Miracle-dz/UniFAR-FTUs huggingface dataset:
A counseling system to predict the study path for freshmen

Now a days, dilemma related to one’s career has been considered as a serious issue, specially among fresh graduates. Starting at the age of 18, the students usually fail to grasp the idea of which career path to pursue as they lack maturity and experience on the matter. Moreover, students suffer greatly in deciding which faculty would result the highest benefit for them due to the insufficiency of counselors in the pre-university education. The students do not have the sufficient knowledge to make themselves aware of the real life career related challenges, which is supported by academic majors. It is crucial for a student to make the proper decision on the matter of their career in order to avoid consequences that may be the result of wrong career selection. As a result, selecting an proper career with highest benefit has become one of the most difficult as well as challenging task for the students because wrong career selection may lead to a work field which was not meant for them. This paper presents a counselling system to predict study path for the freshmen by analyzing necessary attributes such as skills, interests, values and motivation, academic background. Moreover, the proposed freshmen counseling system helps the freshmen in their career choice as well as guides toward their respective appropriate career for future. We have used several different approaches for modeling and prediction such as Decision tree classifier, Random Forest, SVM, K-Nearest-Neighbors Classifiers etc. and differentiated between the resulting precision scores. The results were also cross-checked which determined the best parameters that is responsible for providing highest accuracy scores. Furthermore, some ranking algorithms were used to generate a ranked output for the student counseling system. In this paper, we have separated our work into different parts. Chapter 1 contains the overall idea about our work. Chapter 2 contains Related Works, followed by Chapter 3, where we have mentioned about the methodologies which we have used for the system. After that Chapter 4 contains the implementation of the system. Next in Chapter 5 result analysis has been mentioned. Lastly, Chapter 6 ended with conclusion, our limitations and future scopes of improvements related to our work.
Virtual Sensor Middleware: A Middleware for Managing IoT Data for the Fog-Cloud Platform

Internet of Things is a massively growing field where billions of devices are connected to the Internet using different protocols and produce an enormous amount of data. The produced data is consumed and processed by different applications to make operations more efficient. Application development is challenging, especially when applications access sensor data since IoT devices use different communication protocols. The existing IoT architectures address some of these challenges. This thesis proposes an IoT Middleware that provides applications with the abstraction required of IoT devices while distributing the processing of sensor data to provide a real-time or near real-time response and enable the applications to choose from where to consume sensor data. The suggested middleware architecture minimizes the development efforts required by the applications by automating the processing of sensor data on multiple nodes (fog nodes) deployed near IoT devices and making it configurable. Furthermore, the dissemination of sensor data using the publish-subscribe paradigm makes it easier for applications to decide from where to consume sensor data while maintaining decoupling from IoT devices.
A Virtual Testbed for Fish-Tank Virtual Reality: Improving Calibration with a Virtual-in-Virtual Display

With the development of novel calibration techniques for multimedia projectors and curved projection surfaces, volumetric 3D displays are becoming easier and more affordable to build. The basic requirements include a display shape that defines the volume (e.g. a sphere, cylinder, or cuboid) and a tracking system to provide each user’s location for the perspective corrected rendering. When coupled with modern graphics cards, these displays are capable of high resolution, low latency, high frame rate, and even stereoscopic rendering; however, like many previous studies have shown, every component must be precisely calibrated for a compelling 3D effect. While human perceptual requirements have been extensively studied for headtracked displays, most studies featured seated users in front of a flat display. It remains unclear if results from these flat display studies are applicable to newer, walk-around displays with enclosed or curved shapes. To investigate these issues, we developed a virtual testbed for volumetric head-tracked displays that can measure calibration accuracy of the entire system in real-time. We used this testbed to investigate visual distortions of prototype curved displays, improve existing calibration techniques, study the importance of stereo to performance and perception, and validate perceptual calibration with novice users. Our experiments show that stereo is important for task performance, but requires more accurate calibration, and that novice users can make effective use of perceptual calibration tools. We also propose a novel, real-time calibration method that can be used to fine-tune an existing calibration using perceptual feedback. The findings from this work can be used to build better head-tracked volumetric displays with an unprecedented amount of 3D realism and intuitive calibration tools for novice users.
CEBPB is associated with active tumor immune environment and favorable prognosis of metastatic skin cutaneous melanoma

Metastatic skin cutaneous melanoma (SKCM) is a common malignancy that accounts for low morbidity but high mortality of skin cancer. SKCM is characterized by high lymphocytic infiltration, whereas the states of infiltrated cells are variable in patients leading to a heterogeneous prognosis and hindering appropriate clinical decisions. It is therefore urgent to identify markers associated with lymphocytic infiltration, cellular conditions, and the prognosis of SKCM. In this study, we report that CEBPB, a transcriptional factor, is mainly expressed in macrophages in metastatic SKCM and associated with an active tumor immune environment and a favorable prognosis through integrated analysis of single-cell and bulk RNA-seq datasets. High CEBPB expression is significantly associated with active inflammation and immune response pathways in both macrophages and bulk SKCM tumor tissues. A signature based on CEBPB-associated genes that are specifically expressed in macrophages could robustly and prognostically separate different metastatic SKCM patients. In addition, the associations between the metastatic SKCM tumor signature and microenvironment with respect to T-cell recruitment and state, inflammation response, angiogenesis, and so on were also determined. In conclusion, we present here the first report on CEBPB in tumor immune environment and prognosis regulation in metastatic SKCM and construct a reliable signature, which should provide a useful biomarker for stratification of the patient’s prognosis and therapeutic selection.
A Sound Interpolation Method Using Deep Neural Network for Virtual Reality Sound

In this paper, we propose a deep neural network-based sound interpolation method for realizing virtual reality sound. Through this method, sound between two points is generated by using acoustic signals obtained from two points. Sound interpolation can be performed by statistical methods such as arithmetic mean or geometric mean, but this is insufficient to reflect actual nonlinear acoustic characteristics. In order to solve this problem, in this study, the sound interpolation is performed by training the deep neural network based on the acoustic signals of the two points and the target point
Evaluating the efficiency and sensitivity of one-step cyanoacrylate fuming methods in the detection and visualisation of latent fingerprints on the adhesive side of tape

The evidential value of adhesive tape recovered from a crime scene plays a critical role in the criminal investigation as it could potentially contain things such as fibres, hair, DNA evidence, or fingerprints. Adhesive tape is a ubiquitous material that can be used in crimes that involve kidnapping and murder, as well as used to house cables in acts of terrorism. With regards to the adhesive side of tape, the sticky nature of this surface not only increases the likelihood of latent fingerprint deposits but has routinely proved to be a problematic substrate to work with. As latent fingerprints are generally invisible to the eye, enhancement methods are required to conduct adequate analysis on the fingerprint details. Despite several methods of fingerprint enhancement available, common issues including high background staining and low selectivity of fingerprint deposits create a difficult problem for forensic investigators to solve. Studies have shown that these issues can be overcome by utilising aqueous solutions of fingerprint powders, as well as traditional dye methods like gentian violet. Fluorescent dyes have also been explored and shown to be very effective when used on darker-coloured adhesive tapes. With regards to aged latent fingerprints, sticky-side powder and phase transfer catalysts have proven to be viable methods of detection and development. Traditional cyanoacrylate fuming was observed to be the best method of development in all reviewed cases, but the requirement of subsequent dye staining poses potential health issues to the user and the environment. One-step cyanoacrylate fuming has been proposed as a method incorporating the staining step into the cyanoacrylate fuming step, thus completing both steps simultaneously. As one-step cyanoacrylate fuming is a relatively new method of development, its potential application to the development of latent fingerprints on the adhesive side of tape has not been explored to its full extent and should be researched more extensively.
Tradeoff Analysis of Offshore Structures Under Stochastic Excitation

The analysis and design of structural systems such as offshore structures usually involve several design goals which are required to be maximized or minimized simultaneously. The design goals are in general potentially conﬂicting requirements reﬂecting technical and economical performances. The purpose of this work is to obtain in an efﬁcient manner compromise designs that best represent the outcome that the designer considers potentially satisfactory. The designs are obtained by formulating a compromise programming problem, which is solved by an efﬁcient ﬁrst-order interior point algorithm. In order to exemplify the proposed methodology a typical offshore structural model is considered for analysis. The random sea is modeled as a Gaussian process following a Joint North Sea Wave Observation Project (JONSWAP) type spectrum for free surface elevation. Numerical results show that the proposed approach for decision making is quite effective.
Performance Analysis of Real-Time Eye Blink Detector for Varying Lighting Conditions and User Distance from the Camera

– This paper presents the performance analysis of a blink detector, which detects eye blink, right wink and left wink, under natural & controlled lighting conditions and for variable user distance from the camera. The blink detector has been implemented by using a webcam, a computer and MATLAB software with image processing and computer vision toolbox. It divides the whole process of blink detection into three parts: face and eyes pair localization, blink detection using pixels’ motion analysis and classification of blinks as left wink, right wink and eye blink i.e. blinking both eyes simultaneously. The detection accuracy of the detector was measured under natural and controlled lighting conditions for different values of user distance from the camera. Average detection accuracy of the detector under controlled lighting conditions observed to be 96%, 92% and 88% for detection of eye blink, left wink and right wink, respectively. From the overall analysis it has been observed that the system gives significantly better performance under controlled lighting conditions than under natural lighting conditions, and when the user sits at a distance of about 0.5 meter from the camera.
An iterative reconstruction of source functions in a potential problem using the method of fundamental solutions

In this work, we address the reconstruction of characteristic source functions in a potential problem, from the knowledge of full and partial boundary data. This inverse problem is formulated as a transmission problem and is solved using a decomposition method, based on the Cauchy data reconstruction and an optimization method. A Newton-type of method based on the domain derivative will also be tested. Some density results will be presented in order to justify the application of the Method of fundamental solutions (MFS) for the arising transmission problems. Numerical results will be presented in order to test the performance of both methods.
OFDM Communication System

It gives me immense pleasure in bringing out this book which has the patronage of the student community all over the world . This book endeavours to provide a basic concept about OFDM communication . The main objective of this book is to study and compensate the Phase Noise problem in OFDM based communication system and enhanced the performance of the system in terms of bit error rate (BER) by using R-S coding with LSA channel estimation technique. Some other objectives of this book are (1) To analysis the BER Performance of Uncoded OFDM System without considering Phase Noise. (2) To analysis the BER Performance of Uncoded OFDM System at different values of Phase Noise. (3) To analysis the Comparison between Uncoded OFDM and R-S Coded OFDM System at different values of Phase Noise. (4) To analysis the Comparison between R-S Coded OFDM and R-S coded with LSA Channel Estimated OFDM System at different values of Phase Noise.
Foundation for a classification of collaboration levels for human-robot cooperation in manufacturing

ABSTRACT Industry 4.0 aims to support the factory of the future, involving increased use of information systems and new ways of using automation, such as collaboration where a robot and a human share work on a single task. We propose a classification of collaboration levels for Human-Robot collaboration (HRC) in manufacturing that we call levels of collaboration (LoC), formed to provide a conceptual model conducive to the design of assembly lines incorporating HRC. This paper aims to provide a more theoretical foundation for such a tool based on relevant theories from cognitive science and other perspectives of human-technology interaction, strengthening the validity and scientific rigour of the envisioned LoC tool. The main contributions consist of a theoretical grounding to motivate the transition from automation to collaboration, which are intended to facilitate expanding the LoC classification to support HRC, as well as an initial visualization of the LoC approach. Future work includes fully defining the LoC classification as well as operationalizing functionally different cooperation types. We conclude that collaboration is a means to an end, so collaboration is not entered for its own sake, and that collaboration differs fundamentally from more commonly used views where automation is the focus.
A Multilevel Fusion System for Multirobot 3-D Mapping Using Heterogeneous Sensors

Operating multiple robots in an unstructured environment is challenging due to its high complexity and uncertainty. In such applications, the integration of individual maps generated by heterogeneous sensors is a critical problem, especially the fusion of sparse and dense maps. This paper proposes a general multi-level probabilistic framework to address the integrated map fusion problem, which is independent of sensor type and SLAM algorithm employed. The key novelty of this paper is the mathematical formulation of the overall map fusion problem and the derivation of its probabilistic decomposition. The framework provides a theoretical basis for computing the relative transformations amongst robots and merging probabilistic map information. Since the maps generated by heterogeneous sensors have different physical properties, an expectation-maximization-based map-matching algorithm is proposed which automatically determines the number of voxels to be associated. Then, a time-sequential map merging strategy is developed to generate a globally consistent map. The proposed approach is evaluated in various environments with heterogeneous sensors, which demonstrates its accuracy and versatility in 3-D multirobot map fusion missions.
El niño ciego: Construcción de la grilla argentina de estrategias cognoscitivas

In the present study, the cognitive strategies that the blind baby follows during the sensory - motor period were established. From these observed strategies there was made a cricket of observation that allows to determine the degree of cognitive development of the blind child and to define possible guidelines of action. It started from the notion of "action plan" present in this stage and its integration in structures that will allow to achieve a new level of development and the concept of "affordance", which implies recognizing what the environment offers us, what responds to our interest. An observational qualitative work was carried out. The observation protocol was prepared leaving the observed strategies established, and the "modes of action" used by the child indicated the different strategies. In the developed game certain elements such as ribbons, rings, balls with rattle, support with rotating wooden disk, cars, piano, animals with sound and textures was offered to the child. The strategies systematized through the four stages defined are:a. - in the thematic axis Exploration of the object, from the recognition with the mouth to the mental representation,b. - in the Search of the object, from not looking for it until the integration of space and sound to locate the object,c. - in Orientation and Spatial Location, from the spatial functions precursors of the midline to the mental representation of space,d. - on the Intermediaries axis, from not using them, to using them as a resource to perform a task, ande. - in body Organizer, from discovering the hand, foot and mouth as explorers to recreating experiences.Body organizer was considered to be functioning structures that are guidelines for integration and access to a more complex structure. They are sequential moments in which a growing complexity is observed that goes from the undifferentiated to the organized and structured. Reference is made to an active exploratory sense. This active touch, precursor of the haptic sense in which receptors participate in the skin and in joints and tendons. This exploration allows him to perceive the world and in the case of the blind child, it makes it possible to experience new practices that can compensate for the lack of vision.
STLP-GSM: a method to predict future locations of individuals based on geotagged social media data

ABSTRACT An increasing number of social media users are becoming used to disseminate activities through geotagged posts. The massive available geotagged posts enable collections of users’ footprints over time and offer effective opportunities for mobility prediction. Using geotagged posts for spatio-temporal prediction of future location, however, is challenging. Previous studies either focus on next-place prediction or rely on dense data sources such as GPS data. Introduced in this article is a novel method for future location prediction of individuals based on geotagged social media data. This method employs the hierarchical density-based clustering algorithm with adaptive parameter selection to identify the regions frequently visited by a social media user. A multi-feature weighted Bayesian model is then developed to forecast users’ spatio-temporal locations by combining multiple factors affecting human mobility patterns. Further, an updating strategy is designed to efficiently adjust, over time, the proposed model to the dynamics in users’ mobility patterns. Based on two real-life datasets, the proposed approach outperforms a state-of-the-art method in prediction accuracy by up to 5.34% and 3.30%. Tests show prediction reliability is high with quality predictions, but low in the identification of erroneous locations.
Calcul numérique certifié dans les espaces fonctionnels : Un trilogue entre approximations polynomiales rigoureuses, calcul symbolique et preuve formelle. (Certified numerics in function spaces : polynomial approximations meet computer algebra and formal proof)

Le calcul rigoureux vise a produire des representations certifiees pour les solutions de nombreux problemes, notamment en analyse fonctionnelle, comme des equations differentielles ou des problemes de controle optimal. En effet, certains domaines particuliers comme l’ingenierie des systemes critiques ou les preuves mathematiques assistees par ordinateur ont des exigences de fiabilite superieures a ce qui peut resulter de l’utilisation d’algorithmes relevant de l’analyse numerique classique.Notre objectif consiste a developper des algorithmes a la fois efficaces et valides / certifies, dans le sens ou toutes les erreurs numeriques (d’arrondi ou de methode) sont prises en compte. En particulier, nous recourons aux approximations polynomiales rigoureuses combinees avec des methodes de validation a posteriori a base de points fixes. Ces techniques sont implementees au sein d’une bibliotheque ecrite en C, ainsi que dans un developpement de preuve formelle en Coq, offrant ainsi le plus haut niveau de confiance, c’est-a-dire une implementation certifiee.Apres avoir presente les operations elementaires sur les approximations polynomiales rigoureuses, nous detaillons un nouvel algorithme de validation pour des approximations sous forme de series de Tchebychev tronquees de fonctions D-finies, qui sont les solutions d’equations differentielles ordinaires lineaires a coefficients polynomiaux. Nous fournissons une analyse fine de sa complexite, ainsi qu’une extension aux equations differentielles ordinaires lineaires generales et aux systemes couples de telles equations. Ces methodes dites symboliques-numeriques sont ensuite utilisees dans plusieurs problemes relies : une nouvelle borne sur le nombre de Hilbert pour les systemes quartiques, la validation de trajectoires de satellites lors du probleme du rendez-vous linearise, le calcul de polynomes d’approximation optimises pour l’erreur d’evaluation, et enfin la reconstruction du support et de la densite pour certaines mesures, grâce a des techniques algebriques.
Kinetics control in runners in natural-running conditions after completion of a laboratory-based gait retraining program

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