Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient algorithm for frequent pattern mining for real - time business intelligence analytics in dense datasets

Finding frequent patterns from databases has been the most time consuming process in data mining tasks, like association rule mining. Frequent pattern mining in real-time is of increasing thrust in many business applications such as e-commerce, recommender systems, and supply-chain management and group decision support systems, to name a few. A plethora of efficient algorithms have been proposed till date, among which, vertical mining algorithms have been found to be very effective, usually outperforming the horizontal ones. However, with dense datasets, the performances of these algorithms significantly degrade. Moreover, these algorithms are not suited to respond to the real-time need. In this paper, we describe BDFS(b)-diff-sets, an algorithm to perform real-time frequent pattern mining using diff-sets and limited computing resources. Empirical evaluations show that our algorithm can make a fair estimation of the probable frequent patterns and reaches some of the longest frequent patterns much faster than the existing algorithms.
Maladaptive Perfectionism: A Potential Risk Factor for Smartphone Addiction?

C l i n M e d International Library Citation: Long J, Liu T (2015) Maladaptive Perfectionism: A Potential Risk Factor for Smartphone Addiction? Int Arch Addict Res Med 1:013 Received: November 02, 2015: Accepted: December 12, 2015: Published: December 14, 2015 Copyright: © 2015 Long J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Long et al. Int Arch Addict Res Med 2015, 1:3
Assessing a college readiness model for an independent residential school

ASSESSING A COLLEGE READINESS MODEL FOR AN INDEPENDENT RESIDENTIAL SCHOOL Natalia Dorovskaya Collins Old Dominion University, 2015 Chair: Dr. Dana D. Burnett Interest in the topic of college readiness is growing as more and more high school graduates are not prepared for college-level work (Bok, 2006, 2013; Gonzalez, 2012; Pascarella, Wolniak, Pierson, & Terenzini, 2003; Professor X, 2011). Most models offering assessment of the college readiness of students concentrate strictly upon the academic part of the issue high school GPAs, high school course titles, standardized test scores while disregarding non-academic elements, such as time management, the ability to demonstrate college-level academic behaviors and a general awareness of the environments present in different institutions of higher education. The purpose of this exploratory study was to identify certain key mechanisms, programs, and initiatives developed by a singular boarding school to prepare its students for the rigors of a college education. The study also examined the influence those programs and initiatives had on students. To accomplish this, the researcher interviewed school faculty, administrators, senior class students, and school alumni. The foundation for the interview questions was a college readiness model developed by Conley (2008) which included the examination of both academic and non-academic aspects of college readiness. The results of this research revealed that the programs, methods, and techniques developed and implemented by the private school under study had a positive influence on increasing the college readiness of its students.
- 682-Design of 1-D Linear-Phase Complex FIR Digital Filters by Genetic Algorithm Approach

-The digital filters with complex coefficients are useful in the application of processing analytic signals and complex envelops. They are also applied in single-sideband modulation systems. The genetic algorithm approach for designing such filters is developed in this paper. It is based on the evolution of real-valued population. The method is also optimal in the least-squares sense. Furthermore, the proposed algorithm has several practical advantages such as simplicity and easy implementation with satisfactory performance. Several numerical design examples are shown to demonstrate the usefulness and effectiveness of this proposed approach.
Ara-C, Idarubicine and Gentuzumab Ozogamicin (AIM) as Salvage Treatment in Advanced Acute Myeloid Leukemia Patients

Long-term survival of relapsed/refractory acute myeloid leukemia (AML) remains a major problem, particularly in patients not eligible for transplantation. We hereby evaluated the feasibility and efficacy of adding Gemtuzumab Ozogamicin to salvage chemotherapy (Ara-C, Idarubicine, Peg-Filgrastim) in relapsed/refractory AML. The main endpoints were: the rate of complete remissions (CR) and the proportion of patients capable of undergoing a stem cell transplant. Fourty-two patients were enrolled. The overall CR rate was 76% and no induction deaths were reported. In 56% of patients, a transplant procedure could be performed. The treatment schedule proved feasible and well tolerated, providing a high CR rate and a useful bridge to transplant.
Risk and risk management in organic agriculture: Views of organic farmers

Abstract In a series of focus groups during 2001 and 2002, organic farmers from different regions of the United States identified a wide range of risks to their operations. The focus groups were facilitated by the University of Maryland in cooperation with a research team from USDA's Economic Research Service, to explore the risks faced by organic farmers, how they are managed, and needs for risk management assistance. Contamination of organic production from genetically modified organisms was seen as a major risk, particularly by grain, soybean and cotton farmers. Focus-group participants producing grains and cotton—many of whom knew about and had obtained crop insurance—raised concerns about coverage offered, including the need for insurance to reflect the higher prices received for organic crops. Most fruit and vegetable producers participating in the focus groups had little knowledge of crop insurance. When provided with basic information about crop insurance, operators of small fruit and vegetable farms were skeptical about its usefulness for their type of operation.
Qualitative 3D Surface Reconstruction from Images

Prior to the advent of appearance-based recognition in the early 1990’s, object categorization researchers modeled the prototypical shape of an object, seeking models that were invariant to changes in color, texture, and minor within-class shape deformation. While these categorical models were well-motivated, they could not be reliably recovered from real images of real objects, and eventually gave way to models based on recurring, local, appearance-based features. But while appearance yields powerful exemplar-based recognition features, it is seldom generic to a category. In this work, we use registered optical and range images of objects to learn a mapping from region appearance to qualitative surface shape. At training time, from a set of extracted regions, we compute features describing both the external region boundary as well as the internal region appearance. The corresponding regions in the registered range image can be fit with second-order surfaces, from which mean (H) and Gaussian (K) curvatures can be computed. The signs of these curvatures, in turn, specify one of 8 possible qualitative surface labels [1]. The set of superpixels, paired with surface labels, forms our training set, and is used to learn the parameters of a conditional random field that accounts for both spatial constraints and image evidence. Figure 1 illustrates our operating regime: the qualitative HK labels of the vocabulary, the superpixel random field, and the surface labeling corresponding to the superpixels. Learning 3-D shape from realistic images has been attempted recently. Hoeim et al. [3] and Saxena et al. [2] learn to segment an image into planar structures that are suitable for navigation or simple contextual analysis. In contrast, we aim at a richer representation that better supports object recogition, recovering a mid-level, qualitative shape description of an object without invoking an object-specific model, such as a teapot or human. Even a sparse labeling of the shapes of an object’s surfaces can yield a powerful set of viewpoint-invariant shape indices for object categorization. We
Race, Ethnicity, and Real Estate Appraisal

If a healthy race is to be reared, it can be reared only in healthy homes; if infant mortality is to be reduced and tuberculosis to be stamped out, the first essential is the improvement of housing conditions; if drink and crime are to be successfully combated, decent sanitary houses must be provided. If "unrest" is to be converted into contentment, the provision of good houses may prove one of the most potent agents in that conversion. King George V, 1919 A nation of homeowners, of people who own a real share in their own land, is unconquerable. President Franklin D. Roosevelt, 1933
Marque sur les réseaux sociaux : Etude exploratoire des perceptions des consommateurs internautes

Pour rester (tres) proches de ses clients, les marques, aujourd’hui, tentent tout, elles ont bien compris qu’il faut suivre leurs clients la ou ils sont voire meme dans les espaces concus a l’origine pour les etres humains, notamment les reseaux sociaux. Ces marques ne se jugent pas moins humaines, mettant leur personnalite de marque en avant, elles se permettent des comptes sur les medias sociaux en adoptant un comportant humain qui est la conversation. A la lumiere d’une serie d’entretien, cette recherche exploratoire montre que les marques en conversation sur les reseaux sociaux peuvent paraitre plus humaines, gagner la confiance des internautes ainsi que d’ameliorer les perceptions qui varient selon le style de communication adopte par les marques dans leur conversations.
Nationwide Surveillance in Uterine Cancer: Survival Analysis and the Importance of Birth Cohort: 30-Year Population-Based Registry in Taiwan

Introduction Uterine cancer was the most rapidly increasing malignancy and the second most common gynecologic malignancy in Taiwan. Methods We analyzed the secular trend of uterine cancer incidence and compare the survival of women with uterine carcinomas and uterine sarcomas in Taiwan. Data on women diagnosed with uterine cancer between 1979 and 2008 were obtained from the Taiwan cancer registry. Survival data were analyzed by using Kaplan-Meier and Cox proportional hazards regression methods. Results Records of 11,558 women with uterine carcinomas and 1,226 women with uterine sarcomas were analyzed. The age-adjusted incidence rate of endometrioid adenocarcinoma increased from 0.83 per 100,000 women per year between 1979 and 1983 to 7.50 per 100,000 women per year between 2004 and 2008. The 5-year survival rate of women with endometrioid adenocarcinoma (83.2%) was higher than that for women with clear cell carcinoma (58.3%), serous carcinoma (54.4%), and carcinosarcoma (35.2%) (p<0.0001, log-rank test). The 5-year survival rates of women with low grade endometrial stromal sarcoma, endometrial stromal sarcoma, leiomyosarcoma (LMS), and adenosarcoma were 97.5%, 73.5%, 60.1%, and 77.2%, respectively (p<0.0001, log rank test). The histologic type of endometrioid adenocarcinoma, young age, and treatment period after 2000 were independent, favorable prognostic factors in women with uterine carcinomas by multivariate analysis. The histologic type of LMS, old age, and treatment period after 2000 were independent, poor prognostic factors in women with uterine sarcomas by multivariate analysis. Conclusions An increase over time in the number of patients with endometrioid adenocarcinomas was noted in this 30-year, nationwide, population-based study. Histologic type, age and treatment period were survival factors for uterine cancers. A more comprehensive assessment of uterine cancers and patient care should be undertaken on this increasingly common type of cancer.
Non-intrusive estimation and prediction of residential AC energy consumption

Residential buildings account for a significant proportion of overall energy consumption across the world. Decentralized room level Air Conditioners (ACs) are a commonplace in developing countries such as India, contributing a major share (34% in India) of the total residential energy consumption. Option to independently control each AC presents a prime opportunity for an energy saving system. Thus, we propose PACMAN to non-intrusively (using only the temperature information) predict AC energy consumption prior to usage and estimate energy consumption post-usage. We discuss various possible applications and use cases of such feedback for the occupants. To empirically validate the performance of PACMAN, we conducted an in-situ study across seven homes in Delhi (India). We collected around 2200 hours of usage data from the different ACs, room types, and thermostat temperatures. We achieved an average accuracy of 85.3% and 83.7% with the best accuracy of 97.0% and 93.3% for the estimation and prediction of AC energy consumption respectively, across all homes. Towards the end, we discuss various outlier scenarios, opening up multiple directions for further research in this domain.
A Ubiquitous and Low-Cost Solution for Movement Monitoring and Accident Detection Based on Sensor Fusion

The low average birth rate in developed countries and the increase in life expectancy have lead society to face for the first time an ageing situation. This situation associated with the World's economic crisis (which started in 2008) forces the need of equating better and more efficient ways of providing more quality of life for the elderly. In this context, the solution presented in this work proposes to tackle the problem of monitoring the elderly in a way that is not restrictive for the life of the monitored, avoiding the need for premature nursing home admissions. To this end, the system uses the fusion of sensory data provided by a network of wireless sensors placed on the periphery of the user. Our approach was also designed with a low-cost deployment in mind, so that the target group may be as wide as possible. Regarding the detection of long-term problems, the tests conducted showed that the precision of the system in identifying and discerning body postures and body movements allows for a valid monitorization and rehabilitation of the user. Moreover, concerning the detection of accidents, while the proposed solution presented a near 100% precision at detecting normal falls, the detection of more complex falls (i.e., hampered falls) will require further study.
THE HOME COUNTRY EFFECTS OF FDI IN DEVELOPED ECONOMIES

This paper surveys the effects of outward foreign direct investment on the developed home countries of multinational corporations. The focus is on the production interactions arising from outward investment – what is the impact on home country exports and production structure – but the paper also discusses effects on investment, the balance-of-payments, technology and knowledge, and political decision-making in the home country. The main conclusion is that outward FDI is beneficial to the investing firm, but that the effects on the home country vary depending on the characteristics of the investment project and the business environment in the home and host countries. In most cases, there is only a small impact on total exports and production in the developed home countries, but the net effect on employment may be mildly negative. This is related to a shift in production structure, whereby labor intensive activities are outsourced to host countries with lower wage levels, and more advanced operations are kept at home. Most home countries encourage outward investment, but the fear for negative effects (particularly on the balance-of-payments) has at times motivated restrictions on FDI. The final part of the paper discusses effects on developing home countries, and notes that these are likely to coincide with the effects on developed home countries. One exception is technology-sourcing investments, which may be more important than in developed home countries, and which may, at least in theory, provide an alternative to inward FDI as a source of technology for the more advanced developing economies.
Robust Invariant Feature Extration for Object Recognition and Natural Landmark based Autonomous Navigation

In this paper, we present a new robust image feature detector for the object recognition and vision based mobile robot navigation. The proposed algorithm extracts highly robust and repeatable features based on the key idea of tracking and grouping multi-scale interest points and selecting a unique representative structure with the strongest response in both spatial and scale domains. Weighted Zernike moments are used as the local descriptor for feature representation. The experimental results and performance evaluation show that our feature detector has high repeatability and invariance to large scale, viewpoint and illumination changes. The efficiency and usefulness of the proposed feature detection method are also confirmed by the excellent performance on object recognition and robot navigation.
ASSESSING DATABASE AND NETWORK THREATS IN TRADITIONAL AND CLOUD COMPUTING

Cloud Computing is currently one of the most widely-spoken terms in IT. While it offers a range of technological and financial benefits, its wide acceptance by organizations is not yet wide spread. Security concerns are a main reason for this and this paper studies the data and network threats posed in both traditional and cloud paradigms in an effort to assert in which areas cloud computing addresses security issues and where it does introduce new ones. This evaluation is based on Microsoft’s STRIDE threat model and discusses the stakeholders, the impact and recommendations for tackling each threat.
WORKING ON TRAUMA – A SYSTEMATIC REVIEW OF TF-CBT WORK WITH CHILD SURVIVORS OF SEXUAL ABUSE

Although there is growing interest in evidence-based practice (EBP), the implementation of research into clinical practice is still underutilised (DiCenso, Guyatt & Ciliska, 2005; Rycroft-Malone & Bucknall 2010). One emerging method in clinical practice with child survivors of sexual abuse is trauma-focused cognitive behavioural therapy (TF-CBT). This study aimed to systematically review the literature on TF-CBT work with child survivors of sexual abuse in an attempt to provide social work educators and practitioners with sufficient information about these treatments, which they can pursue in ongoing education and training
Emotion classification using residual sinusoidal peak amplitude

In this work, a new feature, residual sinusoidal peak amplitude (RSPA), is proposed for emotion classification. The RSPA feature is evaluated from the LP residual of the speech signal using sinusoidal model. Residual signal is a major source of the excitation and it is expected that emotional information can be well manifested in the residual signal. The effectiveness of the proposed feature is explored using statistical analysis. Support Vector Machine (SVM) classifier is used for performance analysis of the RSPA feature using EMO-DB database. The recognition results show that the proposed RSPA feature outperforms the linear prediction coefficients (LPCs) and TEO-CB-Auto-Env features. Combination of the RSPA and mel frequency cepstral coefficients (MFCC) further improves the recognition performance of the emotion classification.
Compliance and psychological reactance in schizophrenia.

OBJECTIVES Non-compliance with neuroleptic medication in schizophrenia is a major cause of relapse. A number of sociodemographic variables, and illness, attitudinal and treatment variables, have been demonstrated to be associated with non-compliance. The present study examined a range of these variables and their predictive value in determining past and current compliance. METHODS Thirty-nine patients suffering from schizophrenia and three patients suffering from schizoaffective disorder completed a series of questionnaires assessing psychological reactance, insight, subjective response to medication, perceived threat to freedom of choice, and degree of current and past compliance. Logistic regression analyses were performed to determine which factors best predicted past and current compliance. RESULTS Psychological reactance and age were found to be the best predictors of past compliance, with an interaction between reactance and perceived threat to freedom of choice posed by treatment provision also making a significant contribution. Past compliance behaviour and subjective response to medication predicted current compliance most significantly. CONCLUSIONS Reactance is an important predictor of compliance history especially when patients perceive treatment to be a threat to freedom of choice. Subjective response to neuroleptics is most important in predicting current compliance. Implications for intervention are discussed.
Providing support for creative group brainstorming: taxonomy and technologies

This paper describes our plans and current work towards developing a user modeling- based learning environment for creative group brainstorming in qualitative domains. This research framework aims to guide the investigation and integration of different brainstorming activities, theoretical foundations and supportive technologies in order to benefit learning most. Intervention studies and system development are proposed to take place in parallel to ensure that the design of system behavior is informed by research results.
A fast miniature plasma focus based compact and portable nanosecond pulsed neutron source

A low energy fast miniature plasma focus device ‘FMPF-1’ has recently been developed to be used as compact and portable nanosecond pulsed neutron source for field applications. The system operates in deuterium producing maximum neutron yield in the order of 10 6 neutrons/ pulse in 4� sr. at ~80kA peak discharge current. In the range of 4 to 7mbar distinct and sharp dip in the current derivative signal indicates strong focusing of plasma column registering subsequent emission of hard x-rays (HXR) followed by neutron pulse. The average time duration (FWHM) of HXR and neutron pulses, obtained using NE102A scintillator photomultiplier detector is about ~15 and ~45ns respectively. The overall dimensions of the apparatus including capacitor bank, spark gap and the focus chamber is 0.2m�0.2m�0.5m and the total weight of system is ~25kg.
Attacking a Trusted Computing Platform Improving the Security of the TCG Specification

We describe a flaw which we individuated in the Object-Independent Authorization Protocol (OIAP), an authorization protocol which represents one of the building blocks of the Trusted Platform Module (TPM), the core of the Trusted Computing Platform (TP) as devised by the Trusted Computing Group (TCG) standards. In particular we show that the protocol fails to protect messages exchanges against straight replay attacks. Using such a flaw an attacker could compromise the correct behavior of a TP, thus undermining its main property namely trust. A proposed solution, which requires the modification of the OIAP authorization protocol in order to provide “real” protection against replay attack, has been devised and described as well.