Miracle-dz/UniFAR-FTUs huggingface dataset:
Convex Optimization Algorithms and Statistical Bounds for Learning Structured Models

Convex Optimization Algorithms and Statistical Bounds for Learning Structured Models Amin Jalali Chair of the Supervisory Committee: Professor Maryam Fazel Electrical Engineering Design and analysis of tractable methods for estimation of structured models from massive high-dimensional datasets has been a topic of research in statistics, machine learning and engineering for many years. Regularization, the act of simultaneously optimizing a data fidelity term and a structure-promoting term, is a widely used approach in different machine learning and signal processing tasks. Appropriate regularizers, with efficient optimization techniques, can help in exploiting the prior structural information on the underlying model. This dissertation is focused on exploring new structures, devising efficient convex relaxations for exploiting them, and studying the statistical performance of such estimators. We address three problems under this framework on which we elaborate below. In many applications, we aim to reconstruct models that are known to have more than one structure at the same time. Having a rich literature on exploiting common structures like sparsity and low rank at hand, one could pose similar questions about simultaneously structured models with several low-dimensional structures. Using the respective known convex penalties for the involved structures, we show that multi-objective optimization with these penalties can do no better, order-wise, than exploiting only one of the present structures. This suggests that to fully exploit the multiple structures, we need an entirely new convex relaxation, not one that combines the convex relaxations for each structure. This work, while applicable for general structures, yields interesting results for the case of sparse and low-rank matrices which arise in applications such as sparse phase retrieval and quadratic compressed sensing. We then turn our attention to the design and efficient optimization of convex penalties for structured learning. We introduce a general class of semidefinite representable penalties, called variational Gram functions (VGF), and provide a list of optimization tools for solving regularized estimation problems involving VGFs. Exploiting the variational structure in VGFs, as well as the variational structure in many common loss functions, enables us to devise efficient optimization techniques as well as to provide guarantees on the solutions of many regularized loss minimization problems. Finally, we explore the statistical and computational trade-offs in the community detection problem. We study recovery regimes and algorithms for community detection in sparse graphs generated under a heterogeneous stochastic block model in its most general form. In this quest, we were able to expand the applicability of semidefinite programs (in exact community detection) to some new and important network configurations, which provides us with a better understanding of the ability of semidefinite programs in reaching statistical identifiability limits.
Acquisition Process of Verb-Particle Constructions in English

This paper aims to explore acquisition process of verb-particle constructions (henceforth, VPCs, for expository convenience) in English from the viewpoi nt of Construction Grammar (CxG) approach. CxG is one of the best known approaches to language (Lakoff (1977), Fillmore, Key and O'Connor (1988), Goldberg (1995, 2006)). CxG is typically associated with cognitive linguistics, based on the idea that the primary unit of grammar is the grammatical construction, which is defined as a paring of grammatical form and the corresponding meaning. From CxG viewpoint, constructions reflect scenes which human beings frequently experience. This study shows that there is a relationship between th e constructional properties of VPCs and the cognitive development of infants.
Twitter’s Sentiment Analysis on Gsm Services using Multinomial Naïve Bayes

Telecommunication users are rapidly growing each year. As people keep demanding a better service level of Short Message Service (SMS), telephone or data use, service providers compete to attract their customer, while customer feedbacks in some platforms, for example Twitter, are their souce of information. Multinomial Naive Bayes Tree, adapted from the method of Multinomial Naive Bayes and Decision Tree, is one technique in data mining used to classify the raw data or feedback from customers.Multinomial Naive Bayes method used specifically addressing frequency in the text of the sentence or document. Documents used in this study are comments of Twitter users on the GSM telecommunications provider in Indonesia.This research employed Multinomial Naive Bayes Tree classification technique to categorize customers sentiment opinion towards telecommunication providers in Indonesia. Sentiment analysis only included the class of positive, negative and neutral. This research generated a Decision Tree roots in the feature "aktif" in which the probability of the feature "aktif" was from positive class in Multinomial Naive Bayes method. The evaluation showed that the highest accuracy of classification using Multinomial Naive Bayes Tree (MNBTree) method was 16.26% using 145 features. Moreover, the Multinomial Naive Bayes (MNB) yielded the highest accuracy of 73,15% by using all dataset of 1665 features. The expected benefits in this research are that the Indonesian telecommunications provider can evaluate the performance and services to reach customer satisfaction of various needs.
The Role of Learner Characteristics in the Adaptive Educational Hypermedia Systems: The Case of the MATHEMA

The aim of this paper is to explore the characteristics of the learners used by the developed adaptive educational hypermedia systems to date to draw conclusions about their relation to the adaptation techniques they use and to be explained the rationale for selecting of the learners' characteristics used by the adaptive educational hypermedia system MATHEMA for its adaptation techniques. At first, the characteristics of learners using some systems for their adaptive techniques are presented. Here is the presentation of learner’s characteristics used by adaptation techniques of the adaptive educational hypermedia system MATHEMA. Finally, an evaluation of the main functions of the MATHEMA is performed. In conclusion, we discuss the choice of specific learners' characteristics for adaptation techniques of the MATHEMA and the resulting educational benefits.
Serum Amyloid A (SAA), C-reactive protein (CRP) and IL-6 as prognostic indicators in Renal Cell Carcinoma and Prostate Cancer.

9711 Background: IL-6, CRP and SAA are three biomarkers whose expressions have been shown to correlate with prognosis in select tumor models. We have evaluated these three biomarkers and their potential use as prognostic indicators in renal cell carcinoma (RCC) and prostate cancer in a retrospective study. METHODS Serum samples from patients with RCC or prostate cancer were obtained from IMPATH-BCP, Inc. (New York, NY). Healthy control subjects were also included. Serum levels of IL-6, CRP and SAA were measured using commercially available ELISA kits. Summary statistics were calculated and associations between variables were evaluated using linear regression analysis and Pearson correlation coefficient. RESULTS Serum levels of IL-6 (range <0.78 - 175 pg/mL), CRP (range 0.74 - 144.98 μg/mL) and SAA (<9.40 - 1530.84 ng/mL) were measured. All three biomarkers were found to be significantly higher in patients with RCC, while only SAA and CRP were found to be significantly higher in PC patients when compared to normal donors. Significant correlations between IL-6, CRP, and SAA were revealed by statistical analysis of the RCC serum data (IL-6/CRP r2=0.752; SAA/CRP r2=0.596; SAA/IL-6 r2=0.635). Correlation of these markers with patient survival (defined as the number of days between date of diagnosis and date of death) was found using Pearson correlation coefficients for RCC data analysis (IL-6 -0.4151, p=0.0063; CRP -0.4129, p=0.0059; SAA -0.3793, p=0.0158). In prostate cancer patients, no correlations between PSA and SAA, or CRP and IL-6 were found. Additionally, no significant correlation was observed between the investigated markers and survival (IL-6 0.0996, p=0.4650; CRP -0.0354, p=0.8219; SAA -0.0670, p=0.6207). CONCLUSIONS Based on these results, it appears that there may be mild to moderate association between survival time and the inflammatory markers in RCC but not in PC. However, other clinical variables may affect these conclusions in these heterogeneous populations. [Table: see text].
The Effect of SC vehicles on the Characteristics of Single-lane Traffic Flow

On the basis of the Nagel-Schrekenberg(NS)model, we first study the effect of SC (Self-driving with cooperating)system on the characteristics of single-lane flux under periodic boundary conditions. There are two models of vehicles on the lane(NS and SC). The influence of the proportion of SC vehicles and the Specified headway on the flux is studied by using computer simulation. Introduction In this model ,we select the single-lane Highway SR-520 as the object of study which is composed by the one-dimensional discrete lattice chain whose length is 7527 cell,that is, each grid point is equivalent to 3yards.The total length of the road is 12.83miles. At each moment, the lattice point may be occupied by the vehicle, the vehicle occupies two lattice points, then the corresponding actual length is about 6yards,and the maximum velocity is s cells v / 9 = max (road velocity limit 60mph),the corresponding actual velocity is 55mph.Each type of vehicle state is represented by its own velocity v max ≤ ≤ 0 v v . With ) (t xi represents the i vehicle at the t time of the rear position, i i i i l t x t x t d − − = + ) ( ) ( ) ( 1 represents the distance between the vehicle ) ( 1 + i and the immediately preceding neighboring vehicle ) ( 1 + i , i i v d T / = indicates the vehicle time In each evolutionary step 1 + → t t , some vehicles perform the velocity and position according to the evolution rule of the NS model and others according to the evolution rule of the SC model. The Updating Rules of SC State Evolution. 1 Acceleration or deceleration process: ]) / [ , min( ) 1 ( max T d v t v i i → + 2 Random selection process with probability p : ) 0 , / ; / ] / [ , / )( 0 , 1 ) ( max( ) 1 ( max max = > − = < − → + p v T ifd T d T d p v T ifd t v t v i i i i i i 3 Location Update: ) 1 ( ) ( ) 1 ( + + → + t v t x t x i i i Where ] / [ T di represents the smallest integer but not less than T di / . Computer Simulation and Numerical Analysis In the simulation, the length of the lane is L , and if the total number of vehicles on the lane is N , we will get that the total density of the vehicle L N / = λ ;the total lane occupancy (the ratio of the number of grid points occupied by all vehicles to the lane length) L N c / 2 = . In order to consider the mixing degree of SC vehicles, SC vehicle mixing ratio coefficient R is introduced, 0 . 1 0 . 0 ≤ ≤ R . When 0 . 0 = R , there is no SC vehicle in the lane ,while 0 . 1 = R , there are only SC vehicles in the lane.The average velocity at time t is defined as ∑ = = N i i t t v N V 1 _ ) ( 1 ; the average flux is λ × = t t V J _ . The simulation adopts the periodic boundary condition.At the initial time, the vehicle is randomly mixed in the lane according to the mixed proportion coefficient R , and the initial velocity is 0,and the 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Engineering, volume 126
Electronic Medical Records: Management and Implementation

A medical record contains personal data, a summary of medical history, and documentation of medical events, including symptoms, diagnoses, treatments, and outcomes. Its main purpose is to provide essential facts for medical diagnoses. It also forms the first link in the information chain, producing the depersonalized aggregated data for knowledge discovery and statistical analysis. A medical record is traditionally paper based, rendering it difficult to search for useful information and to reuse data for changing tasks. Often the paper chart is thick, tattered, disorganized, and illegible; progress notes, consultants’ notes, nurses’ notes, and radiology reports are all comingled in accession sequence. Practitioners claim to spend as much as 75% of their work time chasing specific data items on pieces of paper [1]. The records confuse rather than enlighten; they contain distorted, deleted, and misleading information [2] and provide a forbidding challenge to anyone who tries to understand what is happening to the patient [3]. At a time when the concept of “informed patient” is becoming the norm, the records can hardly be used to inform the patient with a coherent, consistent packet of information. Most importantly, it is nearly impossible to exchange data among healthcare providers, to accumulate data for knowledge discovery, and to connect medical records to the growing body of medical facts stored in medical expert systems. To address these issues with paper-based medical records, there has long been a vision to store an entire medical record, or any part of it, electronically so that a paper-based chart CONTENTS
Influences of Tangluoning Oral Solution on content of serum IGF-1 and gene expression of liver IGF-1 in rats with diabetes induced by STZ

Objective To observe the influences of Tangluoning Oral Solution(TOS) on the content of serum insulin-like growth factor-1(IGF-1) and gene expression of liver IGF-1 in rats with diabetes induced by streptozotocin(STZ). Methods The rat model of diabetes was established by the induction of STZ,and then all rats were randomly divided into the model group,Western drug(epalrestat) group and TOS group.After treatment for 12 weeks ELISA was used to detect the content of serum IGF-1 and RT-PCR was applied to determine the expression of liver IGF-1.Results In the model group the serum IGF-1 content decreased significantly and the expression of liver IGF-1 mRNA was down-regulated significantly compared with those in the normal group(P0.01). In Western drug group and TOS group serum IGF-1 content increased significantly compared with that in the model group respectively(P0.01 or P0.05). There was a significant difference between TOS group and Western drug group(P0.01). In TOS group and Western drug group the expression of liver IGF-1 mRNA increased(P0.01) compared with that in the model group.Conclusion TOS can increase serum IGF-1 level,up-regulate the expression of liver IGF-1 mRNA,which may be the mechanism of TOS for treating diabetic peripheral neuropathy.
Reducción de dimensionalidad en Machine Learning.Diagnóstico de cáncer de mama bsado en datos genómicos y de imagen.

The aim of the project is to analyze some of the machine learning techniques that are currently being used to extract information from large amounts of data, to study the statistical and algebraic tools that these techniques use in calculations, and to apply them to Diagnosis and Classification of breast cancer. The handling of large amounts of data requires pre-processing of the same to be employed. This project presents and analyzes different tools used in the pre-processing of data and their impact on the final results. It is intended to reduce the dimensionality of the data, keeping the maximum possible amount of information that is contained within the data. The techniques introduced are applied to the detection and classification of breast cancer. Two databases are used. One of them is used in the detection of the disease and contains indicators taken from mammograms. The other database is used in the classification of breast cancer types and consists of genomic data. A study of the information contained in each database is carried out, as well as a pre-processing of said Data and the elaboration of the respective models. In the case of detection, there are three initial models for the detection of cancer: one based on a Bayesian regressor, another based in a logistic regression and finally, another using Support Vector Machines. Subsequently, the Analysis of main components to reduce dimensionality is applied and the results are compared. In the classification of breast cancer, the data is explored and Clustering techniques are used to observe how clusters behave. This enables the identification of patterns and groups of similar characteristics within the samples. To conclude, the results are contrasted against other techniques used for the same purpose to verify their robustness.
Modèles de jeux sérieux collaboratifs et mobiles

Les jeux serieux collaboratifs sur dispositifs mobiles integrent tous les ingredients necessaires a motiver la nouvelle generation d'apprenants. Cependant, la conception d'un scenario de jeu coherent, qui combine ressorts ludiques, mobilite, collaboration et activites pedagogiques, est tres complexe. Dans cet article, nous proposons trois modeles de jeux, qui integrent naturellement ces caracteristiques, de facon a favoriser l'atteinte des objectifs pedagogiques.
Erratum

Rosati E, Sabatini R, De Falco F, Del Papa B, Falzetti F, Di Ianni M, Cavalli L, Fettucciari K, Bartoli A, Screpanti I, Marconi P. gSecretase inhibitor I induces apoptosis in chronic lymphocytic leukemia cells by proteasome inhibition, endoplasmic reticulum stress increase and Notch down-regulation. Int J Cancer. 2013 Apr 15;132(8):1940–1953. doi: 10.1002/ijc.27863. Epub 2012 Oct 17. In this article, Figure 1b contained an error in the plot relative to DMSO treatment at 1 hr. The plot image of DMSO was mistakenly the same plot image relative to GSI treatment at 1 hr, but the gating numbers were correct. The corrected Figure 1b, showing the correct DMSO plot image, is now provided. The authors regret this error, which however, does not alter the conclusions of the study.
Low Cost Evolution in Materio

This thesis describes a method of using a Low-Cost computer to program Low-Cost materials to perform a computation. The work demonstrates that an evolutionary algorithm running on a Raspberry Pi can exploit physical properties of graphene and sets of resistors to solve simple travelling salesman problems. The work goes on to investigate the use of the platform to evolve a simple electro-magnetic sensor to show the applicability of the platform to solving other problems which cannot be solved in any other way.
Vpliv učiteljevih navodil na učno uspešnost dijakov pri učenju z e-učbeniki

E-education, e-learning and e-textbooks are concepts associated with modern education. Interactive e-textbooks represent a learning resource from which students can learn effectively. Even though contemporary students are skilful with technology in general, that does not mean they are skilful with technology based learning and may need guidance with such learning activities. In our research, we conducted an experiment in order to test the impact of teacher’s instructions on the academic achievements of high school students in learning with interactive e-textbooks. The study involved 83 high school students in their first year. There were 45 students in the experimental group (EG) and 38 students in the control group (CG). The students from the EG who have received teacher’s instructions on how to use multimedia and interactive elements of the e-textbook were more successful at learning than the students from the CG who did not get such instructions. Students of the EG perceived themselves as more competent and they used multimedia and interactive elements of a textbook more often than their peers from the CG. The results showed that students’ independent learning from e-textbooks can be more successful if the teacher provides clear instructions on how to use them.
Cognitive Design Principles for Visualizations: Revealing and Instantiating

The creation of visualizations can be automated, informed by design principles derived from cognitive research. We describe a collaboration between psychology and computer science to uncover design principles for assembly instructions and instantiate them in algorithms. Participants assembled an object and then constructed diagrammatic instructions; those instructions were first rated and then tested. It was found that effective visualizations contain step-by-step action diagrams with 3-D views that best reveal the assembly actions. The design principles were incorporated into algorithms that generate assembly instructions from object models. The general techniques as well as the specific principles extend to other visual explanations.
Applying Petri Nets Extensions To Modeling Commercial Bank Activity

The relevance of the study is determined by the need to improve the methods of modeling and simulating commercial bank activity, including for the purpose of calculating, controlling and managing the risk of the bank, in the context of the transition to the application of Basel III standards. This improvement becomes necessary due to a direct transition to new regulatory standards when the internal assessments of the main risks become the initial data for calculating the capital adequacy of a bank. The purpose of this article is to argue the opportunity to formulate a theory of the commercial bank model on the extensions of Petri nets theory. The main methods of research were the method of scientific abstraction and method of logical analysis. The main result obtained in the study and presented in the article is the argumentation of the possibility to analyze the quantitative and qualitative characteristics of a commercial bank with the help of Petri net extensions
Mapeo linfático y biopsia del ganglio centinela en pacientes con carcinoma epidermoide cutáneo de alto riesgo

l carcinoma epidermoide cutáneo (CEC) es un tumor maligno de las células escamosas que se origina en la epidermis y en la mucosa escamosa estratificada.1,2 Su incidencia está aumentando en todo el mundo debido al incremento de la exposición a los rayos ultravioleta como consecuencia de la destrucción de la capa de ozono causada por la polución atmosférica, al crecimiento de la expectativa de vida en la población y a la exposición crónica a sustancias carcinogénicas. El CEC es un problema de salud pública, su incidencia se ha triplicado en un periodo de 27 años. 6 E ARTÍCULO ORIGINAL
DEVELOPMENT OF FACE RECOGNITION TIME MONITORING AND ATTENDANCE SYSTEM

This study marks the attendance without human intervention. Face Recognition Time and attendance software systems are tools for efficient management of resources and accurate labor reporting. This study attempts to solve the long queue of the employee in the conventional fingerprint methods and improve the accuracy of attendance information. Database management system has played a role for the normalization of the data flow of the system and assisted the organization of attendance diagrams of the employee\, thus resulting to a more effective monitoring and attendance recording. To harness full potential in a networked environment, it is recommended to purchase additional face recognition device and immediate implementation of the developed system not only in the CSIT Department but also in SLSU Sogod Campus.