Miracle-dz/UniFAR-FTUs huggingface dataset:
SUMO performance comparative analysis: C vs. Python

Mobility is an essential part of modern societies. Urban mobility has three important goals, namely Safety, Efficiency and Sustainability. Modern cities have a number of challenges ahead. To name a few, population levels are increasing together with increments in pullution, energy demand and environmental impact. A very important element within urban mobility is Traffic Simulation[4]. There is no doubt about the importance of the development of accurate traffic simulations in particular for an efficient trafficmanagement and planning. In that context, there is an outstanding tool, SUMO (Simulation Urban Mobility)[3][1], which is not only a complete and customizable microsimulation platform. It is also changing the game rules with its open software approach. Its community of developers is very alive and growing everymonth, likewise the number of research groups that embrace this tool as main technology for their research plans. However, SUMO still lacks of something that will be clearly a deal breaker for local administrations regarding other tools and platforms [3][1]. That is performance. Traffic networks are generally very big and computationally expensive to simulate. Realtime performance levels are needed for on-line use. In our lab we are aiming at the parallelization of SUMO, but before of that move, we are evaluation the performance improvement through shifting from Python to ANSI C as programming language. We have studied how SUMO works. SUMO makes its calculations in Phyton[2]. Phyton is a high level multi-platform programming languaje. Its object oriented approach and its portability may yield an inncecessary headover regarding SUMO performance. We use python because the SUMO engine is implemented in that language, and researchers when want to communicate with SUMO through TraCI use that high level language. However, here we present some promissing results using C for several modules. In this work we compare two versions of SUMO, the outof-the-box based on Python and a second one, developed in our lab with some modules in C instead. We present a performance comparison study, using that two versions of SUMO. For our experiments we have used a simple network, consisting of in a two lanes motorway. We simulated a vehicle flow, between fifty and one hundred cars Eurocast 2017, February 19-24, Las Palmas de Gran Canaria Extended Abstracts
Klasifikasi Diabetes Retinopati Menggunakan Metode Statistical Region Merging Dan Convolutional Neural Network

Abstrak Diabetes Retinopati merupakan salah satu gangguan penglihatan yang terjadi pada retina mata. Bila penyakit ini terlambat ditangani, penderita akan mengalami kebutaan. Peningkatan keparahan DR dapat dicegah jika dilakukan perawatan dan pemeriksaan dengan tepat. Pemeriksaan secara manual oleh dokter mata, akan menyita waktu dan hasil pemeriksaan bergantung pada keahlian dokter dalam mendiagnosis. Maka dari itu, diperlukan sebuah sistem yang dapat mendiagnosis secara cepat, akurat, dan objektif. Berdasarkan permasalahan tersebut, pada Tugas Akhir ini penulis merancang suatu sistem yang dapat mengolah citra digital fundus mata dan mengklasifikasikannya berdasarkan tingkat keparahan DR. Tingkat keparahan DR pada Tugas Akhir ini dibagi menjadi 4 kelas yaitu normal, mild NPDR, moderate NPDR, dan severe NPDR. Data yang digunakan pada penelitian ini adalah data sekunder dari dataset MESSIDOR. Sistem yang dirancang pada Tugas Akhir ini menggunakan metode segmentasi ciri Statistical Region Merging dan metode klasifikasi Convolutional Neural Network. Jumlah data yang digunakan adalah 80 citra, yang terdiri dari 20 sampel citra untuk masing-masing kelas. Nilai akurasi tertinggi yang diperoleh dari sistem ini adalah 81,25% dengan waktu komputasi 14,598 detik. Nilai akurasi tersebut didapatkan dengan menggunakan perbandingan 3:2 data latih dan data uji, nilai kompleksitas segmentasi Q=256, jumlah epoch=100 dan nilai learning rate=0,0001. Kata Kunci: DR, NPDR, SRM, CNN. Abstract Diabetes Retinopathy is one of the complications of Diabetes Mellitus, this complication occurs in the retina of the eye. Patients will experience vision problems and if it handled late, patients will experience blindness. Manual examination by an ophthalmologist will take time and the results of the examination also depend on the doctor’s expertise in diagnosing. Therefore, a digital image processing system which able diagnose quickly, accurately, and objectively, is needed. Based on these problems, in this Final Project the author desing a system that can process digital fundus images and classify them into 4 classes namely normal, mild NPDR, moderate NPDR, and severe NPDR. The data used in this study are secondary data from the MESSIDOR dataset. The data is processed using Statistical Region Merging (SRM) segmentation method and is classified using the Convolutional Neural Network (CNN) method. The number of data samples used in this thesis is 80 images, which consist of 20 image samples for each class. The highest accuracy value obtained from this system is 81.25% with a computational time of 14.518 seconds. The accuracy value is obtained by using a ratio of 3:2 training data and test data, the value of segmentation complexity parameters Q=256, the number of epochs=100 and the learning rate=0.0001. Keywords: DR, NPDR, SRM, CNN.
Design Immersion and Virtual Presence

96 Proceedings: Bridging the Gap (1996); J. Glymph, D. Shelden, C. Ceccato, J. Mussel, and H. Schober, “A Parametric Strategy for Free-Form Glass Structures Using Quadrilateral Planar Facets,” Automation in Construction 13, no. 2 (2004): 187–202; G. Lee, R. Sacks, and C. Eastman, “Specifying Parametric Building Object Behavior (BOB) for a Building Information Modeling System,” Automation in Construction 15, no. 6 (2006: 758–776.
Planejamento de Rede de Monitoramento de Estruturas Empregando-se LST (Laser Scanner Terrestre)

Neste trabalho, são apresentados os procedimentos realizados no projeto de uma rede de monitoramento geodésico de uma barragem, empregando-se Laser Scanner Terrestre (LST). A premissa de que o modelo final do objeto tridimensional monitorado é gerado através da concatenação de diversas nuvens de pontos, obtidas a partir de várias estações de observação, norteou a definição de alguns critérios considerados no planejamento da coleta de dados em campo com LST. A definição desses critérios se deu a partir de testes realizados com o Laser Scanner FARO FOCUS 3D 120, em 9 diferentes cenários. Nos quais foi analisada a influência que alguns parâmetros, como a resolução da nuvem de pontos e a distância do LST em relação ao objeto, podem exercer no resultado final do monitoramento. Desta forma foi possível propor três diferentes hipóteses para a rede, baseadas nesses critérios. Em um modelo digital 3D da barragem da Usina Hidrelétrica (UHE) Mauá, local para o qual foi realizado o estudo, simulou-se amostras de dados para cada uma das três hipóteses. Estes dados foram utilizados nas equações de propagação de erros, gerando as incertezas esperadas para os pontos objeto de cada cena. A análise incluiu também as incertezas posicionais em função do diâmetro do feixe laser. Por fim, foi eleita a rede que melhor atendeu as expectativas do monitoramento do ponto de vista das precisões e da funcionalidade de coleta de dados em campo.
Suitability of Finite State Automata to Model String Constraints in Probablistic Symbolic Execution

Probabilistic Symbolic Execution (PSE) extends Symbolic Execution (SE), a pathsensitive static program analysis technique, by calculating the probabilities with which program paths are executed. PSE relies on the ability of the underlying symbolic models to accurately represent the execution paths of the program as the collection of input values following these paths. While researchers established PSE for numerical data types, PSE for complex data types such as strings is a novel area of research. For string data types SE tools commonly utilize finite state automata to represent a symbolic string model. Thus, PSE inherits from SE automata-based symbolic string models to calculate the probabilities of string-based constraints describing program paths. However, to our knowledge, there is lack of research on suitability of automatabased symbolic string models in the context of PSE. This thesis proposes four automata-based symbolic string models for PSE and analyzes their suitability using two criteria: accuracy and performance. We compare the probability computed by the model to the actual probability and the amount of time took to compute it. Our results show that each model varies in their accuracy, however none is able to consistently compute actual value. In addition, our evaluation did reveal that this amount of inaccuracy depends upon the characteristics of a software program. From these findings we suggest guidance when selecting an automaton model for PSE based on the performance and accuracy requirements and the characteristics of the program under analysis. Additionally, we suggest future areas of research to the accuracy and performance deficiencies observed in our evaluation.
Academic Performance Prediction for Engineering Students using RBF-SVM Classification Model Case Study: PPU.

Predicting student performance is becoming more challenging due to large amount of data in the educational databases. Data mining tools could be used to explore academic databases with the objective of extracting knowledge about student’s performance. Machine learning (ML) teaches computer to learn and make decisions, ML tools may include but not restricted: Decision Trees (DT), Artificial Neural Networks (ANN), Support Vector Machines (SVM). etc. The academic databases at Palestine Polytechnic University (PPU), contain millions of records of data about tens of thousands of students over the last 40 years. In this thesis, we decided to extract a subset of this huge data, and build our own data set which contains the most important features about engineering students according to expert advice at PPU. Then, we have built our model using SVM as a classifier and the Radial Basis Function (RBF) with linear kernels as a pre-processor for feature selection. The proposed model is used to predict student performance at PPU. The data set of students in the engineering discipline is used as a benchmark. Results of our model show excellent classification accuracy and AUC for the student’s performance, highest obtained accuracy and AUC is 96% for optimized RBF-SVM model using the genetic algorithm and grid search method, these results make the model a reliable one to be generalized for the university students from other disciplines. Furthermore, it could be developed to be used by instructors, academic supervisors and students to take proactive steps to improve learning strategies.
Augmented reality applications: A Meta-analysis and thematic analysis

﻿ The purpose of this study is to determine the effect of augmented reality (AR) applications on academic success through meta-analytic and thematic analysis. 51 items from 45 studies conducted between 2013 and 2019 were examined in different databases on the effect size of AR in relation on academic success, education level, and duration of the application. The effect size was found to exist at a medium level, considered to be significant which means that AR has positive effect on academic success. In terms of thematic analysis, with reference to common codes and themes found in qualitative studies conducted both nationally and internationally, qualitative findings were obtained. An emphasis on the effect of AR on learning, class environment and affective dimensions was made, together with a consideration of some limitations. It was stated that learning environments could be arranged in such a way that students could be motivated through the use of AR, leading to permanent and solid learning. Therefore, careful and planned use of AR can be said to encourage success.
Desgaste muscular en caquexia asociada a neoplasia: mecanismos proteolíticos implicados

SUMMARY Muscle waste in cancer cachexia, proteolytic mechanism The cachexia associated to neoplasm is a syndrome characterized by a remarkable loss of weight, anorexia, loss of muscle mass and anemia. In fact, a high percentage of patients who die of advanced cancer show cachexia. The cachexia condition is associated with the presence and the growth of tumor that produces a condition of malnutrition as a consequence of anorexia. On the other hand, the metabolic disorders and the competence for nutrients between tumoral and normal cells induce an accelerated condition of wear out of patients. Though, it is certain that this accelerated wear out is caused by anorexia and the metabolic disorders that produce the hypermetabolism, all together explain to a great extent the events present in this syndrome however, the molecular disfunctios cannot be left aside. In this sense the proteolytic system is of great importance, in animal models with developed tumors as in patients with cancer, it is observed an increase in the expression and activity of the proteolyses system; both, lysosomal and non lysosomal, in particular the proteolytic system dependent of ATP and ubiquitin “proteasome”.
Pain in neonates and children: assessment and non-pharmacological interventions

Pain is a multidimensional phenomenon which is influenced by biological, psychological, social, and cultural factors. Pain is a subjective experience, but it could be measured through self/hetero-report and objective signs of physiological and psychological changes. Scientific evidences show wellestablished instruments for pediatric pain assessment, concerning different developmental phases and clinical settings. The systematic pain assessment is relevant to support pharmacological and nonpharmacological management. Several non-pharmacological interventions reveal efficacy for pain relief, such as: sugar substances (sucrose and glucose) and skin-to-skin contact, for neonates, and cognitive and behavioral interventions (distraction and muscle relaxation), for children. Otherwise, institutional studies show gaps on the transfer of scientific knowledge about pain assessment and management to the practice. The future challenge consists on the development of institutional policies about pain to enhance the interdisciplinary health professional practice.
Spatial Augmented Reality Using Structured Light Illumination

OF DISSERTATION Spatial Augmented Reality Using Structured Light Illumination Spatial augmented reality is a particular kind of augmented reality technique that uses projector to blend the real objects with virtual contents. Coincidentally, as a means of 3D shape measurement, structured light illumination makes use of projector as part of its system as well. It uses the projector to generate important clues to establish the correspondence between the 2D image coordinate system and the 3D world coordinate system. So it is appealing to build a system that can carry out the functionalities of both spatial augmented reality and structured light illumination. In this dissertation, we present all the hardware platforms we developed and their related applications in spatial augmented reality and structured light illumination. Firstly, it is a dual-projector structured light 3D scanning system that has two synchronized projectors operate simultaneously, consequently it outperforms the traditional structured light 3D scanning system which only include one projector in terms of the quality of 3D reconstructions. Secondly, we introduce a modified dualprojector structured light 3D scanning system aiming at detecting and solving the multi-path interference. Thirdly, we propose an augmented reality face paint system which detects human face in a scene and paints the face with any favorite colors by projection. Additionally, the system incorporates a second camera to realize the 3D space position tracking by exploiting the principle of structured light illumination. At last, a structured light 3D scanning system with its own built-in machine vision camera is presented as the future work. So far the standalone camera has been completed from the a bare CMOS sensor. With this customized camera, we can achieve high dynamic range imaging and better synchronization between the camera and projector. But the full-blown system that includes HDMI transmitter, structured light pattern generator and synchronization logic has yet to be done due to the lack of a well designed high speed PCB.
Abordagem terapêutica na sialorréia em paralisia cerebral: revisão sistemática

Introducao: a sialorreia e o aumento involuntario do fluxo salivar que ultrapassa a margem da boca. Pode ocasionar problemas na saude e na qualidade de vida dos pacientes com doenca neurologica cronica. Diversas formas de manejo para a sialorreia sao descritas. Objetivo: Essa revisao visa pesquisar a terapeutica da sialorreia em Paralisia Cerebral. Metodologia: pesquisa realizada nos portais PubMed, Biblioteca Virtual de Saude e Ovid, limitando o assunto, o tempo e o idioma. Selecionados apenas estudos intervencionistas em pacientes com 18 anos ou menos e com diagnostico de Paralisia Cerebral. Resultado: sete artigos foram descritos, resumidamente, quanto ao tipo de intervencao, resultados, nivel de evidencia, efeitos adversos e metodo de avaliacao. Conclusao: Verificou-se pouca reprodutibilidade na pratica medica, baixo nivel de evidencia e a necessidade de novos estudos Introduction: Drooling is the involuntarysalivary flow that exceeds themargin of the mouth. It can cause problems in health and quality of life of patients with chronic neurological disease.Many management options for droolingare described. Objective: This reviewaims to investigate the treatment of drooling in cerebral palsy. Methods: Theresearch was conducted at PubMed, Virtual Health Library and Ovid, limitingthe subject, time and language. Onlyinterventional studies in patients with18 years or less diagnosed with Cerebral Palsy were selected. Results: Seven selected articles were briefly described in tables based on type of intervention, results, level of evidence, adverse effects and method of evaluation. Conclusion:Studies have shown that there was poorreproducibility in medical practice, lowlevel of evidence and need for furtherstudies.
SISTEM PROTEKSI KEBOCORAN KRAN DAN PENCATATAN METERAN AIR DIGITAL PADA PDAM BERBASIS MIKROKONTROLLER ARDUINO UNO R3

Tujuan penelitian ini adalah menghasilkan sistem yang dapat digunakan untuk mengatasi masalah pemborosan biaya rekening air, akibat terjadi kebocoran. Selain itu alat ini dilengkapi dengan meteran air digital yang menampilkan jumlah debit air yang digunakan dan tampilan harga yang harus dibayarkan, sehingga pelanggan mengetahui berapa banyak air yang telah digunakan. Komponen yang digunakan untuk perancangan sistem adalah modul mikrokontroler Arduino Uno R3, Sensor Flowmeter, Sensor Tekanan, Solenoid Valve, Led dan LCD. Perancangan software menggunakan Arduino IDE. Hasil penelitian ini mendapatkan bahwa alat yang dibuat mampu mendeteksi kebocoran pada kran dengan skala kecil dan menampilkan debit air yang digunakan, serta harga dalam rupiah pada layar LCD, dimana Solenoid Valve akan menutup sempurna setelah menerima sinyal dari arduino 6 detik kemudian, dengan ratarata kesalahan kalibrasi sensor flowmeter adalah sebesar 6.67%. Kata kunci: Arduino UNO R3, Proteksi Kebocoran, Meter Air Digital The purpose of this research is to produce a system that can be used to overcome the problem of waste costs of water bills due to the leakage. In addition, this tool is equipped with a digital water meter that displays the amount of water used and the price to be paid, so customers can know how much water has been used. The components used for this system are Arduino Uno R3 microcontroller module, Flowmeter Sensor, Pressure Sensor, Solenoid Valve, Led and LCD. The design of software using Arduino IDE. The results of this study shows that the tool was able to detect even a small-scale leakage on the faucet and display the water used, and the price in rupiah on the LCD screen, where the Solenoid Valve will close perfectly after receiving the signal from the arduino 6 seconds later, with flowmeter sensor calibration average error of 6.67%. Keywords: Arduino UNO R3, Leakage Protection, Digital Water Meter
Methods of extraction of optical properties from diffuse reflectance measurements of ex-vivo human colon tissue using thin film silicon photodetector arrays.

Spatially resolved diffuse reflectance spectroscopy (SRDRS) is a promising technique for characterization of colon tissue. Herein, two methods for extracting the reduced scattering and absorption coefficients ( μ s ' ( λ ) and μ a ( λ ) ) from SRDRS data using lookup tables of simulated diffuse reflectance are reported. Experimental measurements of liquid tissue phantoms performed with a custom multi-pixel silicon SRDRS sensor spanning the 450 - 750 nm wavelength range were used to evaluate the extraction methods, demonstrating that the combined use of spatial and spectral data reduces extraction error compared to use of spectral data alone. Additionally, SRDRS measurements of normal and tumor ex-vivo human colon tissue are presented along with μ s ' ( λ ) and μ a ( λ ) extracted from these measurements.
Visual Analysis of Probabilistic Infection Contagion in Hospitals

Clinicians and hygienists need to know how an infection of one patient could be transmitted among other patients in the hospital (e.g., to prevent outbreaks). They need to analyze how many and which patients will possibly be infected, how fast the infection could spread, and which contacts are likely to transfer the infections within the hospital. Currently, infection contagion is modeled and visualized for populations only on an aggregate level, without identiﬁcation and exploration of possible infection between individuals. We present a novel visual analytics approach that simulates the contagion in a contact graph of patients in a hospital. We propose a clustering approach to identify probable contagion scenarios in the simulation ensemble. Furthermore, our novel visual design for detailed assessment of transmission shows the temporal development of contagion per patient in one view. We demonstrate the capability of our approach to a real-world use case in a German hospital.
Solution of Electrical Load Dispatch Problem by Modified Exchange Algorithm

In this paper a Modified Exchange Algorithm has been presented and this technique is applied to one of the main optimization problems in the Electrical Power System i.e., Electrical Load Dispatch. The proposed technique is a robust one and helps to extract the global optimum efficiently. As the name suggests, the technique is based on the working of a stock in which different shareholders achieve the maximum profit by following the elite shareholders’ patterns. The search strategy is then enhanced using the Mutation and Sequential Quadratic Programming to further refine the final fitness values. The proposed technique is then implemented on 6 Unit test system with convex function in order to present the effectiveness of this technique. Finally, the results obtained from the proposed algorithm are compared with some of the already present technique on this problem. The results clearly show that the proposed technique can be a useful tool to solve Electrical Load Dispatch problem.