Miracle-dz/UniFAR-FTUs huggingface dataset:
Trajectory Planning With Lamé-Curve Blending for Motor-Saturation Avoidance Upon Mobile-Robot Turning

In order to avoid motor saturation in turning maneuvers, an iterative Lamé-trajectory planning scheme is proposed to generate a smooth curvature-bounded transition trajectory for a differential-driving wheeled mobile robot (DWMR) switching from one straight path to another. The scheme consists of Lamé-curve blending, inverse-kinematics computation, peak-torque positioning and torque-saturation avoidance. Firstly, a Lamé-curve blending procedure based on affine transformations, is formulated to generate a smooth $G^{2}$ -continuous transition trajectory for connecting two straight paths. Secondly, the platform twist is calculated according to the curvature of the Lamé-curve trajectory, then transformed into the actuated-joint rates by means of the inverse-kinematics model. Thirdly, a peak-torque positioning technique is developed to estimate the peak torques of the driving wheels when the DWMR tracks the trajectory, by combining the computed-torque method and the inverse-dynamics model. Finally, an iterative $r$ -step saturation-avoidance prediction planning strategy is devised to suppress the peak motor torques, by means of two torque limitation schemes via adjusting trajectory curvature and robot speed. The simulation results show that, compared with the conventional planning techniques for circular arcs, our trajectory planning scheme can generate a smooth saturation-free transition trajectory with feasible curvature and traveling speed. The scheme is significantly beneficial for trajectory tracking under finite actuation torque in turning maneuvers, thereby preventing any possible path deviation caused by insufficient torque.
Binaural Spatial Audiometry Screening Using Android Mobile Device Audio I/O Facility

Localization of acoustic sources among hearing impaired (HI) listeners is known to be less satisfactory than normal hearing (NH) listeners and their performance worsens in the presence of interfering sources or noise. However new hearing aids are developed to provide speech enhancement using multi-channel signal processing to preserve spatial cues in binaural presentation. In this work, we propose a methodology to evaluate spatial perception of listeners using a novel MUSHRA-like (MUlti Stimulus test with Hidden Reference and Anchor) experimental setup using an Android mobile phone. We evaluate multiple pre-recorded stimuli, presented randomly for their perceptual localization accuracy, relative to explicitly presented spatial references. The test implemented on Android mobile platform and bluetooth earplugs, along with a variety of directional interference stimuli, provides for the test to be administered at any remote location, without the necessity of expensive clinical facilities. We also propose schemes for different methods of rendering binaural audio for further mobile phone based hearing assistance.
Efficient Integration of Logical Topology Design and Survivable Traffic Grooming for Throughput Enhancement in WDM Optical Networks

Optical networks that employ traffic grooming, merge several low-speed traffic streams onto a high-speed lightpath. A fiber cut (or a link failure) in such networks can disrupt a large number of lightpaths and can cause a huge amount of data loss. Designing survivability schemes to make the network withstand a link failure is thus vital. In this paper we address the problem of survivable traffic grooming in a static scenario. In a static scenario the primary objective is to maximize throughput with the available network resources. Since the problem is NP-Complete, we propose an efficient heuristic TATG (Throughput Aware Traffic Grooming) for the problem. TATG employs an efficient approach of integrating logical topology design and survivable traffic grooming with heuristics at sub-problem level. Our approach ensures that the logical topology carrying the traffic always stay connected in the event of a link failure. Time complexity analysis shows that our heuristic runs in polynomial time. We study two separate forms of survivability in heuristics TATG-SC (TATG -Survivability at Connection) and TATG-SL (TATG-Survivability at Lightpath) with three categories of traffic demand. Performance comparison with a well known heuristic shows that the proposed approach provides much better throughput performance when resources are scarce. The average percentage decrease in request blocking over all experiments obtained using TATG-SC and TATG-SL is 54.87% and 59.57% respectively.
Multiple FSK Data and Power Transmission System using Magnetic Resonance Wireless Power Transfer

This paper presents a multiple Frequency Shift Keying (FSK) transmission system which can simultaneously transmit power and data using magnetic resonance wireless power transfer (MR-WPT). The main challenge of this paper is that the MR-WPT with the Automatic Tuning Assist Circuit (ATAC) enables a multiple FSK communication toward moving objects. The proposed system with ATAC can maintain the resonant state even though the driving frequencies of the transmitter slightly differ from the resonant frequency. Therefore, this characteristic means that it enables simultaneous transmission of power and FSK modulated data at multiple frequencies without a sharp decline in power transmission efficiency. The proposed system is implemented, and it shows double bit data transmission at the same symbol rate with multiple FSK modulation.
Validation of Spiking Neural Networks Using Resistive-Switching Synaptic Device with Spike-Rate-Dependent Plasticity

In this work, we have developed a spiking neural network (SNN) using gradual resistive-switching random-access memory (RRAM) synaptic device. The fabricated RRAM devices demonstrated the characteristics of gradually changing conductance with voltage pulses under both positive and negative polarities, which is suitable for imitating the potentiation and depression functions of a biological synapse by an electron device. Featuring the gradual switching characteristics, spike-rate-dependent plasticity (SRDP) inspired by Bienenstock, Cooper, and Munro (BCM) learning rule was confirmed and modeled for synaptic modification in the SNN. Then, the supervised learning of MNIST patterns was performed on the simulated SNNs, by which it has been validated that the proposed resistive-switching synaptic device and SRDP synaptic modification rule can adjust weights accurately in cooperation without necessitating the conventional calculation-based learning scheme in the artificial neural networks (ANNs), such as error backpropagation.
Some Results on Images of a Class of λ-Constacyclic Codes Over Finite Fields

In this paper, we show that any <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>-constacyclic code over <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}_{q^{m}}$ </tex-math></inline-formula> is a <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>-constacyclic code over <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}_{q}$ </tex-math></inline-formula> under some special maps. Moreover, we show that the images of these <inline-formula> <tex-math notation="LaTeX">$\lambda -$ </tex-math></inline-formula>constacyclic codes can be put into the concatenated form.
In-Situ Electroporation on a Micropore-Arrayed Filter for Cell Labelling

This work reported an in-situ electroporation on an ultra-thin and high-porosity micropore-arrayed filter to introduce a fluorescent dye label into targeted cells. The in-situ electroporation avoids laborious cell release and transfer, guarantees electric field uniformity and thus high efficiency. The ultra-thin and high-porosity properties are the key to achieve a high viability via decreasing forces applied on cells during filtration. The whole procedure including cell separation and electroporation can be finished in a short duration (<15 min). This system demonstrated the applicability in all-in-one separation, labelling and retransfusion of targeted cells to monitor their track for tumor metastasis study.
Dynamic Allocation of Replication and Erasure Codes for Enhancing Storage Efficiency in OpenStack Swift

The object storage system introduced data redundancy techniques such as replication and erasure codes to build a reliable system. However, replication method has storage efficiency problem with large and less frequently accessed data types, and erase coding method has performance problem with small and frequently accessed data types. In this paper, we propose a dynamic allocation of replication and erasure coding approach (DARE) to improve storage efficiency and performance using access frequency and object size factors. Experimental results show that the proposed DARE can improve storage efficiency by 21 percent compared to the traditional resilient system
Validation of Collision-Free Speed Model in Bottlenecks

The pedestrians' safety has attracted increasing attention, especially in large-scale gatherings. A large number of models have been proposed to simulate the movement characteristics of pedestrians. The collision-free speed model can qualitatively reproduce many self-organized phenomena well when there is no pushing and squeezing in the crowd. In addition, as a first-order model its computational efficiency is relatively high compared to force-based models. In this work, we validate the model quantitatively against empirical data from bottleneck experiments. The parameters controlling the desired speed and pedestrians' initial position distribution are adjusted to reproduce the empirical data. The Voronoi-method is used to calculate the density, speed and flow. It is shown that the model can reproduce the relation between the flow and the density when the initial density is less than 3.33 m−2. However, other characteristics in the simulation such as trajectories in the bottleneck and relation between flow and bottleneck width diverge to some extent from the experimental findings.
Molecular Dynamics Simulations as a Competence Developer for Materials Science

Molecular dynamics is a powerful computational tool to model material properties. The potential of the simulation tool to understand and to predict materials behaviors and properties has been widely used for research purposes. In this work, molecular dynamics as an innovative tool is investigated. The goal is to developed competences related with material science using molecular dynamics. The main conclusion is that the tool is of great use for this purpose. It has great potential as a modeling tool that accompany the process of competence development in an engineering student.
Outcome Classification in Cricket Using Deep Learning

With the growth in applications of Artificial Intelligence day by day, every domain is going automated. Machine learning has enabled systems to learn the process on its own in order to reduce the human labour. In sports like cricket, Football AI has not been used on a greater scale but there are certain areas where it can be of great help to apply AI techniques. In this paper the outcome classification task has been performed on cricket videos. The main purpose of performing such activities is to create automatic commentary generation. There are many sub-tasks needed to be considered for this task. One of those tasks is to classify the outcome of each ball for which commentary is to be generated. There has not been any standard data to perform such task, neither are any benchmark results to compare a new one. So in this paper, from data collection to performing the classification operation with results has been produced. There are four most general outcomes in the game of cricket such as Run, Dot, Boundary, Wicket. With the help of Convolutional Neural Network and Long Short-Term Memory Networks the outcome of cricket match ball by ball videos has been classified with 70% of test accuracy.
Time-Frequency Analysis (TFA) Method for Load Identification on Non-Intrusive Load Monitoring

Public awareness of energy conservation can be realized through the process of electricity monitoring so that information can be found related to electricity usage and potential savings that can be made by the community. With the information on the results of this monitoring, the community can manage electricity usage more optimally so that it will have a positive impact on reducing electricity usage costs. The diversity of both linear and non-linear electrical equipment is a challenge in this monitoring process. In this study, the monitoring process is carried out in the aggregate on several electrical equipment indirectly on the electrical panel using the Non-Intrusive Load Monitoring (NILM) approach. The NILM approach is carried out through time and frequency domain analysis (TFA) to identify electrical equipment. Current signals (I) obtained in aggregate will be identified based on the characteristics of the frequency spectrum and its harmonics. The development of the TFA method was carried out to obtain feature vectors used for the identification process. Besides that, the noise reduction method was developed using the hybrid filter method by combining Median Filter and Average FFT filter (MFAFFT). The use of hybrid filter is done to eliminate noise through the frequency domain that was previously still remaining when filtered using Median Filter in the time domain. Classification performance of the test shows better accuracy results on hybrid filtered and using time and frequency feature. In SNR scenarios >15, the accuracy results are quite good with values greater than 0.9 and relatively stable at values above 0.9 at SNR >25.
1 MHz band rectenna with several rectifier devices in nW operation

In this paper, simulational and experimental investigations on the 1 MHz band rectenna in nW operation are described for energy harvesting from AM radio waves. For the objective, a commercial based SBD, a Cross couple CMOS Pair (CCP) IC and a super-steep subthreshold slope PN-body tied SOI-MOSFET (PNBT) diode are investigated as rectifier devices in nW region. In experiments with the CCP IC, efficiency of 9.4 % at -41 dBm can be obtained. In simulation with the PNBT diode, efficiency of 30.3 % at -40 dBm can be estimated for our future step. These results clarify superior possibility for energy harvesting in wider service area with AM radio waves.
Work-in-Progress: Routing of Delivery Drones with Load-Dependent Flight Speed

Drones draws increasing attention as vehicles for home delivery services. Delivery time is one of the most critical concerns of both customers and delivery service providers. The delivery time depends not only on the flight distance but also on the flight speed, and the flight speed depends on the payload. This paper studies a routing problem for delivery drones considering load-dependent flight speed. This paper formally defines Flight Speed-aware Vehicle Routing Problem (FSVRP) and proposes a dynamic programming algorithm to efficiently solve the problem. Experiments show the effectiveness of the proposed algorithm in terms of quality of results and algorithm runtime.
A Wideband Efficient Rectifier Design for SWIPT

Simultaneous wireless information and power transfer (SWIPT) requires rectifiers that achieve a good efficiency for low input power and large signal bandwidths. This paper presents an efficient SWIPT rectifier for wideband multi-sine signals based on a conventional Class F rectifier design allowing low input power level and wide input signal bandwidth. The RF to DC efficiency is more than 35% for a wide input power range from -15 to +5 dBm and frequency from 2.4 to 2.5 GHz. For this input signal range, a DC output voltage of 3.7 V is measured. The maximal efficiency of 54.5% is measured at +3 dBm input power and peak DC output voltage of 4.1 V is measured at +10 dBm input power, respectively. The measurement are done for a signal bandwidth of 30 MHz, showing that the proposed rectifier can enable efficient SWIPT using multi-sine signals in the 2.4 GHz ISM band.
Deep Learning for Consumer Devices and Services 3—Getting More From Your Datasets With Data Augmentation

A key aspect to developing and successfully deploying neural network (NN)-based solutions is the availability of suitable datasets. In this article some of the challenges to acquire and annotate data are discussed in the context of new consumer devices. To increase the sample size of training data several approaches to augment a seed dataset are explained and discussed including a number of advanced, problem-specific techniques. A basic introduction to the concept of learned data augmentation is also provided.
Packet Processing Architecture Using Last-Level-Cache Slices and Interleaved 3D-Stacked DRAM

Packet processing performance of Network Function Virtualization (NFV)-aware environment depends on the memory access performance of commercial-off-the-shelf (COTS) hardware systems. Table lookup is a typical example of packet processing, which has a significant dependence on memory access performance. Thus, the on-chip cache memories of the CPU are becoming more and more critical for many high-performance software routers or switches. Moreover, in the carrier network, multiple applications run on top of the same hardware system in parallel, which requires the capacity of cache memories. In this paper, we propose a packet processing architecture that enhances memory access parallelism by combining on-chip last-level-cache (LLC) slices and off-chip interleaved 3 Dimensional (3D)-stacked Dynamic Random Access Memory (DRAM) devices. Table entries are stored in the off-chip 3D-stacked DRAM, so that memory requests are processed in parallel by using bank interleaving and channel parallelism. Also, cached entries are distributed to on-chip LLC slices according to a memory address-based hash function so that each CPU core can access on-chip LLC in parallel. The evaluation results show that the proposed architecture reduces the memory access latency by 62 % and 12 % and increases the throughput by 108 % and 2 % with reducing blocking probability of memory requests 96 % and 50 %, compared to the architecture with on-chip shared LLC and that without on-chip LLC, respectively.
Work in Progress: Investigating the Effects of High Priority Traffic on the Best Effort Traffic in TSN Networks

This paper investigates the effects of various parameters of high priority traffic classes on the Best Effort (BE) traffic in the networks based on the IEEE Time Sensitive Networking (TSN) standards. In this regard, the paper discusses ongoing work and presents preliminary results using a TSN simulator. The results indicate that several parameters of the high priority traffic such as periods, offsets and preemption modes can have a significant impact on the quality of service (e.g., guaranteed message delivery and message delays) of the BE traffic.
ARTOUR: Augmented Reality for Tourism - A Case Study in Riobamba, Ecuador

Augmented reality (AR) is a state-of-the-art technology that integrates computer-generated virtual information into the real world and changes the way people interact and experience their surrounding environment. AR technology brings the digital world, whether it is an object in two-dimensions (2D) or threedimensions (3D), seamlessly into the physical world. It is establishing itself evermore as a fundamental tool in the modern world, not only as a recreational tool but also in the educational, medical and tourism sectors.AR in tourism can help visitors/tourists to explore places and tourist attractions in real terms, in order to make the most of their experience. In this investigation, we propose an interesting way to guide tourists in the city of Riobamba in a modern way, through an application called AR-TOUR, based on the Augmented Reality technology. AR-TOUR is a mobile service platform that will show the main tourist attractions in the city of Riobamba such as churches and parks in 3D, which will increase the interest of tourists in visiting places and the ease of navigating through the city. The ARTOUR application additionally offers options for the selection menu, multilingual functionality, ease of use and the ability to customize the application, which are among the main requirements that are taken into account to attract tourists. The limitations and recommendations of the study are mentioned that will pave the way for future research. The ARTOUR application was developed in Unity 3D using the Vuforia and Flutter augmented reality software for the menu option.
3D Silk-Based Bioelectronic Scaffolds for Osteochondral Regeneration

This paper describes a silk-based multi-layer cartilage scaffold with an embedded coil to achieve local heating for the promotion of bone tissue regeneration. The multi-layer structure of the silk-based bioelectronic scaffold was designed with a gradient of porosity and bioactive agents to vastly mimic the bone extracellular matrix (ECM) complexities. Multiple silk foams with tailorable porosity, tunable degradation and controllable mechanical properties were integrated with the degradable microcoil. In addition, as-reported silk foams by mimicking the silk fiber spinning process can be facilely fabricated in a bio-friendly and non-toxic manner, which will be benefit to supply smart medical devices in biomedical applications.
Sub-ns Access Sub-mW/GHz 32 Kb SRAM with 0.45 V Cross-Point-5T Cell and Built-in Y_ Line

A 0.45 V 28-nm 32-Kb SRAM with multi-power-supply low-power circuits, such as a cross-point 5T with built-in Y_line, gate-boosted drivers and adaptive tracking circuits, demonstrates a sub-ns access time and sub mW/GHz power dissipation. The 5T circuits are feasible to reduce the power of a 6T 32-Kb core to about 30% with quite the same sub-ns access time. The performance evaluation also indicates the new bit cell and array architecture open the door to the sub-ns access time and sub mW/GHz in sub-0.5 V multi-Mb era.
Monitoring and Research on the Displacement and Deformation of Transmission Line Towers Based on Beidou Monitoring Data

The Beidou is a satellite-based radio satellite navigation and positioning system, which has the functions of intelligence, global, all-weather, continuous and real-time precision three-dimensional navigation and positioning, and has good anti-interference and security. The application of engineering survey, aerial photogrammetry, ocean measurement, city survey and so on has been applied in the fields of military, traffic, communication, resources, management and so on and has been widely used. The basic structure, measurement principle and Beidou satellite positioning error of global positioning system (Beidou) are described and analyzed in this paper. Measures to be taken against Beidou errors.
Framework for Analyzing the Security of Robot Control Systems

The purpose of this work is to analyze the security model of a robotized system, to analyze the approaches to assessing the security of this system, and to develop our own framework. The solution to this problem involves the use of developed frameworks. The analysis will be conducted on a robotic system of robots. The prefix structures assume that the robotic system is divided into levels, and after that it is necessary to directly protect each level. Each level has its own characteristics and drawbacks that must be considered when developing a security system for a robotic system.