Miracle-dz/UniFAR-FTUs huggingface dataset:
An Abdominal Imaging Method Combined Electrical with Ultrasound Tomography

Cancer is an important cause of morbidity and mortality worldwide, and liver cancer accounts for a large proportion. It is very significant to detect and track the development of liver lesion. Electrical impedance tomography is a potential biological imaging technology, which is promising in the field of soft tissue detection. However, it is difficult for electrical tomography to obtain the interface information of different biological tissues. To improve the accuracy of interfaces imaging, a dual-mode fusion imaging method combined electrical with ultrasound tomography is proposed. Tikhonov regularization algorithm is used for electrical imaging of the lesion. Ellipse positioning method is applied to get interface information from the analysis of ultrasonic test information. The adaptive weighted image reconstruction algorithm is used for pixel-level fusion of two modes. Based on the test of simulation model, preliminary studies demonstrate the improvement of the interface detection definition and imaging accuracy compared to single mode tomography.
Simulation of the Proactive Transmission of Replicated Frames Mechanism over TSN

The Time-Sensitive Networking (TSN) Task Group (TG) is providing Ethernet with timing guarantees, reconfiguration services and fault tolerance mechanisms. Some of TSN’s targeted applications are real-time critical applications, which must provide a correct service continuously. To support these applications the TSN TG standardised a spatial redundancy mechanism. Even though spatial redundancy can tolerate permanent and temporary faults, it is not cost-effective. Instead, temporary faults can be tolerated using time redundancy. We proposed the Proactive Transmission of Replicated Frames (PTRF) mechanism to tolerate temporary faults in the links. In this work we present a new PTRF approach, a PTRF simulation model and a comparison of the approaches using exhaustive fault injection.
Improving BER of WiMAX using Interference Mitigation Techniques

New Generation Wireless Networks is still confront the disputes such as resource sharing, channel or bandwidth allocation, synchronization, spectrum efficiency, and interference a major concern among all. Orthogonal Frequency Division Multiplexing (OFDM) is a prevailing technology that is widely adopted by current 4G and 5G wireless communication as it can certainly resolves many issues of wireless networks such as data rates and interferences. The paper introduces three types of interferences – Inter Symbol Interference (ISI), Inter Carrier Interference (ICI), and Co- Channel Interference (CCI) that greatly clog our Bit Error Rate (BER). This paper had taken World Wide Interoperability for Microwave Access (WiMAX) as our 4G wireless application that works with OFDM and try to reduce its BER by using interference mitigation techniques such as Wavelet and Space Time Block Code (STBC). Furthermore, WiMAX physical layer is described with its interferences and relevant solution, also the advantage of Wavelet transform in contrast to Fourier transform and its comparison is shown in terms of BER.
Interactive DEMOnstration of Medical Simulations using a Virtual Reality approach: Application to the Male Urinary System

The objective of this demonstration (DEMO) is to create an interactive environment where any user - irrespective of his/her scientific and cultural background - will be able to interact with scientific simulations (3D Finite Element Simulations) of the Male Urinary System. The user is immersed into a Virtual Reality experience (using Oculus Rift), where all navigation and interaction will be carried out using his bare hands (using a Leap Motion sensor). The experience mixes medical science and engineering, thus allowing a multi-level experience, ranging from the non-specialized user to the medical or engineering professional.The interactive environment has a library of simulations organized hierarchically. The approach can be extended to any scientific simulation(s) that can be discretized into a set of sequential frames. It can display codified simulation data in terms of shape (geometry) and/or color (intensity).
Contention-Based Opportunistic Spectrum Access in One-Way Highway Vehicular Networks

The spectrum sharing problem is considered under the scenario of a one-way highway vehicular network. We model the locations of the vehicle-to-vehicle (V2V) nodes, the vehicle-to-infrastructure (V2I) nodes, and the road side units (RSUs) as 1D Poisson point processes (PPPs) on a straight line of infinite length. To efficiently reuse the spectrum preoccupied by the V2I nodes, a contention based opportunistic spectrum access (OSA) strategy is proposed for V2V nodes. Particularly, a V2V node is designed to first detect the spatial spectrum holes of the V2I links and then if succeeds, compete with other eligible V2V nodes (in the spatial spectrum holes of the V2I links) for the access permission. Under this setup, the transmission probability of V2V nodes is derived. Further, the coverage performances of the V2V and V2I links are analyzed. It is worth noting that one of the key challenges in the computations of the transmission probability and coverage probabilities stem from the non-homogeneity of the eligible/active V2V nodes. Then, for tractability of the analytical results, we propose a HPPP approximation for the spatial model of the eligible/active V2V nodes and validates the respective effectiveness by means of extensive simulations. We also discuss the key design insights by analyzing the impact of system parameters on the network performance. It is shown through both numerical and simulation results that the proposed contention based OSA strategy can enhance the spectrum efficiency of the one-way highway vehicular network.
Deep Learning and Audio Based Emotion Recognition

While tightening and expansion of our facial muscles cause some changes called facial expressions as a reaction to the different kinds of emotional situations of our brain, similarly there are some physiological changes like tone, loudness, rhythm and intonation in our voice, too. These visual and auditory changes have a great importance for human-human interaction human-machine interaction and human-computer interaction as they include critical information about humans' emotional situations. Automatic emotion recognition systems are defined as systems that can analyze individual's emotional situation by using this distinctive information. In this study, an automatic emotion recognition system in which auditory information is analyzed and classified in order to recognize human emotions is proposed. In the study spectral features and MFCC coefficients which are commonly used for feature extraction from voice signals are firstly used, and then deep learning-based LSTM algorithm is used for classification. Suggested algorithm is evaluated by using three different audio data sets (SAVEE, RAVADES and RML).
Development of a Highly Stretchable Strain Sensor Based on Patterned and Rolled Carbon Nanotubes

This paper reports a highly stretchable strain sensor consisting of patterned and rolled carbon nanotubes (CNTs) embedded in an elastomer. To form overlapped lines of CNTs on the elastomer, vertically aligned CNTs (VACNTs) are grown on the patterned catalytic sites and rolled out by a roller. In the initial unloaded state, these lines of CNTs are overlapped with each other. Under loading, the flexible substrate is extended, and the overlapped CNT lines are slid and separated, increasing the electrical resistance. The fabricated sensor showed excellent sensing performances including broad sensing range (>500% strain), high sensitivity (gauge factor >28), high repeatability, and durability. In addition, since the shape of the CNT lines determines the resistance through the deformed lines of CNTs under applied strain, the performance of the sensor can be further improved by optimizing the pattern design. Therefore, the sensor would be an attractive candidate for diverse applications of strain sensors.
Atividade cicatrizante e estudo toxicológico pré-clínico do fitoterápico sanativo®

SUMMARY. “Healing Activity and Pre-Clinical Toxicological Study of Phytotherapic Sanativo®”. The wound healing activity of phytotherapic Sanativo®(SAN) and the possible hazard effects of the subchronic administration of SAN were evaluated in rats. SAN induced significant decrease in the area of the open wound in the rat dorsum. In the sub-chronic toxicity studies, SAN in doses of 1,675 g/kg, decreased the gain in body mass, but this was significant only in the first week of administration. SAN produced only a few significant alterations in the hematological and biochemical parameters, although without dose-response correlation and were within the parameters of this species. The histological analysis of the tissues did not show changes. In conclusion, Sanativo® possesses significant healing property in the open wound model and low toxicity in Wistar rats.
Resilient H∞ State Estimation for State-Saturated Systems: A Dynamic Event-Triggered Approach

This paper is concerned with the dynamic event-triggered H∞ state estimation problem for a class of discrete time-delay systems subject to state saturations and gain perturbations. In order to reduce energy consumption, a dynamic event-triggered mechanism is employed to decide whether the received measurement output should be transmitted to the corresponding state estimator or not. The aim of this paper is to design a dynamic event-triggered resilient H∞ state estimator such that the error dynamics of state estimation is asymptotically stable with a prescribed H∞ performance index. By using the Lyapunov method, a sufficient condition is derived to guarantee the existence of the desired state estimator whose gain matrix is obtained by solving a set of matrix inequalities. An illustrate example is provided to demonstrate the effectiveness of the proposed state estimation scheme.
Online Testing of Clock Delay Faults in a Clock Network

Traditionally, it has been a difficult task to characterize the quality of a Clock Delay Fault (CDF). Here, a CDF is referred to a delay fault occurring in the clock network that causes an abnormal delay when a clock signal travels through it and thereby causing large-than-expected clock skews at the clock ports of some flip-flops. In a recent work [12], a modified flush test procedure taking short pulses as the test stimuli at selected clock cycles has been proven effective in characterizing a CDF. In this work, we extend this technique to support online Built-In Self-Test (BIST). We investigate two fault detection strategies, namely, valid-range criterion, and valid-span criterion, and we compare their fault detection abilities in terms of the minimum detectable CDF. With the proposed BIST scheme, the health condition of the clock network in a device operating in the field can be inspected on a regular basis so as to take precautions before the clock network breaks down due to deteriorating fault effects.
Latency Performance of 5G New Radio for Critical Industrial Control Systems

An innovative feature of the 5th Generation mobile network (5G) is to consider industrial applications as use cases for which its new radio access, 5G New Radio, aims to provide ultra low latency and ultra high reliability performance. These requirements are fulfilled by minimizing standard performance indicators such as end-to-end latency and packet error rate. However, industrial control applications typically require periodic exchange of small data, where the ability of networks to support short and deterministic cycle times is the main key performance indicator. This paper proposes a methodology to evaluate the achievable cycle time of an industrial network deployed over the 5G New Radio specifications. Numerical results shows that 5G can achieve millisecond level cycle time with network size of several hundred, which is promising for many factory automation applications.
An Integrated Visual Signalling, Localisation & Health Monitoring System for Soldier Assistance

To strengthen the security system of a nation, ensuring the safety, whereabouts and healthy body condition of the soldiers is very important. An indoor/outdoor network between the soldiers is effective in terms of informing everyone in the network if anyone is missing or suffering from bad health conditions or if someone wants to communicate with others beyond eyesight. This paper describes the design and implementation of a low-cost embedded system developed for smart soldier assistance, the systems incorporate a gesture recognition based visual signaling, an Ultra Wide Band (UWB) based indoor and short-range outdoor localization and physiological parameter monitoring modules. The modules combined together help in creating a network which is used to track fellow soldiers location and alert messages based on the gesture and health parameters. The gesture recognition module consists of a glove built of flex and IMU sensors; the health monitoring devices comprise of ECG, Temperature and PPG; and the UWB based communication is responsible for alert messaging and indoor localization.
Graphene Field-Effect Transistors for Millimeter Wave Amplifiers

In this work, we analyze high frequency performance of graphene field-effect transistors (GFETs), applying models of drain resistance, carrier velocity and saturation velocity. This allows us to identify main limitations and propose an approach most promising for further development of the GFETs suitable for advanced mm-wave amplifiers. Analysis indicates, that the saturation velocity of charge carriers in the GFETs can be increased up to 5.107 cm/s via encapsulating graphene by hexagonal boron nitride layers, with corresponding increase of extrinsic maximum frequency of oscillation up to 180 GHz at 200 nm gate length.
Spatial Mismatch Correction Based on 3D Electromagnetic Scattering Model

3D electromagnetic scattering models(EM-model) can predict features at different angles for matching, which plays an important role in the automation target recognition for synthetic aperture radar imagery(SAR-ATR) system. However, there is a space mismatch between the model and the measured image. Therefore, the EM-model and the measured image are in different coordinate systems. To solve this problem, this paper proposes a new spatial mismatch correction algorithm based on EM-model. Considering that the model can be characterized by the position and amplitude of the scattering center(SC), we take the scattering center as the main feature. The scattering centers of the model and the measured data are extracted separately, and the Hausdorff distance(HD) is utilized to measure the distance between EM-model and the measured image. According to the rigid transformation relationship between the EM-model and the measured image, the corresponding rigid transformation model is established. Experimental results based on the moving and stationary target acquisition and recognition (MSTAR) dataset demonstrate the validity of the proposed algorithm.
A Hybrid Approach to Increase Network Lifetime in WSN Using PSO and Firefly Optimization

In WSN the major problem is energy and lifetime of the network. This problem can be solved by appropriate selection of the cluster head (CH) in each cluster. This is an important process in the cluster based network to select the CH and its member which affects the energy of the network. The link stability is also the main factor in the network. The route or link that consumes less energy or load will be chosen for data transmission between the nodes and for this purpose open shortest path routing protocol is used. A hybrid optimization method is considered to decrease the network energy. In this paper, a hybrid approach is proposed where the PSO and firefly algorithm are applied for energy optimization. Using this hybrid approach the network power can be saved and hence the network life increases.
A Nichesourcing Framework applied to Software Sustainability Requirements

Background] A software sustainability model is commonly defined in terms of social, economic, technical and environmental dimensions. A key challenge is its characterization regarding sustainability requirements and their dependencies since it depends on, and varies with, the type of software system, and changes in operational contexts. [Aims] With the purpose of facilitating the definition of a context-dependent software sustainability model, we introduce nichesourcing as a type of distributed problem-solving paradigm, named crowdsourcing. [Method] First a set of nichesourcing requirements were identified, and an existing nichesourcing methodology, originally used in the cultural heritage domain was analyzed with respect to its applicability in Software Engineering. [Results] As a result, we propose an adapted methodology for nichesourcing the knowledge on sustainability requirements and their dependencies. Strengths and challenges for crowdsourced software engineering are also identified.
Online Control of Islands Microgrids Connected by Electrical Submarine Cable

The present paper introduces a description of the use of online systems for real-time monitoring, control and management of power grids. Following the Smart Fossil Free Island project, which aims to make Porto Santo Island an intelligent, self-sustaining, and free of harmful gases emissions Island, or, in other words, to produce energy without using fossil fuels, arises the possibility to interconnect the electricity grids of Madeira and Porto Santo Islands through a submarine high voltage cable. This is an innovative project, since it intends to interconnect two isolated microgrids from two Islands with small dimensions, through a submarine electric cable installed at about 2300 m depth. This allows to partially or totally power Porto Santo Island electrical grid from the electro producing system of Madeira Island. In order to analyze the viability of this connection, a comparative study between a High Voltage Alternating Current (HVAC) system and a High Voltage Direct Current (HVDC) system has been carried out. The client impositions require a bidirectional system, given the possibility of installing, on Porto Santo Island, a wind farm able to power this Island and transfer a considerable percentage of the electric energy needed to power Madeira Island. This project uses online systems to monitor, manage and control the frequency, voltage, active and reactive power of the two Islands from Madeira, regulating the transfer of power between them, in order to ensure the continuity of service and all parameters of electrical quality.
Towards Building a Better Biometric System Based on Vein Patterns in Human Beings

Until a couple of years ago, lifting fingerprints from photos was considered to be an impossible task. But with all the technological advancements coupled with the ingenuity of hackers, spoofing fingerprint information is not so difficult now. Add to this, the fact that human fingerprints are not always unique, and we see that we need to stop relying heavily on fingerprint-based security systems. So a project that extracts the vein distribution patterns in human palms was devised as a solution to this problem. Biometric identification using IR images of palm vein patterns offers more distinctiveness, robustness and difficulty to plagiarize when compared to similar mechanisms. De-oxidized blood in human veins has a property of absorbing the light rays emitted by an infrared source. This property of IR absorption makes the veins distinctively visible when exposed to IR rays. An image of a human palm is prone to noise when captured under infrared light. Canny’s edge detection algorithm was employed on an image dataset where all the images are preprocessed using several steps which will be discussed in detail in the following sections. The detected edges act as authentication information for security systems. A feature extraction algorithm is implemented on these edge-detected images and the result is used to classify the subjects.
Survey on multi-robot manipulation of deformable objects

Autonomous manipulation of deformable objects is a research topic of increasing interest due to the variety of current processes and applications that include this type of tasks. It is a complex problem that involves aspects such as modeling, control, perception, planning, grasping, estimation, etc. A single robot may be unable to perform the manipulation when the deformable object is too big, too heavy or difficult to grasp. Then, using multiple robots working together naturally arises as a solution to perform coordinately the manipulation task. In this paper, we contribute a survey of relevant state-of-the-art approaches concerning manipulation of deformable objects by multiple robots, which includes a specific classification with different criteria and a subsequent analysis of the leading methods, the main challenges and the future research directions.
LoRa Performance Assessment in Dense Urban and Forest Areas for Environmental Monitoring

In this work, some experimental results aiming to assess the performance of LoRa modulation are presented taking in consideration two specific scenarios (namely, a dense urban area and a forest environment). These scenarios have been chosen since they are very prone for environment monitoring and protection. The considered LoRa performance criteria are Range, Packet Reception Rate (PR) and Received Signal Strength Indicator (RSSI). The obtained experimental results have provided valuable information on how LoRa modulation can be influenced according to specific environment characteristics as well as combination of them. In addition, experimental results shows that, using a particular LoRA setup, packet loss may be near zero even with a high signal attenuation demonstrating the LoRA robustness feature.
A Block-sparse Set-Membership PNLMS Algorithm Based on Hybrid Zero-Attraction Penalty

In some practical communication systems, the channel impulse responses whose values are large but just account for a small fraction distributed in clusters. Hybrid norm l2, 0 is employed as a zero-attraction penalty to build the cost function (CF) of the proportional normalized least mean square (PNLMS) algorithm. In addition, the set-membership (SM) criterion is also used to reduce the computing complexity and to get good tracking performance by presetting a thresh-old of error. The novel method named l2, 0-set-membership PNLMS (l2, 0-SMPNLMS) algorithm not only has fast initial convergence speed inheriting from the PNLMS algorithm, but also has good performance to deal with block-sparse signals. Numerical simulations have been conducted and the result shows the superiority of the proposed algorithm compared with the related algorithms.