Miracle-dz/UniFAR-FTUs huggingface dataset:
Decision Tree Analysis to Improve e-mail Marketing Campaigns

The efficiency of e-mail campaigns is a big challenge for any ecommerce venture in terms of the response rate of e-mail campaigns and customer segmentation based on loyalty. Decision tree analysis are useful tools to extract customer information related to response rate from e-mail campaigns data. This study aims at predicting customer loyalty and improving the response rate of e-mail campaigns, specifically open rate and click through rate, using decision tree analysis such as CHAID , CART and QUIST. The methodology used in this study is Cross Industry Standard Process for Data Mining (CRISP – DM) methodology. The models are trained and tested using split sample validation. Furthermore, we used a classification measures to calculate the accuracy, precision, recall and F1 to evaluate the models. The models reported satisfactory results in predicting customer loyalty based on open rate, click through rate values and on customer demographic variables. The response rates also increase at the preferred moment at which e-mails should be send to customers in email campaigns.
PIER Working Paper 19-002 Dynamic Mechanisms with Verification

We consider a principal who allocates an indivisible object among a finite number of agents who arrive on-line, each of whom prefers to have the object than not. Each agent has access to private information about the principal’s payoff if he receives the object. The decision to allocate the object to an agent must be made upon arrival of an agent and is irreversible. There are no monetary transfers but he principal can inspect agents’ reports at a cost and punish them. A novelty of this paper is a reformulation of this dynamic problem as a compact linear program. Using the formulation we characterize the form of the optimal mechanism and reduce the dynamic version of the inspection problem with identical distributions to an instance of the secretary problem with one fewer secretary and a modified value distribution. This reduction also allows us to derive a prophet inequality for the dynamic version of the inspection problem.
A Study on Human Gait Kinematic Validation in Multi-Kinect v2 Environment

Assessment of lower extremity joint angles is a crucial task in clinical gait analysis. Microsoft Kinect (v2) has become very popular vision-based motion tracking system due to its low cost. But, in kinematic gait parameter assessment, single Kinect (v2) set-up was proved to be unworthy from the previous studies. The present study investigates three different case studies in determining the validity of multi-Kinect setup in assessing lower extremity joint angle where Inertial Measurement Unit was used as the gold standard. A simulation framework, OpenSim was used for joint angle generation using inverse kinematics. Substantial reduction of RMSE was observed in our case studies compared to state-of-art methods.
Explorer Extracting common sense knowledge from Wikipedia

Much of the natural language text found on the web contains various kinds of generic or “common sense” knowledge, and this information has long been recognized by artificial intelligence as an important supplement to more formal approaches to building Semantic Web knowledge bases. Consequently, we are exploring the possibility of automatically identifying “common sense” statements from unrestricted natural language text and mapping them to RDF. Our hypothesis is that common sense knowledge is often expressed in the form of generic statements such as Coffee is a popular beverage, and thus our work has focussed on the challenge of automatically identifying generic statements. We have been using the Wikipedia xml corpus as a rich source of common sense knowledge. For evaluation, we have been using the existing annotation of generic entities and relations in the ace 2005 corpus.
Evaluation of a Nurse-led Telephone Intervention with Symptomatic Heart Failure Patients

Evaluation of a Nurse-led Telephone Intervention with Symptomatic Heart Failure Patients Samantha Stone, MSN, FNP-BC Heart failure (HF) is a chronic illness that affects approximately 550,000 Americans each year. By 2037, the prevalence is expected to double. Many symptomatic HF patients have difficulty managing their symptoms and are often readmitted within thirty to sixty days after hospital discharge. Research has shown that symptom management and quality of life can be improved in HF patients by utilizing a nurse-led telephone intervention. With improved symptom management patients not only experience a better quality of life, but, HF hospital admission and readmission rates can be reduced. The objectives of this capstone project were to 1) increase patient awareness about their illness, 2) improve symptom management, and 3) improve their quality of life by utilizing a nurse-led telephone intervention on a weekly basis for six weeks following a hospitalization for HF within the past six months. Following the intervention patients showed statistically significant improvement in symptom management and awareness of their illness. Although not statistically significant, they also had overall improved quality of life. Running head: HEART FAILURE TELEPHONE INTERVENTION iii
Empirical Likelihood Estimation for Panel Count Data Models with Fixed Effects

In this paper we examine the empirical likelihood (EL) estimation for panel count data models with fixed effects. While the EL and optimal GMM estimators enjoy the same large sample properties, the former does dominate the latter in terms of finite sample bias as shown in our Monte Carlo simulation study. As applications, we consider two empirical studies. The first one examines the relationship between patents and research and development (R&D) expenditures. In contrast with the early findings in Hall, Griliches, and Hausman (1986) and Montalvo (1997), our results suggest that in addition to the contemporaneous R&D, the second lag of R&D also has a significant effect on patents. Moreover, the total effect of R&D is smaller than that of Montalvo (1997). In the second application, we examine if market-wide information and firm-specific information affect the number of stock transactions (NST) under different market conditions. It is found that while the market condition does play an important role in determining the behavior of NST, the up-market results are different from the linear-model-based results of Tai, Chiang and Chou (2006). JEL classification: C23, C25, G12
A Survey of Image Forgery Detection

: We are undoubtedly living in an age where we are exposed to a remarkable array of visual imagery. While we may have historically had conﬁdence in the integrity of this imagery, today’s digital technology has begun to erode this trust. From the tabloid magazines to the fashion industry, main-stream media outlets, scientiﬁc journals, political campaigns, courtrooms, and the photo hoaxes that land in our email in-boxes, doctored photographs are appearing with a growing frequency and sophistication. Over the past ﬁve years, the ﬁeld of digital forensics has emerged to help return some trust to digital images. Here I review the state of the art in this new and exciting ﬁeld. Digital watermarking has been proposed as a means by which an image can be authenticated (see, for example, [21, 5] for general surveys). The drawback of this approach is that a watermark must be inserted at the time of recording, which would limit this approach to specially equipped digital cameras. In contrast to these approaches, passive techniques for image forensics operate in the absence of any watermark or signature. These techniques work on the assumption that although digital forgeries may leave no visual clues of having been tampered with, they may alter the underlying statistics of an image. The set of image forensic tools can be roughly categorized into ﬁve categories: (1) pixel-based techniques detect statistical anomalies introduced at the pixel level; (2) format-based techniques leverage the statistical correlations introduced by a speciﬁc lossy compression scheme; (3) camera-based techniques exploit artifacts introduced by the camera lens, sensor or on-chip post-processing; (4) physically-based techniques explicitly model and detect anomalies in the three dimensional interaction between physical objects, light, and the camera; and (5) geometric-based techniques make measurements of objects in the world and their positions relative to the camera. I have selected several representative forensic tools within each of these categories to review. In so doing, I have undoubtedly omitted some worthy papers. My hope, however, is that this survey offers a representative sampling of the emerging ﬁeld of image forgery detection.
Manifestations of the European Ecological Footprint from the Perspective of Social Responsibility Codes

The process of converting the economy to more sustainable production forms is the essence of bio-economy, currently becoming more and more important in all the European countries. Sustainability is a complex concept that can be quantified through an entire system of indicators. A “marker” of corporate environmental responsibility, of the extent and manner in which the companies apply social responsibility codes is the ecological footprint. The present study identifies, using a cumulative ordinal logistic regression model with proportional odds, the factors with significant impact on the behavioral changes of the ecological footprint of the production, for finding ways of increasing the sustainability in the business environment, through a better application of social responsibility codes. At the same time, the variables included in the model were selected in accordance with the principles of the European Corporate Social Responsibility Strategy, serving as criteria for the hierarchy and clustering of European countries, for identifying patterns and predicting the behavior of ecological footprint of production, as a prerequisite for optimizing social environmental responsibility and applying social responsibility codes in the business environment. The analysis results indicate that the educational level of labor force, the degree of economic freedom and the use of renewable energy sources have a significant positive influence on the ecological footprint behavior, while the social exclusion has a significant negative effect, with a major impact on the prospects of sustainable growth, specific to bio-economy.
A Hybrid SEM-Neural Network Model for Predicting Determinants of Mobile Payment Services

ABSTRACT This study develops a new research model to understand and predict the key determinants influencing the adoption of mobile payment services in a Middle Eastern country, Oman. The research model was tested using a hybrid structural equation modeling (SEM) and neural network (NN) modeling. The findings suggest valuable insights into the mobile payment service providers in the development of an appropriate and effective strategy to raise the number of new consumers in Oman.
Value Added Tax and Economic Growth: An Empirical Study of China Perspective

This study investigates the role of Value-Added Tax (VAT) on the economic growth in China. The data used for the study is a time series of the period from 1985-2016. These researches use the gross domestic product (GDP) as a dependent variable. For the independent variables, this research using the total population, employed persons, consumer price index, and value-added tax. The current findings add to a growing body of literature on identifying the properties of VAT in China and identifying the tax system reform from 1993 to 2012 and the mechanism of transfer application of the business tax in the services sector to Value-Added Tax. The test result indicated to have a positive relationship between the GDP and independent variables value-added tax in both in the long and short-run
Ritonavir: expanded access begins, warning on drug interactions.

Abbott Laboratories is providing ritonavir, a protease inhibitor, through an expanded access program. Abbott warns that the drug's use should be monitored very closely. Ritonavir blocks a liver enzyme and its use with medications that are normally metabolized by the liver may cause toxic levels to build quickly. Call Project Inform for a list of drugs which should not be taken with ritonavir.
– Special issue : Imaging in Coronary Artery Disease The use of coronary artery calcium scanning in detection and risk stratification of coronary artery disease

Coronary artery calcium (CAC) scan can be obtained using chest computed tomography, with no use of contrast agents, and with a relatively low radiation exposure. The mere absence of calcium is associated with a good prognosis in asymptomatic subjects and in patients at low to medium risk of coronary artery disease. CAC can be quantified in different ways, with higher scores being associated with a higher cardiovascular risk. CAC carries both diagnostic and prognostic information over and above that determined by classical risk factors. This paper presents the overview of the current use of CAC scanning, its advantages and limitations, as well as potential future applica-
Towards Vector Space Models of Semantics and the Semiotic Textology Some Relations between Recent Advances in Computational Linguistics and Semiotic

3 Towards an integration of Vector Space Models in a Semiotic Textology framework. 6 3.1 The verbal conceptual sensus and the Vector Space Models of (Distributional) Semantics. 6 3.2 Similarity as interpretation at the first grade of the descriptiveexplicative interpretation. 9 3.3 Vector space models for the representation of the Relatum Imago and multimediality . 12
Bystrzycki Applications of additive combinatorics methods to some multiplicative problems

The main aim of this dissertation is the study of di erent ways in which additive combinatorics may be used to tackle some problems arising in multiplicative number theory. Speci c problems studied here concern computational complexity of calculating values of number-theoretic functions, sums of dilates and exponential sums. The main part of the thesis deals with the following problem: Suppose that for some natural number n and some prime number p we are given the set of residues mod p of all its divisors and we would like to know which of those residues correspond to prime factors of n. An algorithm which approximately solves this problem for p and n satisfying some natural conditions is presented and it is proved that there are plenty of such numbers. One interesting feature of the proof is that it relies on additive combinatorics. The proposed algorithm consists of two algorithms, which performed one after another lead to the solution. Failure of the rst part implies the structural properties captured by the notion of additive energy of the set which are then used by the second, more intricate part based on techniques from Fourier analysis. The main theorem of this part states that for a squarefree integer n satisfying some constraints and a prime number p satisfying some other technical conditions if we are given the set of residues modulo p of all divisors of n (denoted Ap), there exists an e cient deterministic algorithm which nds a set B such that Γp ⊂ B ⊂ Ap (where Γp denote the set of residues of prime divisors of n) and |B| < |Ap|. All conditions appearing in the assumptions are very weak and in fact occur for almost every squarefree number n and for enough primes p in order to be practical. In this way, we show that for all but o(x) squarefree numbers less than x and a suitable p (dependent only on x, not on n), the set B from theorem can be found. We also give an application of this result to the algorithm which nds factorization of a given number using an oracle for values of functions σk(n). In fact, the search for deterministic reductions of factorization to some other number-theoretic problems was our original motivation to study this problem. In the next part of the thesis the problem concerning exponential sums is studied. More speci cally the following expression
TERTIARY BIOVALORISATION OF GRAPE POMACE By JUSTINE OMA ANGADAM

In the Western Cape, South Africa and other regions globally, grape pomace (GP) is one of the abundant agro-waste from the winery industry. This study reports on the hyper-extraction of fermentable sugars from GP treated with white rot fungi (WRF) Phanerochaete chrysosporium BKMF 1767 to facilitate improved biovalorisation for total reducing sugars (TRS) extraction in conjunction with Nepenthes mirabilis digestive fluids. TRS were quantified using the 3,5-dinitrosalicylic acid (DNS) reagent method. The free readily dissolvable sugars from the GP recorded for the bio-treated (BT) samples was 206.39 ± 0.06 mg/L and for the untreated (UT) samples was 271.05 ± 0.02 mg/L. Overall, the TRS yield for the Bio-treated (BT) and untreated (UT) samples was recorded as 205.68 ± 0.09 and 380.93 ± 0.14 mg/L, respectively, using hot water pretreatment (HWP) with 2266.00 ± 0.73 (BT) and 2850.68 ± 0.31 mg/L (UT), respectively, for dilute acid pretreatment (DAP); with 2068.49 ± 6.02 (BT) and 2969.61 ± 8.054 mg/L (UT) respectively, using the cellulase pretreatment (CP) method. Using the HWP as a reference, the relative increases imparted by the biotreatment was higher (51%) for DAP and low (33%) for CP. The combination of conventional used pre-treatment methods (hot water pretreatment, dilute acid pre-treatment, and cellulase pre-treatment) in a single pot system was also done while monitoring the total residual phenolics (TRPCs) in the samples. Furthermore, powder X-ray diffraction (pXRD) were used to measure the crystallinity index (CrI) and functional groups of preand post-pretreated GP to ascertain the efficiency of the pre-treatment methods, with quantification of lignin, holocellulose, and ash. Overall, the TRS yield for N. mirabilis pre-treated agro-waste was 951 mg/L ± 4.666 mg/L, with biomass having a lower CrI of 33%, and 62% residual lignin content. Furthermore, reduced TRPCs were observed in hydrolysate, suggesting limited inhibitory by-product formation during N. mirabilis pre-treatment.
EasyChair Preprint No 1424 Multi-session lakeshore monitoring in visually challenging conditions

Long-term monitoring of natural environments raises significant challenges due to the strong perceptual aliasing in trees, bushes and shrubs. This paper reports on the multi-session localization and mapping of a small lake shore using an autonomous surface vessel equipped with a 2D lidar and a camera. Our publicly available dataset includes 130 autonomous surveys of the 1 km shoreline while recording lidar, GPS and image data. We build our globally consistent multi-session map using ICP at multiple scale. The end result is evaluated qualitatively by superimposing all the lidar maps, and quantitatively by comparing images taken from the same pose at different times. The localization and mapping results, as well as the dataset of image pairs, are made available within our public dataset.
Phytobezoar Induced Ileal Obstruction in Children - Report of Two Cases

Two cases of small bowel obstruction ( SBO) in children induced by phytobezoar impaction are reported. Both the children were between 3-4 yrs of age and had no history of any previous intra-abdominal operation. Preoperative diagnosis was not possible in either case. Both the cases were diagnosed at laparotomy and obstruction was relieved by disintegration of the phytobezoar mass. Postoperatively, after specific questioning suggestive history of Carissa Opaca (Garna) ingestion, 24 hrs before onset of symptoms was obtained from the parents.
University of Dundee Modeling human errors in security protocols

Many security protocols involve humans, not machines, as endpoints. The differences are critical: humans are not only computationally weaker than machines, they are naive, careless, and gullible. In this paper, we provide a model for formalizing and reasoning about these inherent human limitations and their consequences. Specifically, we formalize models of fallible humans in security protocols as multiset rewrite theories. We show how the Tamarin tool can then be used to automatically analyze security protocols involving human errors. We provide case studies of authentication protocols that show how different protocol constructions and features differ in their effectiveness with respect to different kinds of fallible humans. This provides a starting point for a fine-grained classification of security protocols from a usable-security perspective.
GOODNESS-OFFIT TESTS FOR COMPOUND POISSON DISTRIBUTIONS BASED ON THE MOMENT GENERATING FUNCTION

talled compounding, distribution, while N is a Poisson random variable with parameter il which is distributed independently of the Yj ‘s . The Com-Poi model is the most popular case of a random sum of random variables. The statistical significance of this model arises from its applicability in real life situations: There the researcher often observes only the total “amount” X which is composed of an unknown random number N of (unobserved) random “contributions” Y, . Despite of the statistical applications of the Com-Poi distribution, the only goodness-of-fit
Nobody Expects the Unexpected: Unexpected Action Effects in Two Cortical Lesion Populations

We recruited patients with orbitofrontal lesion (OFC; n = 18), right lateral prefrontal cortex lesion (LPFC; n = 9), and healthy age-matched controls (CTR; n = 22) to perform a self-paced, two-choice random generation task (adopted from Iwanaga & Nittono, 2010)⁠. We compared how each set of participants responded to the perceivable consequences of their voluntary actions while recording behavioral responses and electroencephalography (EEG). All participants repeatedly pressed both a left and a right button, but not at the same time. Each button was normatively associated with its own tone, a 1 kHz tone for right button presses and a 2 kHz tone for left button presses. Participants were instructed that their button presses should be random, in a measured manner, without overlap (roughly 1500 ms between presses), and that the tones that their button presses produced were task-irrelevant. After an initial 20 presses, a button press would occasionally produce the tone normatively associated with the other button (p = 0.132) and this condition was classified as a cognitive mismatch. The standard condition, when a button press produced its expected tone was classified as a cognitive match. Event-related potentials (ERPs) were extracted from the EEG recording in relation to these two conditions. In CTR participants cognitive mismatch trials elicited enhanced N1, N2, P3, and a late positive potential (LPP) components. The OFC group had an ERP that indicated they did not differentiate between instances of cognitive match and mismatch. The LPFC group had an ERP on cognitive mismatch trials that was not highly differentiated from cognitive match trials, except for a posterior P3a component. Comparisons between and within the different participant groups suggest that action effect outcome monitoring is severely undermined by orbitofrontal damage and is impacted, but not devastated in patients with LPFC lesion. These findings are discussed in relation to the performance monitoring neural network, predictive processing, the cognitive map of a state space, and action effect experimental paradigms in general.
Strategies for Recruitment and Retention of Teen Mothers in a Program to Prevent Repeat Pregnancy

Recommended Citation South-Paul, Jeannette E. ; Ncube, Collette N. ; Lin, Chyongchiou J.; Nowalk, Mary Patricia; Kagwima, Ruth N. ; Wheeler, Emily A. ; Matambanadzo, Annamore; and Adeyeye, Ayotunde (2014) "Strategies for recruitment and retention of teen mothers in a program to prevent repeat pregnancy," Journal of Adolescent and Family Health: Vol. 6 : Iss. 2 , Article 1. Available at: https://scholar.utc. edu/jafh/vol6/iss2/1