Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote monitoring of BLDC motor using LabVIEW and zigbee

Brushless DC motors (BLDC) are preferred over brushed motors in industries because of many advantages such as increased reliability, reduced noise, higher speed range, better speed-torque characteristics, higher efficiency and high torque to weight ratio. This paper focuses on the remote monitoring of parameters of BLDC motor such as Temperature, Voltage, Current and Speed using Zigbee wireless technology and virtual instrumentation tool, LabVIEW. The results shown during the tests are accurate and the low-cost system is able to efficiently transmit the parameters remotely using ZigBee and display them on the LabVIEW front panel. The system can be of great importance in industries as it is not possible to manually access the motors functioning in hazardous environment. This system can also be used for predictive maintenance where the parameters monitored can be used to study the lifetime of the motor. The hardware requirements of the system are Arduino Microcontroller, two Zigbee (one as coordinator and other as end device), BLDC motor, an optical encoder for determining the speed of the motor, LM35 Temperature sensor for measuring the temperature, Current transducer, ACS712, for measuring the input current and Voltage transformer for stepping down the voltage before giving the input to Arduino to measure the voltage.
Model-Based Dynamic Control of Soft Robots

This work focuses on modeling and control of soft robots. It covers the entire development of the controller, from the modeling step to the practical experimental validation.From a theoretical point a view, large-scale dynamical systems along with model reduction algorithms are studied. In addition to the theoretical studies, different experimental setups are used to illustrate the results. A cable-driven soft robot and a pressurized soft arm are used to test the control algorithms. Through these different setups, we show that the method can handle different types of actuation, different geometries and mechanical properties. This emphasizes one of the interests of the method, its genericity.
Kronik tromboembolik pulmoner hipertansiyon Chronic thromboembolic pulmonary hypertension

*Kaliforniya Üniversitesi, San Diego, La Jolla, Kaliforniya, ABD; †Leuven Üniversite Hastanesi, Pnömoloji Departmanı, Leuven, Belçika; ‡Papworth Hastanesi, Kardiyotorasik Cerrahi, Cambridge, İngiltere; §Massachusetts Genel Hastanesi, Pulmoner Yoğun Bakım, Boston, Massachusetts; ||Kardiyotorasik Cerrahi, Paris-Sud Üniversitesi, Le Plessis Robinson, Fransa; ¶Charles Üniversitesi, Prag, Çek Cumhuriyeti; #Viyana Tıp Üniversitesi, Kardiyoloji, Viyana Avusturya; **Tokyo Tıp Üniversitesi, Kardiyak Cerrahi, Tokyo, Japonya; ††Padova Üniversitesi, Kardiyak, Torasik ve Vasküler Bilimler, Padova, İtalya; ‡‡Kerckhoff-Klinik, Torasik Ceerrahi, Bad Nauheim, Almanya Dr. Nick H. Kim,* Dr. Marion Delcroix,† Dr. David P. Jenkins,‡ Dr. Richard Channick,§ Dr. Philippe Dartevelle,|| Dr. Pavel Jansa,¶ Dr. Irene Lang,# Dr. Michael M. Madani,* Dr. Hitoshi Ogino,** Dr. Vittorio Pengo,†† Dr. Eckhard Mayer‡‡
Surgery of Primary Basal Cell Carcinoma with Frozen Section Controlled Excision

Amaç: Perioküler bazal hücreli karsinom (BHK) tedavisinde intraoperatif dondurulmufl kesit denetimli eksizyon ile rekürrensi de¤erlendirmek. Gereç ve Yöntem: Histolojik tan›s› bazal hücreli karsinom olan 30 hasta çal›flma kapsam›na al›nd›. Hastalar demografik verileri, tümör yerleflimi, boyutlar›, tümörün histolojik tipi ve rekürrens aç›s›ndan incelendi. Tüm hastalarda tümör 3 mm’lik sa¤lam cerrahi s›n›r b›rak›larak dondurulmufl kesit denetimi ile eksize edildi. Cerrahi s›n›rda tümör varl›¤›nda eksiyon geniflletildi ve ayn› seansta kapak rekonstrüksiyonu yap›ld›. Postoperatif tüm hastalara parafin kesit inceleme yap›ld›. Sonuçlar: Primer BHK tespit edilen 30 hastan›n yafl ortalamalar› 66,1±10,03 (45-82) y›l idi. BHK en s›k alt ve üst kapaklarda lokalize idi. ‹ntraoperatif dondurulmufl kesit denetimli eksizyon sonras›nda 5 (%16,7) hastada cerrahi s›n›rda tümör saptand›. Bu hastalarda tümör pozitif s›n›rdan eksizyon geniflletildi. Ortalama 18,46±6,22 (12-36) ay takip süresince hiçbir hastada rekürrens görülmedi. Tart›flma: Dondurulmufl kesit denetimli eksiyonu primer BHK’un cerrahi tedavisinde, tümörden ar›nd›r›lm›fl cerrahi s›n›r elde etmede ve rekürrensin önlenmesinde etkin bir yöntem oldu¤u kanaatindeyiz. (TOD Dergisi 2010; 40: 125-9) Anahtar Kelimeler: Bazal hücreli karsinom, frozen inceleme, rekürrens
Analyzing Delay Performance of Multi-hop Wireless Networks

In this paper a multi-hop wireless network is considered to analyze the delay performance. We assume that there is a fixed route between a given source and destination pair. The multi-hop nature of network may cause complex correlations of the service process. In order to handle them, we propose a queue grouping technique. An interference model is assumed which is set based. With the help of interference constraints the lower bound of delay performance is obtained. To achieve this systematic methodology is used. The simple-path delay-optimal policy we designed is used for wireless networks. Empirical studies revealed that our approach is good to optimize scheduling policies and analyzing delay in multi-hop wireless
Deep learning for field-based automated high-throughput plant phenotyping

The current rapid development trend in Artificial Intelligence (AI) provides a vast selection of high-quality tools to solve complex problems in more efficient ways than before. As a consequence, many fields of science and engineering are starting to explore AI tools, especially Deep Learning (DL) models for visual perception, audio understanding and decision making. This thesis explores the application of DL in plant science and agriculture to overcome the throughput bottleneck inherent in the currently practiced manual phenotyping in fields. Among many field-based phenotyping challenges, we focus on the problems of pod-counting and flower detection in soybean crop production. To accomplish this objective, we leverage the RetinaNet DL model with different backbones to process the raw image data collected by autonomous groundrobotic platforms. The proposed high-throughput phenotyping framework also involves tracking algorithms for robust decision-making using multiple image frames from the video data collected by the robots. In the thesis, we discuss the training data generation, model building and inference processes in detail. High degree of accuracy results presented in this study demonstrate the promise of DL tools for field-based automated high-throughput plant phenotyping. Hence, a framework such as the one presented here can dramatically transform agriculture in terms of scalability, precision and profitability.
EXTRACTION OF TEXTURE FEATURES FROM LOCAL IRIS AREAS BY GLCM AND IRIS RECOGNITION SYSTEM BASED ON KNN

Biometric systems are systems that enable individuals to be recognized in electronic environment using some physical and behavioral characteristics. Iris recognition system is one of the effective biometric recognition systems. The main goal of this study is recognition of the human from the iris images according to the local texture structures. The digital iris images were derived from CASIA database. The texture features were extracted from the four local iris regions of segmented image by using Gray Level CoOccurrence Matrix (GLCM). Totally 88 parameters were extracted for each image as a feature vector. Then, the obtained feature vectors were classified by using k-Nearest Neighbor (k-NN) classifier and the average performance of each system were compared according to different k values (1, 3, 5, 7 and 9). Finally, the best average performance among system architectures of iris recognition system was observed as 85 % in k=1 neighbor structure of k-NN classifier
Regression-Induced Representation Learning and Its Optimizer: A Novel Paradigm to Revisit Hyperspectral Imagery Analysis

This thesis presents a novel paradigm to analyze the remotely sensed hyperspectral imagery, i.e. hyperspectral dimensionality reduction, spectral unmixing, cross-modality fusion and learning. The trade-off between spectral robustness and discrimination is considered by regression-based representation models. Accordingly, the optimizers are designed for the solutions of these models. Results are assessed on several datasets in comparison with state-of-the-art methods.
Fault-Tolerant Inverter Operation Based on Si/SiC Hybrid Switches

The silicon (Si)/silicon carbide (SiC) hybrid switch comprising a Si insulated gate bipolar translator (IGBT) and a SiC metal-oxide-semiconductor field effect transistor (MOSFET) in parallel offers not only excellent performance and cost tradeoff but also inherent switch-level redundancy for potential power converter fault-tolerant operation. It is possible to operate the power converter even when either the SiC MOSFET or the Si IGBT experiences an open-circuit fault. This article first analyzes various switch failure scenarios and then proposes a novel fault-tolerant control strategy for a single-phase inverter based on the Si/SiC hybrid switches to mitigate a single-point switch failure and maintain inverter operation. Experimental results validate the effectiveness of the proposed fault-tolerant control strategy.
Design and Analysis of 5G Communication System in Multi-Channel OFDM

In this paper, we are going to analyze the simulink model of FFT based OFDM system for 5G communication. OFDM is a technique which is used for parallel transmission which is applied to achieve high throughput and better transmission quality. The use of OFDM in MIMO is used to achieve speed of data transmission which is much higher in amplitude than the current technology. We will be analyzing BER (bit error rate), error symbols and total symbols during the transmission and reception of the signal.
FontRNN: Generating Large‐scale Chinese Fonts via Recurrent Neural Network

Despite the recent impressive development of deep neural networks, using deep learning based methods to generate large‐scale Chinese fonts is still a rather challenging task due to the huge number of intricate Chinese glyphs, e.g., the official standard Chinese charset GB18030‐2000 consists of 27,533 Chinese characters. Until now, most existing models for this task adopt Convolutional Neural Networks (CNNs) to generate bitmap images of Chinese characters due to CNN based models' remarkable success in various applications. However, CNN based models focus more on image‐level features while usually ignore stroke order information when writing characters. Instead, we treat Chinese characters as sequences of points (i.e., writing trajectories) and propose to handle this task via an effective Recurrent Neural Network (RNN) model with monotonic attention mechanism, which can learn from as few as hundreds of training samples and then synthesize glyphs for remaining thousands of characters in the same style. Experimental results show that our proposed FontRNN can be used for synthesizing large‐scale Chinese fonts as well as generating realistic Chinese handwritings efficiently.
Design, Analysis, and Performance Evaluation of a UHF RFID Forward-Link Repeater

The range of UHF-RFID systems, involving passive tags, is typically limited by the tag’s RF harvesting circuitry. In this paper a forward-link UHF RFID repeater is proposed. The repeater amplifies the reader-to-tag carrier signal. Then, a passive RFID tag can be successfully identified from a much larger distance, compared to current technology, by exploiting the sensitivity of the reader. The proposed repeater consists of low-cost components; namely a pair of antennas, a low-noise amplifier and passive electronics. The proposed design also accounts for out-of-band emissions and the limitations posed by the maximum effective isotropic radiated power of the EPC UHF Gen2 standard. In contrast to prior-art, it can be deployed with any commercial RFID reader. Link-budget analysis reveals i) that the location of the repeater is of great importance to the system, ii) the range depends on the reverse link and not on the forward, as in typical RFID technology and iii) optimum performance can be achieved with bistatic RFID readers and RFID tags, capable of harvesting RF power at higher input power-levels. It is shown that with common, commercial, monostatic RFID technology, a maximum range of 80m can be achieved. By deploying bistatic configurations, which allow for improved reader’s sensitivity, the read-range could be extended to 350m. By “tuning” the tag’s front-end to achieve good matching for increased incident power levels, the expected range could be increased to 2km. Experimental results validate the performance of the proposed repeater and reveal how the link budget is affected by the tag’s front-end. 73m measured range is experimentally achieved with commercial monostatic RFID equipment.
Comparative analysis of selected human-computer interfaces

This article deals with the comparison of two technologies for manipulating 3D objects in terms of ease of use, ergonomics and intuitiveness. The comparison was based on the results obtained from the outcome of test tasks and questionnaires performed on the group of 15 people. Detailed research and test scenarios and additional questionnaires have been made. Each of the respondents had the opportunity to familiarize themselves with the device by performing three tests in two test scenarios (one per device).
Mobile Application for Indicating Phone Call Using Applications of IoT

IoT is the most emerging technology in recent era. Our day to day life has become smoother with the wide range of mobile applications. With the advancement in science and technology most of the human activities are being automated. People prefer automation rather than getting things done manually. Here the paper describes a system based on IoT for home automation. This paper demonstrates a home automation system that will indicate the user with lamps blinking when he gets a phone call.
The Activities of the Scapular Muscles during Isometric Contraction of Internal and External Shoulder Rotation

[Purpose] The activities of the scapular muscles during isometric contraction were measured to examine the mechanism of scapular stability. [Method] The activities of the scapular muscles were measured during isometric contraction of internal and external shoulder rotation at 0 degrees and 90 degrees abduction with three kinds of resistance loads. Scapular muscles were classified into agonists and antagonists of each motion, and the changes in each muscle activity were analyzed. [Results] The integrated electromyograms of both agonists and antagonists increased significantly with increasing resistance load in internal and external rotation at 0 degrees and 90 degrees abduction. In the case of the strongest resistance load at 0 degrees abduction, the integrated electromyograms of the agonists showed from 14 to 24 times as much as the start position and those of antagonist showed from 3 to 5 times that of the start position. At 90 degrees abduction, the integrated electromyograms of agonists showed from 2 to 12 times and those of antagonists showed from 2 to 7 times. [Conclusions] All scapular muscles needed to be active during concentric contraction of shoulder rotation. We consider that the agonists might work against external force and the antagonists might contribute to the stability of the scapula and trunk, in light of a previous study.
Ambulatory Function in Men with and without HIV Infection: Association with Cardiorespiratory Fitness

Objective: The study purpose was to compare ambulatory function in men with and without HIV infection, and test the association with aerobic exercise capacity. Methods: We conducted a cross-sectional study of 45 HIV-infected men and 37 age and race-matched HIVuninfected men at the Baltimore VA Medical Center. Participants performed cardiorespiratory exercise testing, sixminute walk (6-MW) and the 400-meter long distance corridor walk (LDCW) as part of a study of veterans without history of CVD. Results: The mean (SD) age was 55 (6) years. Among the 82 male participants, 98% were African American race. The 6-MW distance correlated with aerobic exercise capacity (VO2peak) in both HIV-infected subjects (r=0.50, p 0.1). Between HIV groups, there was a significant difference in LDCW (p=0.01) but not in 6-MW (p=0.3). Conclusions: In HIV-infected men without known CVD the 6-MW and LDCW, provide similar estimates of aerobic exercise capacity. The findings are comparable to uninfected men with similar demographic and clinical characteristics, and support endurance walk tests to estimate aerobic exercise capacity in HIV-infected patients.
Online Environments for Supporting Learning Analytics in the Flipped Classroom: A Scoping Review

: The Flipped Classroom (FC) is an instruction method, where “events that have traditionally taken place inside the classroom now take place outside and vice versa”, which has known a significant surge of popularity in the past decade. In FCs, different types of activities may take place depending on the session type (pre-class, in-class, or after-class), the learning objectives to fulfil, the type and size of the class, the available infrastructure, the time available etc. In order to support the activities taking place in FCs, instructors can use various technological tools and online environment, especially to support the preparation of students before class. A marked recent trend in the FC is the increased use of Learning Analytics (LA) to support the development of the FC and students’ reflexive learning. However, there has been no systematic investigation into combining LA and the FC, and it appeared that there was a lack of research on the issue. The aim of this paper is to investigate the literature on applications of LA in FCs, and to determine the best practices and needs for technological development supporting LA in the FC. In order to perform this study, we did a scoping review of literature in the subject to determine research trends in the use of LA in the FC. We conclude that there is great potential to use LA in the FC, and try to project where further research is heading.
Identificação e impacto clínico de fração de ejeção preservada em pacientes admitidos por insuficiência cardíaca descompensada

Identification and clinical impact of preserved EF (ejection fraction) on in-hospital outcomes in patients with acute decompensated heart failure (HF) remain poorly defined. Methods. Consecutive admissions for decompensated HF, defined by Boston criteria equal to or higher than to 8 points, at a tertiary care hospital in Brazil were included. Preserved systolic function was defined as left ventricular EF ≥ 50%. Approximately 80 clinical variables based on history, physical examination, laboratory and echocardiographic data were evaluated to identify predictors of preserved EF at admission. Included patients were followed up through hospitalization to discharge or death. Results. Overall, 721 consecutive HF admissions were enrolled (66 ±13 years, EF= 42 ±17%, 50% male) and preserved EF was identified in 224 (31%). Patients with acute decompensated HF and preserved EF presented with distinctive clinical characteristics: older age, female gender, non-ischemic etiology, higher prevalence of chronic atrial fibrillation, lower hemoglobin levels, lower pulse pressure and wider QRS complexes. No significant differences were observed on in-hospital mortality according to quintiles of EF, but we observed a trend toward increased clinical complications in patients with higher EF. Conclusions. Preserved EF is a prevalent and morbid condition among hospitalized HF patients.
Bir Terörist Saldiri Sonrasinda Travma Sonrasi Stres Bozukluğu Gelişimini Etkileyen Risk Faktörleri

Amaç: 03 Ocak 2008 günü Türkiye’nin Güneydoğu Anadolu Bölgesi’nde bulunan Diyarbakır’ın işlek bir caddesinde otomobil içerisine konulan patlayıcılarla terörist bir saldırı gerçekleşmiştir. Bu çalışmada meydana gelen bu patlamaya görsel ya da işitsel olarak tanık olan kişilerde patlamanın 1 ve 3 ay sonrasında Travma Sonrası Stres Bozukluğu (TSSB) oranlarını ve TSSB gelişimi açısından risk faktörlerinin saptanması amaçlanmıştır.
Heuristics for Efficient Resource Allocation in Cloud Computing

The resource allocation in cloud computing determines the allocation of computer and network resources of service providers to service requests of users for meeting user service requirements. It is not scalable to solve the resource allocation problem as an optimization problem to obtain the optimal solution in real time. This paper presents the development and testing of heuristics for the efficient resource allocation to obtain near-optimal solutions in a scalable manner. We first define the resource allocation problem as a Mixed Integer rogramming (MIP) optimization problem and obtain the optimal solutions for various resource-service problem types. Based on the analysis of the optimal solutions, we design heuristics for the efficient resource allocation. Then we evaluate the performance of the resource allocation heuristics using various resource-service problem types and different numbers of service requests and resources. The results show the comparable performance of the heuristics to the optimal solutions. The resource allocation heuristics also demonstrate the better computational efficiency and thus scalability than solving the MIP problems to obtain the optimal solutions. Keywords: Resource allocation; Clouds computing; Heuristics; Mixed integer programming
Fault handling processes in district heating customer installations : Current and future solutions

When trying to integrate more fossil-free heat sources such as renewable energy and heatrecycled from other processes into the current district heating systems, problems occur due tothe high temperature levels in the systems. There are many reasons to why the temperaturelevels are high, but one frequently occurring issue is that the return temperatures of thecustomer installations are undesirably high due to faults in the substations or internal heatingsystems of the installations. This cause the return temperature of the entire district heatingsystem to increase. Therefore, it is of great importance to be able to identify the customerinstallations with high return temperatures and eliminate the faults that are causing the hightemperature levels.The focus of this thesis has been to investigate what fault handling processes are currentlybeing employed by district heating utilities to detect customer installations containing faults,and what could be done in addition to improve these. The first aim was to gather experiencesfrom the existing district heating systems about how the utilities are working with their cus-tomers to decrease the system temperatures, and what faults are currently the most commonones. The second aim of the thesis was to investigate if the customer data that is availablefrom the customers could be used to detect when and where a fault occurs. This was of interestsince the large amount of customer installations in the district heating systems makes it hardto manually survey the performance of all installations. Therefore, automatic fault detectionmethods are needed.The overall results show that the most important aspects of the faults handling process isto clearly involve the customer in the process and for the utilities to gain physical access to,and mandate to fix faults in, the customer installations. The results also show that the faultdetection methods developed in the thesis are able to detect installations containing faults andthat they may be a good addition to the already existing fault handling processes to simplifythe work at the utilities