Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum Average Power Control for Linear Systems with Random Communication Delays

The paper studies the long-time average cost control for discrete-time linear networked feedback system via state feedback, where the transmitted effort is assumed to be expensive. The control signals are assumed to be linearly encoded, and an unreliable channel, which subjects to random transmission delays as well as packet dropout with certain probability, is placed in the path from the encoder to the receiver/decoder. At the terminal of the channel, a convex combination of the received data is used to actuate the plant. The design of state feedback law and encoder is based on the mean-square small gain theorem for the system. The optimal average transmitting power problem is solved in terms of a stabilizing solution of a discrete algebraic Riccati-like equation (DARE). A necessary and sufficient condition for the existence of the stabilizing solution of the DARE is presented. An effective algorithm to obtain the solution of the DARE is provided. Moreover, a numerical example is illustrated to verify the proposed results.
A Dual Band Wilkinson Power Divider with Extended Band Ratio

In this paper a new dual band Wilkinson power divider (WPD) with extended band ratio has been proposed. The proposed WPD has been developed by replacing each transmission line (TL) of the single band WPD with the dual band TL. In order to validate the proposed technique, a dual band WPD for Long Term Evolution (LTE)0.7GHz and Wireless Local Area Network (WLAN) 5.8GHz has been developed and tested. The comparative analysis has been done to report the novelty of the proposed WPD.
Manufacturing Stacks: from Reference Models to Technology Stacks for Digital Manufacturing

A number of initiatives promote the topic of digital manufacturing, i.e., the adoption of pervasive, fine-grained cyber-physical systems (CPS) and of data-driven optimization techniques within the manufacturing domain, both in order to gain efficiency while running conventional operations and to allow for new production and business models such as mass customization or networked value chains.In this context, we contribute the findings from our experience in pursuing this vision through two projects with different goals (gradual improvement over current operations vs. more ambitious rethink), target maturity of their results (production-grade vs. proof-of-concept pilots), and therefore approaches. Concretely, we first elaborate on the often neglected line-level automation and the importance of making it a first-class citizen in digital manufacturing, especially for transitioning current manufacturing facilities into future scenarios. We describe the approach and reference the specific technologies used for its production deployment on the factory floor at a customer organization. We then introduce the positioning, within a second stack jointly prototyped with partner organizations, of reasoning algorithms. As entry points for added autonomy into manufacturing systems, they pave the way for automatic (re)configuration from high level goals and for error recovery.This contribution provides insights on how to design the next generation of software architectures for manufacturing, and aims to contribute to the transition from early reference architectural models into design blueprints for actual technology stacks.
Robot Localisation in 3D Environments Using Sparse Range Measurements

This paper presents an algorithm for mobile robot localisation given a map of a 3D environment and a sparse set of range-bearing measurements. The environment is represented using a spline approximation of its vector distance function (VDF). For a given location in the environment, VDF encodes the distance to the nearest occupied region along three orthogonal axes. VDF is first obtained from an occupancy voxel map and its three components are then approximated in the least-square sense using a set of three dimensional cubic b-splines, providing a rich and continuous representation of the environment. First and second order derivatives of the VDF are also computed and stored. The difference between an observed range measurement in a given direction and its expected value is formulated as a function of the robot location and the spline coefficients representing the VDF. This leads to a non-linear least-squares optimization problem that can be solved to localise the robot given a set of such measurements. It is demonstrated that a sparse set of range-bearing measurements, an order of magnitude smaller than what is typically available from 3D range sensor is adequate to achieve accurate localisation. The algorithm presented is illustrated using a number of examples including a single point range sensor mounted on a pan-tilt head to localise a robot moving in an indoor environment.
Direct Modulation Piezoelectric Micro-Machined Ultrasonic Transducer System (DMUT)

This paper demonstrates, for the first time, a new underwater communication scheme based on the Direct Modulation (DM) of an array of piezoelectric Micro-Machined Ultrasonic Transducers (MUT). The use of this new modulation scheme permits to achieve more efficient data transmission compared to what could be attained through conventional continuous waves-based (CW) driving approaches. In addition, as the received information can be extracted without the employment of mixers or amplifiers, it enables lower power consumption and low noise-figures. In this work, we report on the performance of the first dMUT-prototype. This system, which relies on a Bipolar Junction Transistor (BJT) to periodically connect and disconnect an array of pMUTs to a DC-biased filter (Fig. 1), exhibits power consumption of 140mW and enables transmitted energy-per-bit of $0.7\mu J$. Such a value is two orders-of-magnitude more efficient than what attained through conventional communication approaches for underwater networks [1]–[3].
On the Practical Limitations of Electronic Beamsteering using Metamaterials at 28 GHz

In this paper, the practical limitations and constraints of electronic (active) beamsteering using metamaterials at 28 GHz, in terms of the parasitic elements introduced by varactor diodes, are addressed. Parametric studies will be presented to ascertain the insertion losses of both series inductance and resistance of the varactor diodes used at unit-cell level, in addition to their bandwidth, frequency of resonance and maximum phase shift yielded. This study and characterisation has been performed in simulation environment using CST Microwave Studio.
Sizing and multi-objective optimization of a multisource micro-grid with storage for an economic activity zone

Micro-grid is promoted as an economical and efficient energy system in which different renewable sources and storage are interconnected to meet the load power demand at any time. This paper studies a micro-grid simulation for sizing of hybrid power production system consisting on PV/Wind sources with battery storage. A dynamic simulator process is adopted for the sizing of this system. Later a multi-objective optimization study is established with economic activity zone load and different evaluation to look for all the best compromises between four criteria: Loss of Power Supply Probability (LPSP), Embodied Energy (EE), Greenhouse Gas (GHG) and Life Cycle Cost (LCC). A front Pareto is build through the genetic algorithm.
ANN Based Fundamental Current Extraction Scheme for Single Phase Shunt Active Filtering

Current harmonics are one of the major causes for grid pollution. Shunt active power filters (SAPFs) are employed for harmonic current compensation. Separation of fundamental and harmonic currents is essential for the control of SAPF. Artificial neural networks (ANN) are an attractive option for the extraction of fundamental current components. The use of power converters such as rectifiers and ac voltage controllers often result in discontinuity in the current. In three phase systems, the discontinuity does not impact the ANN based extraction as three current quantities are available as input to the ANN. However, in a single phase system, extraction cannot be carried out in case of a discontinuity in the waveform. For a single phase system, this paper proposes ANN based fundamental active current extraction with single phase to three phase transformation. ANN separates the fundamental active and harmonic components with the help of the 3-phase currents obtained through the transformation. Thus, extracted fundamental active component is used for controlling the SAPF to ensure total current harmonic distortion within the 5% limit. The performance of the proposed extraction scheme is evaluated for loads and the proposed extraction technique is compared with the other techniques for the purpose of validation.
A Game Theoretic Approach for Service Chain Composition in Network Function Virtualization Network

Network functions virtualization (NFV) is a network architecture that visualizes entire classes of network node functions into software to create Network Service (NS). In this paper, the service chain composition problem in NFV Network is investigated. We leverage non-cooperative game theory to provide a solution to the above-mentioned problem. The service chain composition is converted to the seeking of the potential function under the game framework. By using semi-tensor product of matrices (STP), the potential function of the formulated game is presented and the service chain composition is achieved. Finally, an example is studied to illustrative the effectiveness of the results.
The Influence of Student Abilities and High School on Student Growth: A Case Study of Chinese National College Entrance Exam

Enabled by available educational data and data mining techniques, educational data analysis has become a hot topic. Current researches mainly focus on the prediction of problems and performance rather than revealing the underlying causal relationships. Based on a unique exam data, we extracted the abilities of examinee from HSEE (High School Entrance Exam) based on the knowledge of educational experts, then we measured student growth from middle school to high school in total score and subject scores. We studied the impact of high school ranking and student abilities of HSEE on student growth by multiple linear regression model, in which high school ranking is divided into 5 levels, Level 1 being the best and Level 5 being the poorest. We found that: 1) the higher of the ranking of the high school was, the higher of their student growth in total score was, but there were exceptions in Level 4 and Level 5 schools. The growth in subject scores did not follow the same rule. Level 3 schools performed better than Level 2 schools in student growth in Physics, and Level 2 schools performed better in student growth in Chemistry. 2) Student abilities in HSEE have different impacts on student growth in total score and subject scores. For student growth in total score, the abilities of English memory and Math analysis and solutions have larger positive influences than the other abilities. For student growth in the subject score, most abilities have a negative impact on the growth of the same subject, except for English listening and memory. Our research can not only help educational authorities evaluate the impact of high schools on the variations of student abilities to ensure equity and efficiency, but also help students and parents choose schools based on student abilities and the characteristics of high schools.
Profil hématologique des patients infectés par le VIH à Conakry

hma.2011. 0630 Auteur(s) : Andre Loua1,,2 loua.andre@yahoo.fr, Cece Dominique Dramou2, Nyankoye Yves Haba1,2, Fode Bangaly Magassouba2, Mathieu Lamah2, Abdoulaye Camara2,3, Mohamed Cisse4, Kovana Marcel Loua2,5, Emile Pe Gamy2,5, Xavier Troussard6 1 Centre national de transfusion sanguine, BP 2737, Conakry 2 Departement de pharmacie, Universite de Conakry 3 Laboratoire central de biologie medicale, Hopital national Ignace-Deen, Conakry 4 Service de dermatologie-venerologie-IST, Hopital [. ]
Sensor fault detection using a new online reduced rank kernel PCA for monitoring an air quality monitoring network

Process monitoring has a Great interest in the industry, due to their capacity to ensure safety operation and to maintain product quality. Therefore, the idea of this paper is to improve the fault detection performance of conventional Kernel Principal Components. In this context, a new online method based on the Reduced Rank KPCA approach has been developed for sensor fault detection of a dynamic nonlinear process. To demonstrate the efficiency of the proposed method with adaptive model compared to the conventional KPCA and the Reduced Rank KPCA, the fault detection performances are illustrated through a simulated air quality-monitoring network AIRLOR.
Distance Education as a Service System

Distance education (DE) is the teaching method that grows the most in Brazil, and as the enrolment number grows, the challenges expand with it, because the teaching organizations need to structure themselves to attend the increasing demand. In this scenario, DE should be viewed not just in the technology basis, but rather with a systemic view that is compounded by all teaching modality aspects such as learning, teaching, communication, creation and management. Due to this need, it aims to analyse DE as a service system, like it is defined in the Service Science perspective, as dynamic settings of resources (people, technologies, organizations and shared information) to generate a mutual value. In doing so, it proposes the conceptual model DE-SS that provides a holistic vision of relations among resources and stakeholders in a distance education system.
The AFarCloud ECSEL Project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate identification and proper quantification of pathogens affecting plant and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate FARming in the CLOUD) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision-making solutions based on big data and real-time data mining techniques.
Frequency-selective Filter Based Frequency Separated Feedback Control of Linear Systems: State Feedback Case

This paper presents a new frequency-selective filter based frequency separated feedback control strategy for disturbance attenuation over multiple frequency ranges. The measured output/state of the plant is firstly separted/divided into auxiliary frequency-limited outputs/state by introducing a group of pre-specified frequency-selective filters. Furthermore, a group of frequency-selective controllers is designed to render the frequency-selective component of the closed-loop system. With the aid of generalized KYP lemma, the design of control gains can be recasted into solutions to a set of linear matrix inequalities(LMIs). Finally, the effectiveness of the proposed method is illustrated via numerical examples.
A Survey on Multi-unmanned Aerial Vehicle Communications for Autonomous Inspections

The system design of autonomous Unmanned Aerial Vehicles (UAVs) poses several challenges for the wireless communication concerning performance, resiliency, and scalability. The UAV system is typically restricted by flying time limitations due to energy constraints and can benefit from coordination of tasks among UAVs. It may further profit from cooperation between UAVs to share information context, maintain flying formation, extend communication range etc. In this paper, we review communication schemes for clusters of autonomous UAVs cooperation. Performance metrics for assessing those schemes are investigated. We provide a survey of candidate wireless communication technologies considering a power line inspection target application. Performance measurements and UAV related channel modeling of those candidate technologies are reviewed. We present how the requirements of the UAVs communication system are identified through the application specification.
A Compact Wearable Textile Antenna with Dual Band-Notched Characteristics for UWB Applications

This paper presents design and simulation analysis of a Compact Wearable Textile Antenna with Dual Band-notched characteristics for UWB applications. The antenna consists of a CPW fed semicircular radiator with two semicircular split ring resonators (SSRR). The antenna has a dimension of 43mm $\times 40$ mm $\times 2$ mm, designed on the leather substrate with dielectric constant 1.65 and a loss tangent of 0.02 and uses copper foil as conducting material. The frequency band-notched characteristics are achieved by inserting two semicircular split ring resonators (SSRR) on the patch of the antenna. The first notch band is obtained from 2.3 – 2.5GHz for Bluetooth application band and the second notch band is obtained from 3.3 – 3.7GHz for WiMAX (IEEE 802.16) application band. It is observed that the notch frequencies can be controlled by varying the widths of the slots, the distance between two semicircular rings and the two ends of the semicircular ring slot. The simulated frequency results show that the antenna has an impedance bandwidth of 1.8 – 10.7GHz and reflection coefficient less than -10dB, except the two eliminated bands to reject the Bluetooth application band at 2.4GHz and the WiMAX application band 3.3 - 3.6GHz. Ansys HFSS Electromagnetic simulator has been used for simulations and results are presented.
Spintronic THz Generation Using a Silicon-based Fe/Pt Bilayer as the Radiation Source

A spintronic bilayer structure of 2-nm Fe and 3-nm Pt was fabricated by molecular beam epitaxy on a Silicon substrate. We demonstrate that this Fe/Pt on Si heterostructure is an efficient and convenient alternative terahertz emitter particularly for systems which are driven by femtosecond fiber lasers with 1550-nm output wavelength.
Endocrine Psychiatry: Solving the Riddle of Melancholia

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing endocrine psychiatry solving the riddle of melancholia as the reading material.
A Resonant Reflection Type Microwave Reference Sensor for Testing of Small Biomolecules

Electromagnetic analysis of small biomolecules, such as amino-acids, is important in development of new methods for biomedical therapy and diagnostics based on the dielectric properties of biomolecular solutions. The dielectric behavior of amino-acid solutions is especially interesting in microwave band, because they possess their dielectric signature at around few GHz. We apply our biophysical insights from the rotational dynamics of a particular amino-acid to rationally select the operation frequency and, therefore, to design a microwave reference sensor resonating at the operation frequency of interest. The proposed sensor is based on a coplanar waveguide (CPW) terminated with flares to impedance-match the line at the operating frequency of the complementary split ring (CSRR) sensing element on the other side of the substrate. The unique design of sensing element gives freedom in testing of water-based bio-molecular solution without disturbing the electromagnetic field of CPW. The proposed sensor is comprised of two sensing elements operating at the same frequency, while one of them works as the reference sensor. Our results contribute to the label-free microwave based technologies for the analysis of the biomolecular components of proteins - main nanomachines executing life processes.
A methodology to compute long-term fault resilience of NoCs under fault-tolerant routing algorithms

Networks-on-Chips (NoCs) are the preferred communication interconnect for many-core systems. Technology scaling increases the susceptibility to failures in the NoC’s components. Fault-tolerant routing algorithms are applied to maintain reliable operation in the presence of such failures. Fault resilience is a measure of a NoC’s ability to tolerate faults. In this paper, we investigate how fault resilience develops over a long period of time during which faults appear and disappear. We apply Markov reward models to investigate long-term fault-resilience of mesh-based NoCs under three different routing algorithms. Fault-tolerant XY routing brings the best long-term fault resilience even though it is less adaptive than fault-tolerant negative-first routing. We further investigate how long-term fault resilience develops with scaling towards larger NoCs.
Constructing Preconditioner Based on Tight Frame for Bernoulli Random Sensing Matrix in Compressed Sensing

Compressed sensing (CS) is an attractive research topic. The critical process - sparse recovery has drawn many scholars’ attention, but the performance is usually hard to guarantee. In linear algebra and numerical analysis, preconditioning technique is a process that transforms a given problem into a form that is more suitable for numerical solutions. In this paper, we investigate the problem of applying preconditioning to improve the performance of CS system. In order to facilitate projection, Bernoulli random sensing matrix is considered. We formulate the model to design the preconditioner by making the product of preconditioner, sensing matrix and dictionary approximate to a tight frame which has been proven valid in the design of CS system. The analytical form of the preconditioner is derived efficiently. Simulations are carried out to demonstrate the superiority of the proposed method compared with other existing work.
Thumb Controlled Low-Cost Prosthetic Robotic Arm

Not everyone is gifted with perfect limbs. There are people in this world who lose their precious body parts in accidents or diseases. They are also not up to speed with the staggering development of technology and productivity. To solve this issue, the area of prosthetic limbs has been widely explored since its inception. However, the existing solutions are financially out of the reach for general people of developing countries. In this paper, a low-cost robotic arm has been proposed which is affordable to above or below elbow amputees. Using servo motors, Arduino UNO, end effector etc. to construct the proposed system can enable a person to move, grasp and replace objects that are heavy or require both hands to carry. A prototype of the model has been made to show the efficiency, productivity and cost analysis of the proposed system. The result displays that the system is cost-effective and affordable to the poverty-stricken section of the community.