on-chip transformer baluns is provided, which enables the compact implementation. The mixer occupies an area of <inline-formula> <tex-math notation="LaTeX">$365\,\,\mu \text{m}\,\,\times 400\,\,\mu \text{m}$ </tex-math></inline-formula> with pads and <inline-formula> <tex-math notation="LaTeX">$175\,\,\mu \text{m}\,\,\times 300\,\,\mu \text{m}$ </tex-math></inline-formula> without pads, consuming 52 mW from a 2.5-V power supply. The mixer achieves an OP1dB of −1.4 dBm at 60-GHz radio frequency, intermediate frequency (IF) bandwidth of 0.5–8.5 GHz on both sidebands, a maximum conversion gain of 13.4 dB, and a 3-dB bandwidth of 50 to above 67 GHz. The performance of the proposed mixer outperforms other state-of-the-art V-band mixers in terms of chip area, IF bandwidth, and linearity.
Resource Allocation for Full-Duplex Systems With Imperfect Co-Channel Interference Estimation

In-band full-duplex (FD) systems have been widely studied because they can double the spectral efficiency (SE) compared with conventional half-duplex (HD) systems, theoretically. However, inherent interference caused by both self-interference (SI) and co-channel interference (CCI) makes FD systems to achieve theoretical SE hard. In this paper, we propose a CCI estimation and cancellation (CCI-EC) protocol for the FD systems to overcome performance degradation due to CCI. We suggest to use a coherence channel block for two phases: CCI channel is estimated at a downlink (DL) user through uplink (UL) pilot signals in the first phase, then a base station (BS) and a UL user transmit their data simultaneously in the second phase, in which a DL user cancels interfering signals from a UL user by utilizing the estimated CCI channel information. We analyze the achievable SE of FD systems with CCI-EC and formulate a resource allocation problem to maximize it, where resource includes pilot and data transmission time, and transmit power of a BS and a UL user. A closed-form optimal power allocation for UL pilot and data transmissions and a suboptimal power allocation for DL data transmission are provided. The simulation results show that FD systems with the proposed CCI-EC achieve near-optimal achievable SE and outperform the conventional HD systems and FD systems without CCI-EC in terms of the achievable SE. Especially, the SE gain achieved by the proposed CCI-EC protocol in FD systems is remarkable under severe interference environment.
Mission Profile Based Reliability Evaluation of Capacitor Banks in Wind Power Converters

With the increasing penetration of wind power, reliable and cost-effective wind energy production is of more and more importance. The doubly-fed-induction-generator-based turbine system is widely used and dominates the wind market. In this paper, an analytical approach to assess reliability for power capacitors, both the dc-link capacitor bank and ac-side filter capacitor bank, is presented considering the annual mission profile. Based on the electrical behavior at various loading conditions, the lifecycle of the single power capacitor can be predicted through its electrothermal stresses. This percentile lifetime can be translated to the Weibull lifetime distribution of the power capacitor by considering the parameter uncertainties and tolerance variations. Thereafter, a reliability block diagram is used to bridge the reliability curves from the component-level of the individual capacitor to the system-level of the capacitor bank. A case study of a 2-MW wind turbine shows that the lifecycle is significantly reduced from the individual capacitor to the capacitor bank, where the dc-link capacitor bank dominates the lifetime consumption. Furthermore, the electrical stresses of the power capacitors are experimentally verified at a down-scaled 7.5 kW prototype.
LA PRECISIÓN DEL RECUERDO DE PATRONES DE JUEGO EN JUGADORES INFANTILES (SUB-13 AÑOS) DE BALONMANO [The recall accuracy of play patterns in handball players (U-13)]

The aim of the study was to address whether the skill to recall play patterns in handball was influenced by the temporal period in which those actions were perceived by the players. The sample of participants was seven U-13 federated handball players. The participants had to observe different play actions of a competition match played previously, and then, they had to judge how these actions ended. The recall tests were performed 1 day (1st test), 15 days (2nd test), and 30 days (3rd test) after the match. Specifically, the players perceived a set of 18 representative play actions, including 6 trials for each test. They had 30 seconds to recall how the play actions finished, selecting one option between several ones available on an observation sheet created specifically for this study. The players decreased their performance recalling the end of the play patterns as more time elapsed since the date that they played the match and the recall test. For example, their recall was significantly worse in the third test compared to the second and the first tests. Keywords: Perceptual-cognitive ability; recall; decision-making; handball.
Tunable Contact Conditions and Grasp Hydrodynamics Using Gentle Fingertip Suction

Gentle suction flow at the fingertips of a compliant hand can enhance object acquisition and increase the robustness of pinch grasps under water. The approach adds a low-pressure pump and flexible tubes that terminate at the distal phalanges. The light flow rate does not create a powerful suction force, nor does it stir up significant sediment. The method works on porous and rough objects in addition to smooth objects as it does not require forming a seal. It changes contact conditions—normal force and coefficient of friction—and enlarges the acquisition region when grasping free objects under water. A simple hydrodynamic model matches empirical force measurements adequately for incorporation in a dynamic simulation to explore the effects of flow rate and object mass. Simulations and experiments show that effects of fingertip suction flow are most pronounced for acquiring objects on the order of 1 kg or less and when pinching large objects. Gentle suction flow is an effective, versatile, and convenient addition for robots that must grasp and manipulate objects under water.
The Feasible Job Scheduling Algorithm for Efficient Resource allocation Process in Cloud Environment

Virtualized environment is the most important emerging area now a day's. It is advisable not to buy the required resources for a specific period of time. Especially small startup companies and some other companies also. Instead of buying these resources for a single time usage, virtualized environment provides the platform for user requirement. In the cloud environment, it is important to check the availability of the resources and keep on monitoring the performance analysis of the overall allocation of resources for all user requests. Because, usage of cloud is getting increased day by day. So the CSP (Cloud Service Provider) should assure the sophisticated user experience to maintain SLA by ensuring the availability and efficiency of the resource consistently. Allocation of resource for a user request is the most important task in this process. In order to enhance the overall system performance and boost the process of resource allocation, varieties of algorithms are being proposed by the researchers. In this proposed work, We have designed an effective job scheduling mechanism based on the size of the job request and arrival time of the same. By the analyzed method some efficiency improvement is archived in resource allocation task, through which the overall system performance is boosted.
Correlation of the Formants of the Romanian Vowels

Although interest has been shown in the literature for the study of the correlation and the analysis of the language phraseological elements, no research has focused mainly on the correlation of the formants of the vowels in the Romanian language. The purpose of the current study is to analyze the correlation elements noticed during the sustained pronunciation of vowels and in short sentences. The applicability of the results consists in the possibility of extrapolating the results in order to the correct pronunciation, the analysis of the naturalness of synthesized speech, and for the recognition of emotions.
Maximum Energy Efficiency of Three Precoding Methods for Massive MIMO Technique in Wireless Communication System

Nowadays, Energy Efficiency (EE) has turned into a buzzword for 5G. Consequently, Massive MIMO (MMIMO) technologies have attained a great attention for Multi-User Communication scenario. In this paper, the Minimum Mean Square Error (MMSE), the Maximum Ratio Transmission (MRT) and the Zero Forcing (ZF) precoding methods are analyzed for MMIMO technique from an EE perspective. The results show the optimization of EE against the amount of clients, amount of assigned base stations as well as launch input power in the system respectively.
Real-Time Speaker Independent Isolated Word Recognition on Banana Pi

Devices controlled with voice commands have gained popularity over the last decade. To recognize an utterance, they usually require an internet connection, or use commercial programming libraries. Therefore, their flexibility is low, and algorithm update opportunities are limited. In this study, a speaker independent isolated word recognition algorithm, embedded in a single board computer, is proposed to recognize utterances in realtime. The proposed system neither requires an internet connection, nor uses external libraries. Mel Frequency Cepstral Coefficients and their deltas are used as feature vectors. Gaussian mixture models are utilized to define word models. Digits and some confirmation words of Turkish language are recorded ten times in one session from twenty-four individuals. Seven of these records are used for training, and the others for testing the system. The off-line experimental results showed that the system is working with 99.98%. In real-time experiments, the system's recognition accuracy was proficient for controlled environments.
A Precise Wavenumber Domain Algorithm for Near Range Microwave Imaging by Cross MIMO Array

An electronically large planar antenna with wideband illumination retrieves 3-D microwave image with high resolution. Cross multi-input-multi-output (MIMO) topology is commonly used to produce the effective planar array at a reasonable cost and complexity. However, the imaging algorithm for effective monostatic array will cause distortion and dispersion in near range imaging applications. In this paper, an efficient and precise algorithm for near range imaging by cross MIMO array is proposed. The integrals over the transmitting and receiving arrays are carried out in the wavenumber domain to improve efficiency. No approximation is made to further decouple the space and wavenumber variables so the reconstructed image precisely retains both intensity and phase information. The algorithm achieves the same imaging quality as the back-propagation algorithm at the computation complexity of O(<inline-formula> <tex-math notation="LaTeX">$N^{4}$ </tex-math></inline-formula>lg<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>). It can also be implemented to boundary arrays by coherent subarray superposition. Experiments using both simulated and measured data verify its performance. The point spread function and resolution of cross MIMO topology are discussed based on the images reconstructed by this algorithm using measured data.
A Dynamic Selection Approach for Quality Control Mechanisms in Crowdsourcing

Crowdsourcing has emerged as a new model for leveraging human knowledge and intelligence toward accomplishing tasks that are difficult to fulfill effectively with machines alone. However, owing to its open nature, quality control is a big challenge. Current crowdsourcing systems use one or two standard mechanisms for evaluation and quality control of a task, regardless of its type. In this paper, we propose a dynamic approach that exploits task-quality ontology to select the most suitable quality control mechanism (QCM) for a given task based on its type. The proposed approach has been enriched by a reputation engine that collects requesters’ feedback on the performance of QCMs. Accordingly, QCMs and tasks were automatically matched using the underlying categorization structure of tasks on one side and the reputation scores of QCMs on the other side. Our experiments establish that our proposed dynamic approach yields better results compared to existing approaches.
Modeling and Designing a Genetically Optimized PID Controller for Separately Excited DC Motor

This paper presents an intelligent method to design a proportional-integral-derivative (PID) controller to control the speed of a separately excited DC motor (SEDCM). There are various artificial intelligent (AI) based proposed methods for tuning the parameters of a PID controller. Genetic Algorithm is a powerful optimization tool used to optimize several parameters from the given population based on natural evolution. The purpose of this paper is to obtain the suitable speed characteristics of a SEDCM by optimizing the transient response i.e. by minimizing the settling time, overshoot and the rise time using genetic algorithm (GA). In this method, integral of absolute error (IAE) is taken as the cost function. The GA optimized PID controller shows better performance with respect to settling time, rise time and percentage of overshoot than other conventional methods and adaptive fuzzy PID controller.
Thermoelectric Transport Modeling Based on Neural Computation

Analytical and neural network models for the thermoelectric transport in Bi2Te3 are presented with non-parabolic band effects’ consideration. The analytical model is newly formulated by using the Boltzmann transport equation, and the artificial neural network (ANN) models are employed for the computational integration of the thermoelectric coefficients. In order to incorporate the realistic band structures in Bi2Te3 materials, the integrand of the thermoelectric coefficients is simulated by using both the integration of ANN and the radial basis function ANN (RBF-ANN). It is found that the RBF-ANN model has a good performance for predicting the thermoelectric transport.
Angular Parameters Estimation of Multiple Incoherently Distributed Sources Generating Noncircular Signals

In this paper, we introduce for the first time a new method for the estimation of the angular parameters [i.e., central directions of arrival (DOAs) and angular spreads] of multiple non-circular and incoherently-distributed (ID) sources. The new method is derived by going through three different stages to finally obtain a robust solution that allows decoupling the estimation of each central DOA from its associated angular spread by means of two consecutive 1-D searches. By doing so, we reduce significantly the complexity of the proposed technique as compared to the brute-force 2D grid search solution. This new technique is also oblivious to the sources’ angular distribution or any mismatch thereof. By analyzing its performance, we show that our new estimator outperforms most well-known state-of-the-art techniques in terms of estimation accuracy and robustness, especially for small DOA separations and/or low SNR levels. We also derive an explicit expression for the stochastic Cramér–Rao lower bounds (CRLBs) of the underlying estimation problem. These CRLBs are compared to those for circular ID signals. It will be shown that the noncircularity of the signals is more informative about the angular parameters when the sources have different angular distributions and/or when the angular spreads increase. Besides, the noncircular CRLBs depend on the noncircularity rate, the noncircularity phase separation, and the DOA separation.
IMDD Transmission at Net Data Rate of 333 Gb/s Using Over-100-GHz-Bandwidth Analog Multiplexer and Mach–Zehnder Modulator

We demonstrate intensity-modulated direct-detection optical transmission at a record-high data rate with single wavelength and single polarization. The high data rate is achieved with simple optics by using electronic and electrooptic devices with large operation bandwidths. We use a digital-preprocessed analog-multiplexed digital-to-analog converter with a >100-GHz analog multiplexer (AMUX) to drive an 80-GHz Mach–Zehnder optical modulator (MZM). The AMUX is based on 0.25-μm-emitter-width InP heterojunction bipolar transistor technology, and the MZM has InP n-i-p-n heterostructure optical waveguides with capacitance-loaded travelling-wave electrodes. We employ discrete multi-tone modulation controlled by a margin-adaptive bit-loading algorithm. In the experiment, the signal was transmitted over a 20-km dispersion-compensated single-mode fiber link and received by a single photodiode followed by a digital signal processor including a nonlinear equalizer. At a gross bit rate of 400 Gb/s, the bit error rate of the received signal was below the threshold of 20% overhead soft-decision forward error correction code. This result corresponds to a net data rate of 333 Gb/s.