Miracle-dz/UniFAR-FTUs huggingface dataset:
Pigmented skin lesion segmentation based on random forest and full convolutional neural networks

Segmentation of pigmented lesions is often affected by factors such as hair around the skin lesions, artificial markings, etc., and the complexity of the lesion itself, such as lesions and skin boundaries is not clear, the internal color of lesions is variable, etc., resulting in segmentation difficulties. Aiming at the problem that the segmentation method of pigmented skin lesions using only random forests is not accurate, a segmentation method for pigmented skin lesion using a combination of random forest and fully convolutional neural networks (FCN) is proposed. This method firstly classifies and recognizes skin lesion images based on random forests to obtain a probability distribution of the lesions and the background. Then, the other probability distribution is obtained using FCN based on an improved loss function. Finally, the classification results of random forest and FCN are fused into the final image segmentation results. The experimental results show that the combination of random forest and FCN yields better performances than using random forest alone, in particular, can increase the sensitivity by about 20%.
Extension of the Integrated Database "HyperGenome" for Genome Maps and Sequence Information

called \HyperGenome"[1, 2] which integrates data on genome mapping and DNA sequences. The HyperGenome system provides a user friendly integrated interface for a database of genome maps and DNA sequences. We assume that the average users of the HyperGenome will not enter their own data into the database, rather they retrieve information which is currently stored separately in genome mapping databases and/or in DNA sequence databases.
Contributo alla validazione italiana delle versioni breve e molto breve del physical self inventory (psi) per adolescenti

Il presente studio rappresenta un contributo alla validazione italiana delle versioni breve e molto breve del Physical Self Inventory (PSI) per adolescenti. Le due versioni del Physical Self Inventory sono state valutate positivamente nella letteratura internazionale anche se sono state utilizzate per lo piu in campioni di lingua francese. Un ampio campione di adolescenti italiani ha preso parte allo studio (N = 1121; 52% femmine). I risultati dell’analisi fattoriale confermativa sono per lo piu in linea con quelli trovati in adolescenti francesi. I test di invarianza confermano l’equivalenza della struttura fattoriale per genere cosi come per pratica sportiva; tuttavia le medie latenti sono risultate significativamente piu elevate nei maschi e negli sportivi. L’attendibilita delle scale e generalmente buona con l’eccezione della scala per l’aspetto fisico. In breve, il Physical Self Inventory nelle sue due versioni (breve e molto breve) rappresenta una buona alternativa agli strumenti esistenti per lo studio del se fisico in adolescenza; infatti, esso e caratterizzato da facilita e brevita di somministrazione cosi come proprieta psicometriche adeguate, sebbene migliorabili.
Observing the Pulse of a City: A Smart City Framework for Real-Time Discovery, Federation, and Aggregation of Data Streams

An increasing number of cities are confronted with challenges resulting from the rapid urbanization and new demands that a rapidly growing digital economy imposes on current applications and information systems. Smart city applications enable city authorities to monitor, manage, and provide plans for public resources and infrastructures in city environments, while offering citizens and businesses to develop and use intelligent services in cities. However, providing such smart city applications gives rise to several issues, such as semantic heterogeneity and trustworthiness of data sources, and extracting up-to-date information in real time from large-scale dynamic data streams. In order to address these issues, we propose a novel framework with an efficient semantic data processing pipeline, allowing for real-time observation of the pulse of a city. The proposed framework enables efficient semantic integration of data streams, and complex event processing on top of real-time data aggregation and quality analysis in a semantic Web environment. To evaluate our system, we use real-time sensor observations that have been published via an open platform called Open Data Aarhus by the City of Aarhus. We examine the framework utilizing symbolic aggregate approximation to reduce the size of data streams, and perform quality analysis taking into account both single and multiple data streams. We also investigate the optimization of the semantic data discovery and integration based on the proposed stream quality analysis and data aggregation techniques.
Structure guided GANs

Generative adversarial networks (GANs) has achieved success in many fields. However, there are some samples generated by many GAN-based works, whose structure is ambiguous. In this work, we propose Structure Guided GANs that introduce structural similar into GANs to overcome the problem. In order to achieve our goal, we introduce an encoder and a decoder into a generator to design a new generator and take real samples as part of the input of a generator. And we modify the loss function of the generator accordingly. By comparison with WGAN, experimental results show that our proposed method overcomes largely sample structure ambiguous and can generate higher quality samples.
FINDING INFORMATION ON THE WORLD WIDE WEB

This is an educational case study trying to show a little bit of how and what children (10 - 12 years old) think about searching for information on the Internet. In the guidelines for primary (and secondary) school it is said among other things that the students should learn how to evaluate facts from different sources. Since Internet came into our schools this has been the subject for many discussions. To what extent are these young children able to search for information on the Internet? Some teachers do not let the children even try and others think that Internet is a fantastic tool to use in training the pupils to evaluate facts. There have been observations, interviews, less formal talks and analysis of the children's written works in three different schools/classes. The schools/classes were chosen because it was known that the teachers let the students use the Internet for relatively free information search. All the students used AltaVista, MegaCrawler and similar search engines. The findings are that the children appreciate that Internet is a fast way to find current information and they all want to find "good" information. What "good" is differ from student to student. It can be anything from short texts (in Swedish) to "non-commercials", but they all had the ambition to do a good job and not just take the first hit available. They were also aware of that there could be "lies" on the Internet. If the children are supposed to succeed with this type of work they have to have the opportunity to practice. We live in a changing society. It is slowly transforming into something other than the industrial society it has been for a long time. Some people call it an information society, as information is becoming an increasingly important part of our existence. We are unceasingly flooded by immense amounts of information. The Internet has become the symbol of information overflow. Even our children are using the Internet, including the World Wide Web, and it is of vital importance to start thinking about how we deal with this phenomenon in the classroom. The Swedish curriculum prescribes that the students should be able to orient themselves in a complex reality with great information flow and rapid changes. It is also necessary that the students develop their ability to evaluate facts and conditions critically and to realize the consequences of different alternatives (Utbildningsdepartementet 1994, p. 15) 1 .
Using Community Advisory Panels (Caps) For The Development Of A Stem Professional Development Model For Teachers Of American Indian Students

The Communities of Effective Practice: A Professional STEM Development Model for Teachers of American Indian Students project is NSF funded with a vision to improve American Indian student achievement in science and mathematics. This project implements a professional development STEM model for teachers in American Indian schools by linking Utah State University (USU) engineers and teacher educators with teachers in grades 4-6. The model is designed to include standard-based and researchbased mathematics and science curricula using engineering and technology concepts and strong links with tribal elders, parents, and community leaders. The core partners for this effort include the Navajo Nation in the Mexican Hat Elementary School in Mexican Hat, Utah and the Northern Ute Nation in the Todd Elementary School, in Fort Duchesne, Utah. The three-year proof of concept grant: 1) designed a series of culturally relevant professional development modules for teachers of grades 4 through 6 that include an American Indian perspective and that satisfy national and state of Utah core curriculum requirements in math and science; and 2) developed a template that describes the organization and methods for creating a Community Advisory Panel (CAP) of teachers, American Indian students, community leaders, parents, and tribal elders who work to incorporate important cultural knowledge reflecting their specific community into math and science curricula. The findings presented are based on surveys, phone interviews and observations conducted with teachers and CAP members representing each elementary school. The findings indicate that it is critical to have fully functioning CAPs, as their input and support is tantamount to the success of the professional development, and in turn, has effects class-wide and school-wide.
An Adaptive Smart Grid Management Scheme Based on the Coopetition Game Model

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non‐cooperative hedonic game model. By exploiting multi‐appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.
Emerging clinical applications of strain imaging and three-dimensional echocardiography for the assessment of ventricular function in adult congenital heart disease.

Management of congenital heart disease (CHD) in adults (ACHD) remains an ongoing challenge due to the presence of residual hemodynamic lesions and development of ventricular dysfunction in a large number of patients. Echocardiographic imaging plays a central role in clinical decision-making and selection of patients who will benefit most from catheter interventions or cardiac surgery. Recent advances in both strain imaging and three-dimensional (3D)-echocardiography have significantly contributed to a greater understanding of the complex pathophysiological mechanisms involved in CHD. The aim of this paper is to provide an overview of emerging clinical applications of speckle-tracking imaging and 3D-echocardiography in ACHD with focus on functional assessment, ventriculo-ventricular interdependency, mechanisms of electromechanical delay, and twist abnormalities in adults with tetralogy of Fallot (TOF), a systemic RV after atrial switch repair or in double discordance ventricles, and in those with a Fontan circulation.
Interference mitigation in 5G mobile networks : Uplink pilot contamination in TDD massive MIMO scheme

Par la revolution du Cloud Computing et des Smartphones, une quantite enorme de donnees devrait traverser le reseau chaque seconde ou la plupart de ces donnees sont fournies par des mobiles utilisant des services Internet. La croissance rapide de la bande passante et des demandes de QoS rend les reseaux mobiles du 4eme G insuffisants. Le systeme de prochaine generation doit avoir un taux de sommation de 100Mbps a 1Gbps par terminal utilisateur (UT), avec une densite de connexion superieure a 1M connexion / Km2, la mobilite des vehicules a grande vitesse jusqu'a 500 km / h et une fin a la fin (E2E) retardent moins de 10 ms. Un candidat prometteur qui peut repondre a ces demandes est le systeme sans fil a multiples sorties multiples (MIMO) Multi-Cell Multi-Cell. Cependant, la capacite Massive MIMO est delimitee par l'Inter-cell Interference (ICI) en raison de la reutilisation du pilote et, par consequent, de la contamination du pilote. Dans cette these, nous etudions la contamination du pilote de liaison montante dans le systeme de formation a la division temporelle (TDD) des reseaux sans fil MIMO massifs. En supposant un canal de decoloration, l'intervalle de coherence sera temporairement limite, ou l'estimation du canal, la reception des symboles et le precodage des symboles doivent etre effectues dans le meme intervalle. Cela dit, la longueur du pilote de formation est limitee. De meme, le nombre de terminaux de l'utilisateur (UT) par zone d'interference est egalement limite. Inspire par la variation de la taille de l'intervalle de coherence parmi les UT, cette recherche presente deux nouvelles contributions independantes pour faire face a la contamination pilote de liaison montante dans le MIMO massif. La premiere contribution repertorie la region de couverture de la cellule de base (BS) dans une carte d'information d'etat de chaine (CSI). Cette carte est creee et mise a jour a l'aide d'un algorithme special d'apprentissage machine, et elle est exploitee pour predire UT CSI au lieu d'estimer ses canaux. Compte tenu de cela, la formation des pilotes aeriens et de liaison montante est considerablement reduite. La deuxieme contribution classe les UT en fonction de la taille de leur intervalle de coherence de canal. En outre, nous appliquons une technique de changement de pilote pour deplacer des pilotes similaires vers differentes positions temporelles (qui sont considerees comme vides en raison de trames TDD pilotes vides). Les resultats de la simulation montrent une augmentation a l'echelle de la performance du MIMO massif, en particulier dans la performance de l'efficacite energetique et spectrale, UT par cellule et taux d'addition. En particulier, la troisieme contribution evolue le MIMO massif multi-cellulaire a une performance de cellule unique et meme surmonte un simple enorme conventionnel dans l'efficacite energetique et UT par cellule.
Geant4 and beyond: recent progress in precision physics modeling

This extended abstract briefly summarizes ongoing research activity on the evaluation and experimental validation of physics methods for photon and electron transport. The analysis includes physics models currently implemented in Geant4 as well as modeling methods used in other Monte Carlo codes, or not yet considered in general purpose Monte Carlo simulation systems. The validation of simulation models is performed with the support of rigorous statistical methods, which involve goodness-of-fit tests followed by categorical analysis. All results are quantitative, and are fully documented.
Anaesthesia for nephrectomy

### Key points This paper will summarize the perioperative anaesthetic considerations for patients undergoing nephrectomy for both non-neoplastic and neoplastic disease of the kidney. It does not include the management of patients undergoing living donor nephrectomy. Nephrectomy for patients with renal cell carcinoma (RCC) was first described in 1969.1 Surgical treatment varies with the pathology. Simple nephrectomy is the preferred option for those with non-neoplastic disease (e.g. trauma, non-functioning kidney with chronic infection) with radical nephrectomy being preferred in those with neoplastic disease. Radical nephrectomy implies resection of the whole of Gerota's fascia, including the perinephric fat, lymphatics, and the ipsilateral adrenal gland. The vast majority (∼90%) of solid renal masses are RCC; the remainder comprising mainly of transitional cell carcinoma or Wilm's tumour (in children). RCC accounts for between 1% and 3% of all visceral malignancies. It is twice as common in men when compared with women and most commonly presents in the seventh decade of life. The main environmental risk factor is cigarette smoking, contributing to one-third of all cases. Other important risk factors include obesity, hypertension, asbestos exposure, and acquired polycystic kidney disease. If symptomatic, presentation is usually with haematuria, loin pain, and a palpable mass. Non-specific symptoms such as malaise, …
Physical Layer Impairments A ware OVPN Connection Selection Mechanism

In optic al virtual private network (OVPN), the quality of connection depends not only on network layer information, but also on physical layer impairments (PLIs) constraints, which are incurred by non-ideal optical transmission media and accumulates along with the optical connection. It is important to analysis PLIs in-order to satisfy OVPN client's necessary requirement of QoS for their connection setup. In-corporate to the above point, the design methodology says how to understand the process that provide PLI information to the control plane protocols and use this information efficiently to compute feasible connections. Based on the PLI constraints, it is proposed a centralized PLI based routing algorithm for the selection of OVPN connections.
A Novel Approach of Eye Detection Based on Haar-Like Feature and SVM

Recognizing the importance of eye detection technology in face detection and recognition, facial expression recognition, driver fatigue detection, and so on, the current paper presents a novel approach to eye detection in images based on AdaBoost and the Support Vector Machine (SVM). The proposed method can accurately detect eyes with different postures, facial expressions, skin colors, and glasses in a simple background image. First, a Haar-like feature AdaBoost classifier based on the developed training samples is used to detect eyes in images. An SVM post classifier trained by coordinates of the true and pseudo eye rectangles is then used to optimize the results. Experimental results show that the proposed method is fast, robust, and has high generalization capability.
n in Parallel Query Plans

In this paper we show an alternative way to optimize join sequences in (I shared nothing architecture of the distributed relational DBMS HE# 2. The hardware resources are also used for database independent applications in concurrency to the database access. To achieve a better hardware utilization we span a complete search space involving all intermediate shapes between left deep, right deep and bushy trees, but without join sequences including Cartesian products. The approach is based on any combinatorial search engine and a complex cost function. The cost function involves the actual load of the processors, the networkload, and the memory capacities. The new idea of this paper is the technique to have a free access to any join sequence in the whole search space. The approach is not restricted to ucyclic join conditions.
Passivity-based Visual Feedback Pose Synchronization in Three Dimensions

This dissertation investigates visual feedback attitude/pose synchronization on the Special Euclidean group SE(3) for a group of rigid bodies equipped with vision sensors. The objective of attitude synchronization is to lead orientations of all the bodies with the same linear body velocity to a common value. Therefore, all the bodies move in the same direction when attitude synchronization is achieved. On the other hand, the goal of pose synchronization is to drive orientations and virtual positions to common values. Here, a virtual position is the position with a desired position bias to guarantee collision avoidance and visibility to neighbor bodies when synchronization is achieved. We first introduce a notion of visual robotic networks to be controlled throughout this work. Visual robotic networks consist of multiple rigid bodies with kinematic models, visibility structures representing visual information flows between bodies and measured output, called visual measurements, extracted by monocular cameras which bodies equip. We next define visual feedback attitude/pose synchronization as the goals of this work. The definitions require each body to utilize only visual measurements for the implementation of control laws in addition to achieve synchronization, which is the main feature of this work. We then propose visual feedback attitude/pose synchronization laws consisting of vision-based observers to estimate relative poses of visible bodies and relative pose information-based synchronization laws. Here, passivity of the kinematic models plays a central role for the design of the present estimation and control mechanisms. We next give convergence and performance analysis for the visual robotic network with the present estimation and control schemes. In the analysis, we focus mainly on leaderfollowing visibility structures. It is first shown via Lyapunov methods that the present laws achieve visual feedback attitude/pose synchronization under leader-following type visibility structures. Then, for the leader moving independently, we analyze the tracking performance of the network by employing the theory of input-to-state stability or inputto-output stability. Here, we regard the individual velocity of the leader as an external disturbance to the network and evaluate the total estimation and control errors in the network. We also give some further developments on visual feedback attitude/pose synchronization in regard to (i) linear velocity observers for visual feedback attitude synchronization, (ii) ring-type visibility structures which does not require the existence of a leader, (iii) extension from velocity laws to force and torque ones by integrating Newton-Euler equations as rigid body dynamics, and (iv) collision avoidance and visibility maintenance. The effectiveness and validity of the present estimation and control strategies and the convergence and performance analysis are demonstrated through simulation in three dimensions and experiments on a planar testbed.