Miracle-dz/UniFAR-FTUs huggingface dataset:
Incentive Stochastic Stackelberg Games With Measurement Feedback Control

In this paper, incentive Stackelberg games are investigated for a class of stochastic linear systems. Unlike the existing ordinary Stackelberg games, output feedback control is developed in such a way that state variables cannot be measured directly, especially for networked control systems. First, the incentive Stackelberg strategy is designed by the leader to achieve team-optimal solution. Second, the follower achieves its equilibrium ensuring the incentive Stackelberg strategy by solving some cross-coupled stochastic Riccati differential equations. Finally, the optimal estimator (conditional expectation) for the leader and follower is derived.
Sine Wave Current Tracking of Grid-tied Two-stage Single-phase Inverter via Adaptive Model Predictive Control with Voltage Regulation

Two-stage inverters have been commonly applied in the distribution systems, where Total Harmonic Distortion (THD) is important for the judgement of the tacking effects. This paper focuses on the current tracking of the grid-tied two-stage inverter composed by the front buck-boost converter and the rear single-phase inverter. A cascaded Proportional-Integral (PI) Model Predictive Control (MPC) is applied for the intermediate voltage tracking of the front stage. Meanwhile, an adaptive MPC scheme is adopted for the output current tracking of the single-phase inverter stage by introducing an time-varying observer for the filter inductance and load resistance identification. By regulating the intermediate voltage, there will be a corresponding voltage which minimizes THD under the same other parameters. Hence, a reference voltage generator based on the circuit parameters, the input voltage, the reference current and grid voltage is employed for the voltage regulation to obtain lower THD. The simulation results show the effectiveness of the control scheme for the two-stage inverters applied in this paper.
On-line Monitoring of Batch Process Using Multi-phase Based Dynamic Model

Multiphase characteristics and auto-and-cross correlation between process variables are two critical issues to be addressed for fermentation process monitoring. A method namely multi-phases dynamic PCA is proposed to investigate these two non-negligible issues. We introduced Affinity Propagation (AP) clustering to solve the problem of unequal length in batch process, and to optimize the clustering number of AP method, Silhouette index is applied. After phase division, autoregressive-PCA (AR-PCA) model is structured to remove auto and cross correlation in each phase. Model order is determined using Akanke information criterion (AIC) and the model parameters are estimated by PLS method. Additionally, to improve the fault detection effectiveness, normal historical data is introduced to structure AR-PCA model when monitoring the new batch. The experiment result of penicillin cultivation process indicates the feasibility and effectiveness of the proposed method.
An All-Digital, $V$ MAX-Compliant, and Stable Distributed Charge Injection Scheme for Fast Mitigation of Voltage Droop

Distributed charge injection (CI) scheme featuring distributed <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ MAX}}$ </tex-math></inline-formula>-complaint CI clamps, distributed digital droop detectors (DDDs), and distributed droop controllers for fast mitigation of voltage droop is fabricated in 10-nm FinFET CMOS test-chip. A local DDD detects nearby voltage droop in two clock cycles of IP block, and quickly triggers associated CI clamps to inject charge from a high voltage rail (e.g., 1.8 V) to <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm{ CC}}$ </tex-math></inline-formula> for immediate voltage droop mitigation. Local droop controller collectively guarantees stable operation after CI is triggered, by gradually allowing the voltage regulator to take over after the droop subsides. Measured data shows droop reduction by up to 45% for a uniform transient load current transition, and by 38% in a hot-spot load current transition at 1.0 V and 2.0 GHz. The droop reduction is translated to power savings of ~11% over a guard-banded baseline.
Personalized POI Travel Recommendation With Multiple Tourist Information

A proposal of POI based location recommendation system by using multidimensional preference collection system is put forth. This paper compare the layers given in some paper to find out POIs of the user. Along with that we focuses on image based POIs extraction by using emotion extraction algorithm. And compare the POIs based location recommendation with automatic trip planning.When user visited popular or unpopular place at that time the POI popularity prediction with user’s visited places. When this paper compare the planning about trip, according to user’s POI. Their are various travel routes, get the assertion that many property of POIs(Point of Interest) for POI popularity prediction. In multi preference collection system, this paper focus on image features, comments analysis and click through data to detect user’s preferences according to user’s interest. With respective POI data this paper proposed a classification technique for location POI popularity prediction.
Formation Deployment of Hybrid Control Search Algorithm for Multi-robot in Two-Dimensional Space

In order to deploy multi-robot into a 2-D desired formation during the seeking process, this paper proposes a hybrid seeking algorithm with the formation deployment. Firstly, this paper expands the 1-D deployment algorithm to 2-D, and then combines with the extreme seeking algorithm to obtain the hybrid seeking algorithm. With the algorithm, multi-robot can deploy into a desired 2-D formation during seeking process. Simulation results are provided to illustrate the effectiveness of the algorithm.
Automating E-Government Services With Artificial Intelligence

Artificial Intelligence (AI) has recently advanced the state-of-art results in an ever-growing number of domains. However, it still faces several challenges that hinder its deployment in the e-government applications–both for improving the e-government systems and the e-government-citizens interactions. In this paper, we address the challenges of e-government systems and propose a framework that utilizes AI technologies to automate and facilitate e-government services. Specifically, we first outline a framework for the management of e-government information resources. Second, we develop a set of deep learning models that aim to automate several e-government services. Third, we propose a smart e-government platform architecture that supports the development and implementation of AI applications of e-government. Our overarching goal is to utilize trustworthy AI techniques in advancing the current state of e-government services in order to minimize processing times, reduce costs, and improve citizens’ satisfaction.
An Angularly Stable Frequency Selective Surface with Vent Holes for 5G Electromagnetic Shielding

A frequency selective surface (FSS) based electromagnetic shielding structure with vent holes is proposed for 5G electromagnetic (EM) shielding. The proposed FSS structure is developed for the demanding requirements of EM shielding at 28 GHz without worsening the ventilation. Through a number of simulations using full-wave analysis, the optimized FSS achieves a bandwidth of more than 2 GHz with 30 dB shielding effectiveness. Moreover, the proposed FSS-based shielding structure has the advantage of response stability to the incident angle from 0° up to 60° for both TE and TM polarization. Results show that there is a good agreement between the measurement and the simulation.
Event-Triggered and Self-Triggered Control for Linear System Based on New Event Condition

Event-triggered control and self-triggered control have recently been proposed as an alternative to more traditional periodic execution control tasks. The possibility of reducing the number of executions while guaranteeing the desired level of performance makes event triggering and self-triggering control very attractive in sensor/actuator network environments. In this case, reducing the number of feedback control executions means reducing the amount of transmission, thus reducing energy expenditures. This paper describes two new distributed implementations of event triggering and self-triggering strategies on sensor/actuator networks. The usefulness of the results is illustrated through a numerical example.
Adaptive Hypersonic Flight Control under Asymmetric AOA Constraint

This paper investigates an asymmetric barrier Lyapunov function (ABLF) based adaptive learning controller for hypersonic flight vehicle (HFV). With consideration of the asymmetric constraint on angle of attack (AOA), by analysing the ABLF, the controller is designed based on back-stepping technique with AOA constraint being applied. Moreover, the composite learning method is utilized to estimate unknown nonlinear functions. Simulation results verify that the designed controller can guarantee good tracking performance, and the AOA tracking error is well restricted.
The Road to the Internet of Things: a Survey

The Internet of Things (IoT) concept has recently been presented as the next revolution and a part of the internet of the future. IoT consists of billions of uniquely identified smart objects ‘things’ with communication ability over the internet. These smart objects generate useful information for the provision of better services and improve the quality of life in different domains. However, there is a general lack of an integrated vision or a plan for selection and implementation of these smart objects. This paper presents the required tools and technologies (such as sensors, RFID, processors, actuators and communication models) that are essential in the IoT paradigm. The major objective of this review is to provide more detailed information about IoT smart objects, the building block of IoT, and conduct a comprehensive overview of IoT architecture with different scenarios. Moreover, this paper gives insight into IoT networking and the new type of low power wide area network (LPWAN) leading technologies in the licensed and unlicensed spectrum. Finally, this paper provides perspectives for future research and developments.
Educação para a Saúde na Terceira Idade: relato de experiência

Resumo: Este trabalho descreve as atividades desenvolvidas durante o estagio supervisionado da disciplina Pratica de Ensino do Curso Licenciatura em Enfermagem da Ufrgs, o qual objetivou discutir questoes relativas a saude na terceira idade, visando a promocao de uma melhor qualidade de vida. Durante os encontros foram discutidos diferentes temas, definidos previamente em conjunto com os participantes, que fazem parte do Programa do Idoso implementado pela Secretaria Municipal de Saude de Viamao, o qual beneficia pessoas com mais de 60 anos e renda mensal de ate um salario minimo. A metodologia utilizada foi diversificada, em funcao da escolaridade e interesses dessas pessoas. Destaca-se alguns aspectos considerados relevantes: convivio grupal e auto-estima, momentos de aprendizagem, entendimento sobre as modificacoes naturais do processo de envelhecimento e a integracao profissional-comunidade. Palavras-chave: Saude. Educacao. Qualidade de Vida. Idosos. Enfermagem. Abstract: This paper describes the activities developed during the supervised training course of the Teaching Practice (Practicum), which is part of the Nursing College program in the Universidade Federal do Rio Grande do Sul (Ufrgs). Such training course was meant to discuss issues related to health in old age aiming at promoting better quality of life. Different topics, previously defined along with the participants were discussed during the meetings. The participants belong to the "Programa do Idoso"(ederly program), implemented by the Health Care Department of Viamao (RS – Brazil) which serves people who are over 60 years old and who earn minimum wage. Diverse methodology was used and depended on people’s interests and level of education. Relevant aspects are: group association and self-esteem; learning moments; understanding the natural modifications during the aging process; professional-community integration. Keywords: Health. Education. Life Quality. Senior Citizens. Nursing.
Multi-Objective optimization for Microgrid Considering Demand Side Management

Energy management is one of the main strategies that have been widely applied in the microgrid field. Management can be done from many sides, such as the generation side and demand side. In this paper, a multi-objective strategy was formulated including an effective optimal load scheduling which aims to minimize the cost of demand and the emission in a grid-connected microgrid including different distributed resources such as renewable energy (PV, wind turbine), diesel engine, and batteries. For this purpose NSGAII was used to simulate and validate the results of the multi-objective optimization problem. Key Words: microgrid, multi-objective optimization, demand response, NSGA-II.
Controlled Hydration in Epidermal Ridges Probed by THz Time-Domain Spectroscopy

Fingerprints are common to humans, primates, and koalas but how their role in grip activities is poorly understood. Here, we reveal that the fingerprints control the hydration level of the fingertip, as required for precision gripping, by ultimately maximizing the friction. Electromagnetic waves with frequencies in the megahertz, terahertz, infrared, and visible ranges were used to identify the hydrodynamics in fingerprints, which lead to the steady-state hydration condition in ‘dry’ and ‘wet’ conditions. The results suggest that the fingerprint structure functions as a moisture channel for facilitating precision grip.
Analyzing Regional Food Trends with Geo-tagged Twitter Food Photos

Twitter is a world-wide popular SNS where many images are being posted along with tweet messages and location information. It is known that large regional differences exist regarding posted images. The differences are expected to be prominent especially for food images, since there are many kinds of regional foods over the world. However, the regional difference on food images over Twitter has not been explored so far. Therefore, in this paper, to make the difference clear, we analyzed geo-tagged food image gathered from the Twitter stream on the basis of the six regions and 17 kinds of rough food categories. For image analysis, we used only image features without any textual analysis, since Twitter messages are not always directly related to image contents. In addition, we visualized discriminative parts of local food images by applying the visualization method of CNNs.
Real-time Detection of Travelable Path Based on Image Point Cloud

In the process of moving, the robot first needs to perform ground detection, and the currently feasible area is analyzed to achieve the purpose of safe driving. Using image information and point cloud data, a system for detecting feasible regions by processing three-dimensional information is proposed. The system can quickly identify the approximate travelable area by detecting the edge of the image, and then pass the recognized image information to the corresponding depth image (point cloud date). By performing local normal vector calculation, clustering and segmentation on the depth image, a safe area that the mobile robot can travel is obtained.
Fusion Evaluation of X-Ray Backscatter Image and Holographic Subsurface Radar Image

X-ray backscatter imaging technology and Holographic Subsurface Radar can detect surface invisible targets nondestructively. These two techniques differ in the imaging mechanisms and the target characteristics they reflect, therefore, the existence of target and its electromagnetic characteristics can be known by merging these two images. In this vein, a number of fusion methods based on Weighted Fusion algorithm, Wavelet transform (WT), Non-Subsampled Contourlet transform (NSCT), Guided Filtering Fusion (GFF) and Shearlet transform are evaluated in this paper. Non-local mean filter and principal component analysis (PCA) are applied to X-ray backscattered images, and the classical Otsu method is used to extract target automatically. Experiment results from image quality metric clearly demonstrate the better performance of Shearlet transform fusion in terms of less false information, better color fidelity and better image readability.
Defect Recognition of Insulators on Catenary via Multi-Oriented Detection and Deep Metric Learning

Nowadays in electrified railway industry, 4C running vehicle is widely used to record images of catenary for defect recognition of insulators. This paper proposes a vision-based solution that applies deep convolutional neural network to recognize defect of insulators. Two main stages are included in the proposed method. First, a framework called Angle-enhanced Faster RCNN is proposed as a multi-oriented detector to localize insulators on catenary. Then, a discriminator is proposed to decide whether an insulator is defective using deep metric learning. Compared to conventional form of detection, the detector precisely takes out insulators into horizontal position so that defect discrimination with similarity measurement can be applied. For the discriminator, a novel feature extractor based on convolutional neural network is designed and triplet loss is applied as the loss function, which is more robust than classification method when facing a lack of defective samples. Experiments indicate that this solution achieves a good performance of accuracy.
Intentional Occlusion of the Left Subclavian Artery in Diseases of the Thoracic Aorta

Bertoni and et al. (1) present an interesting experience in occlusion of the left subclavian artery (LSA) in order to improve the proximal fixation of tubular aortic endovascular devices to treat acute type B dissections (n = 4; 13.8%) or chronic (n = 14, 48.3%), intramural hematoma (n = 1; 3.4%), true aneurysm (n = 7; 24.1%), aortic ulcer (n = 1; 3.4% ) and traumatic pseudoaneurysm (n = 2; 6.8%). The percentage of occlusion of the subclavian artery in this series is similar to that observed in our series of patients. The work has a good statistical analysis and is supported by an extensive and important bibliography. It has been recently suggested that the use of selfexpanding devices with proximal end point with free flow stent in the treatment of aortic dissections carries some risk of complications, such as retrograde dissection to the ascending aorta. This complication is the result of trauma which can lead that bare stent. (2, 3) The incidence of stroke may reach 7% (4, 5) according to what was observed in the EUROSTAR registry. Referring to the topic of “overstretch” of the device, we consider that there should not be similar if the pathology to be treated were an atherosclerotic fusiform aneurysm or type B dissection. The objectives of treatment in these pathologies differ, since the aneurysm should be approximately oversized 15-20% in relation with the diameter of the healthy proximal aorta, while for the dissection, in our consideration, this oversize should not exceed 3mm that diameter (about 10% if it is considered a standard diameter of 30-36mm in the transverse aorta). This is because in the second mentioned pathology, the end point of treatment is the closure of the proximal tear (which, as it is known, in more than 80% it is within the first 2 left postsubclavian centimeters) and “restoration” of the true lumen, compressed, sometimes measuring no more than 10mm in diameter and sometimes virtually has collapsed under the pressure of the false lumen, thus higher the prosthetic diameter is , greater the risk of rupture of the flap, especially in acute or subacute. For the same reasons, the required length of the seating proximal and distal areas of the endoprotheses differ in both cases and it requires a greater length in the case of aneurysms (1.5 to 2cm), since a large part of the device will be literally “loose” in the aneurysm sac. MARCELO H. CEREZO1
Semen characteristics of male infertile couples in the Kumasi metropolis: a study of primary and secondary infertile couples.

Aims: To assess the semen characteristics of primary and secondary male infertile couples in the Kumasi metropolis. Study Design: A cross-sectional study. Place and Duration of Study: Department of Obstetrics and Gynaecology, Komfo Anokye Teaching Hospital, Kumasi; between February 2012 and May 2013. Methodology: The study involved 150 men whose female partners reported to the Obstetrics and Gynaecology Department of Komfo Teaching Hospital (KATH) in Ashanti Region of Ghana for infertility treatment. Semen of the respondents were examined for various characteristics (viscosity, pH, volume, presence of RBC and bacteria, motility, etc). Original Research Article British Journal of Medicine & Medical Research, 4(6): 1432-1441, 2014 1433 Results: Eighty-eight partners involved in the study representing 59% of total respondents were partners of primary infertile couples whereas 41% were partners of secondary infertile couples. Semen abnormalities were reported in terms of sperm motility, sperm concentration, pH and presence of bacteria and these were significantly different among primary and secondary infertile couples. Conclusion: Sperm abnormalities influence infertility among males of infertile couples. There is the urgent need to include male partners in the screening, detection and treatment of infertility among couples.
Hybrid MIMO-OFDM System for 5G Network Using VLC-A Review

The 5G mobile network promises to be faster and smarter and has lower latency and higher efficiency, lower bandwidth issues compared to 4G. A VLC uses LED for higher data transfer rate wireless communication. Wireless standards in broadband system LTE (Long Term Evolution) and MIMO (Multiple-Input-Multiple-Output) Wi-Fi technology incorporate an increase in antennas create more signal path which increases reliability and performance. This paper reviews the performance of VLC usage for the 5G network using MIMO-OFDM, Massive MIMO, SU (Single-user) MIMO, MU (Multi-user)MIMO and Hybrid MIMO which are optimised using various algorithms and presents a comparison of the techniques as mentioned above.
Third Party Messaging at the Network Edge

The ability to send messages to mobile subscribers has become immensely popular since the introduction of Short message Service (SMS). Despite of different messaging solutions today, SMS is still used for many services. The 5G core network and mobile terminals will support SMS transfer over non-access stratum messages. As a key technology for 5G Multi-access edge computing that distributes cloud intelligence at the network edge may be used to deliver context aware text messaging to mobile subscribers without the support of core network functionality. In this paper, we propose a new mobile edge service that enables third party applications to send messages to mobile subscribers. Third party text messaging at the network edge decreases the core network signaling and saves network resources while at the same time delivers timely location and context based information. The service is described by typical use cases, interfaces definition and the respective data model. Some implementation aspects are discussed related to the service state models supported by a mobile edge application and the platform.