Miracle-dz/UniFAR-FTUs huggingface dataset:
eSkyline: Processing Skyline Queries over Encrypted Data

The advent of cloud computing redefines the traditional query processing paradigm. Whereas computational overhead and memory constraints become less prohibitive, data privacy, security, and confidentiality concerns become top priorities. In particular, as data owners outsource the management of their data to service providers, query processing over such data has more resources to tap into, yet the data oftentimes has to be encrypted so as to prevent unauthorized access. The challenge that arises in such a setting is to devise an encryption scheme that still allows for query results to be efficiently computed using the encrypted data values. An important type of query that raises unconventional requirements in terms of the operator that has to be evaluated is the skyline query, which returns a set of objects in a dataset whose values are not dominated by any other object therein. In this demonstration, we present eSkyline, a prototype system and query interface that enables the processing of skyline queries over encrypted data, even without preserving the order on each attribute as order-preserving encryption would do. Our system comprises of an encryption scheme that facilitates the evaluation of domination relationships, hence allows for state-of-the-art skyline processing algorithms to be used. The actual data values are reconstructed only at the client side, where the encryption key is known. Our demo visualizes the details of the encryption scheme, allows a user to interact with a server, and showcases the efficiency of computing skyline queries and decrypting the results.
Performance of double threshold energy detection in cooperative-cognitive networks over Nakagami fading channels

In this paper the performance of Cooperative-Cognitive Networks is analyzed using the Double Threshold Energy Detection algorithm. Introducing Double Threshold Energy Detection improves the spectrum detection accuracy and also it reduces the noise uncertainty. Monte Carlo Simulation is performed to show the significant improvement in the performance of Cooperative-Cognitive networks for proposed algorithm over Nakagami-m fading channels and using Maximal Ratio Combining (MRC) on the receiver. The results show that the proposed algorithm effectively improves the Collision Probability at a cost of little decrease in Detection Probability and Probability of spectrum unavailable.
Neue Erkenntnisse zur unterschätzten Beeinträchtigung der Lebensqualität bei altersbedingter Makuladegeneration – ein Literaturüberblick

Different forms of age-related macular degeneration (AMD) can lead to massive visual impairment up to blindness. Therefore, AMD has a high impact on patients' daily life and causes restrictions of their psychological well-being, autonomy and mobility. These restrictions influence their quality of life. It is difficult to define the term "quality of life". It consists of different aspects that can be measured with psychometric tests. Besides the general health status and the psychological well-being, the vision-specific functional status plays a central role for determining the quality of life of AMD patients. To compare the impact of different diseases on the quality of life, the utility analysis has been developed. It demonstrates the relevance of AMD for patients and shows that its impact on patients' life is comparable to those of other systemic diseases like carcinoma or HIV. The impairment of patients' quality of life by AMD is often underestimated by their attending ophthalmologists. Different medical treatments have influenced the quality of life of AMD patients. However, there is still a large group that cannot be treated. These patients benefit from rehabilitation with low vision aids or psychosocial interventions. Further clinical trials at a high evidence level using valid and comparable psychometric tests are necessary to improve the therapy for and the rehabilitation of AMD patients and to increase their quality of life.
Sequential Experimental Designs for Generalized Linear Models

We consider the problem of experimental design when the response is modeled by a generalized linear model (GLM) and the experimental plan can be determined sequentially. Most previous research on this problem has been limited either to one-factor, binary response experiments or to augmenting the design when there are already sufficient data to compute parameter estimates. We suggest a new procedure for the sequential choice of observations that offers five important advantages: (1) It can be applied to multifactor experiments and is not limited to the one-factor setting; (2) it can be used with any GLM, not just binary responses; (3) both fully sequential and group sequential settings are treated; (4) it enables efficient design from the outset of the experiment; and (5) the experimenter is not constrained to specify a single model and can use the prior to reflect uncertainty as to the link function and the form of the linear predictor. Our procedure is based on a D-optimality criterion and on a Bayesian analysis that exploits a discretization of the parameter space to efficiently represent the posterior distribution. In the one-factor setting, a simulation study shows that our method is superior in efficiency to commonly used procedures, such as the “Bruceton” test, Neyer's procedure, or Wu's improved Robbins–Monro method. We also present a comparison of results obtained with the new algorithm versus the “Bruceton” method on an actual sensitivity test conducted recently at an industrial plant. Source code for the algorithms and examples throughout the article is available at http://www.math.tau.ac. il/∼dms/GLM_Design.
Optimization With Affine Homogeneous Quadratic Integral Inequality Constraints

We introduce a new technique to optimize a linear cost function subject to an affine homogeneous quadratic integral inequality, i.e., the requirement that a homogeneous quadratic integral functional affine in the optimization variables is nonnegative over a space of functions defined by homogeneous boundary conditions. Such problems arise in control and stability or input-to-state/output analysis of systems governed by partial differential equations (PDEs), particularly fluid dynamical systems. We derive outer approximations for the feasible set of a homogeneous quadratic integral inequality in terms of linear matrix inequalities (LMIs), and show that a convergent sequence of lower bounds for the optimal cost can be computed with a sequence of semidefinite programs (SDPs). We also obtain inner approximations in terms of LMIs and sum-of-squares constraints, so upper bounds for the optimal cost and strictly feasible points for the integral inequality can be computed with SDPs. We present QUINOPT, an open-source add-on to YALMIP to aid the formulation and solution of our SDPs, and demonstrate our techniques on problems arising from the stability analysis of PDEs.
Side-chain Liquid Crystal Polymers (SCLCP): Methods and Materials. An Overview

This review focuses on recent developments in the chemistry of side chain liquid crystal polymers. It concentrates on current trends in synthetic methods and novel, well defined structures, supramolecular arrangements, properties, and applications. The review covers literature published in this century, apart from some areas, such as dendritic and elastomeric systems, which have been recently reviewed.
A tool for RApid model parameterization and its applications

The utility of simulations and analysis heavily relies on good models of network traffic. However, it is difficult to model and simulate the Internet traffic because of the network's great heterogeneity and rapid change. The statistical properties of Internet traffic not only constantly change over time but also vary in other dimensions such as locations and directions. Previously we have developed a tool RAMP that supports rapid parameterization of traffic models from live network measurements. In this paper, we first extend RAMP to support near-real-time trace-driven simulation. Next, we demonstrate the applications of RAMP via three case studies: generation of realistic traffic model for simulation, generation of high bandwidth synthetic network traces, and analysis and modeling of malicious traffic. Finally, we discuss some lessons we learned from using RAMP for traffic modeling.
Application of classifiers: Support vector machines, artificial neural networks and classification trees to identify acoustic schools

The purpose of this study was to compare the results of the classification of the pelagic fish species, the common sardine, anchovy, and jack mackerel with classification trees (CART), Support Vector Machine (SVM) and artificial neural network (multilayer perceptron, MLP), using mono-frequency acoustic data in southern-central Chile. The classifiers had similar performances, those of the MLP and SVM being the same, while t hat of CART was the lowest. The separation of anchovy and common sardine is considered acceptable with all methods, 90.8% for anchovy and between 87.4% (CART) and 90.3% (MLP) for sardine. These performances were higher than that for the jack mackerel, 77.8% (CART), 81.5% (MLP) and 85.2% (SVM). There is concordance on the groups of descriptors (bathymetric and positional) considered as effective for classification in all methods, but the importance of the descriptors presented by each method is not fully concordant. The energetic and morphological descriptor had low incidence. We recommend trying many classifiers to identify acoustic schools as a good practice.
Speech and Prosody indevelopmental disorders: Autismand Down’s Syndrome

Language impairment is a key characteristic of many developmental disorders, with the relationship between linguistic and cognitive ability a critical topic for research in this field. Speech (articulation and phonology) and prosody have largely been absent from these discussions, perhaps because they are not universally impaired. The portfolio of published research critically appraised here addresses the relationships between speech and prosody and other domains, such as language and cognition, in two conditions in which disordered speech is common: primarily at the suprasegmental level in autism and at the segmental level in Down’s syndrome. Speech disorders were found in both conditions, though speech was much more severely impaired in Down’s syndrome. Errors were typically categorised as delayed phonological processes, implying a linguistic cause. However, through fine phonetic transcription and instrumental techniques it was shown that both conditions also presented with distortions that were more phonetic in nature and with non-developmental errors. Severity of speech disorder was not related to cognitive or linguistic ability as measured by standardised assessments, suggesting that a generalised delay in language or cognition was not the cause of disordered speech. In autism minor delays and distortions may be due to a lack of ability to identify with peers and impaired theory of mind, whereas in Down’s syndrome anatomical differences and difficulty with motor planning are likely causes. Both linguistic and paralinguistic prosody were found to be disordered in children with autism and correlations with linguistic ability were found. However, disordered prosody is more likely to be due to impaired theory of mind or weak central coherence than a result of delayed language. Both autism and Down’s syndrome present with speech that is disordered rather than simply delayed and this is unlikely to be due to delayed language, suggesting that specific, targeted intervention may be warranted.
An Automatic Approach for Translating Simple Images into Text Descriptions and Speech for Visually Impaired People

Image processing is a rapidly growing field of research. Images are of different file formats and of different things, places, humans, scientific, astrological and many such. An image is a collection of several pixels arranged in rows and columns. These images are captured, processed and stored for various uses. For common people it is very easy to identify and analyze general images but for the blind and physically disabled people it is difficult. Unfortunately, there is no prior medium or interface for such needy people to communicate with the world. Blind or visually impaired people are usually those people who are neglected by the society, so there is always a need to help such people. Hence, we propose a new technique of converting images into text as well as speech using techniques provided by image processing like pre-processing, image segmentation, edge detection, object detection and speech synthesis. In this paper we first introduce image to text conversion need for blind people and system overview of image to text and speech conversion system. Edge detection plays an important role in this system where Canny edge detection algorithm is used to detect objects from images. Object recognition is done on the basis of color, size, texture and shape of the object.
Busy Beaver - An Evolutionary Approach

The Busy Beaver is an interesting theoretical problem proposed by Tibor Rado in 1962. Since then, it has attracted the attention of many researchers and several contests were organised trying to produce good solutions. In this paper, we propose an evolutionary approach to the problem. Our experimental results prove that this technique is very effective in attacking Busy Beaver, since we were able to find several Turing machines that outperform previous best-known solutions.
Human Cytomegalovirus UL97 Kinase and Nonkinase Functions Mediate Viral Cytoplasmic Secondary Envelopment

ABSTRACT Previous studies have revealed critical roles for the human cytomegalovirus (HCMV) UL97 kinase in viral nuclear maturation events. We have shown recently that UL97 affects the morphology of the viral cytoplasmic assembly compartment (AC) (M. Azzeh, A. Honigman, A. Taraboulos, A. Rouvinski, and D. G. Wolf, Virology 354:69-79, 2006). Here, we employed a comprehensive ultrastructural analysis to dissect the impact of UL97 on cytoplasmic steps of HCMV assembly. Using UL97 deletion (ΔUL97) and kinase-null (K355M) mutants, as well as the UL97 kinase inhibitor NGIC-I, we demonstrated that the loss of UL97 kinase activity resulted in a unique combination of cytoplasmic features: (i) the formation of pp65-rich aberrant cytoplasmic tegument aggregates, (ii) distorted intracytoplasmic membranes, which replaced the normal architecture of the AC, and (iv) a paucity of cytoplasmic tegumented capsids and dense bodies (DBs). We further showed that these abnormal assembly intermediates did not result from impaired nuclear capsid maturation and egress per se by using 2-bromo-5,6-dichloro-1-(β-d-ribofuranosyl) benzimidizole (BDCRB) to induce the artificial inhibition of nuclear maturation and the nucleocytoplasmic translocation of capsids. The specific abrogation of UL97 kinase activity under low-multiplicity-of-infection conditions resulted in the improved release of extracellular virus compared to that of ΔUL97, despite similar rates of viral DNA accumulation and similar effects on nuclear capsid maturation and egress. The only ultrastructural correlate of the growth difference was a higher number of cytoplasmic DBs, tegumented capsids, and clustered viral particles observed upon the specific abrogation of UL97 kinase activity compared to that of ΔUL97. These combined findings reveal a novel role for UL97 in HCMV cytoplasmic secondary envelopment steps, with a further distinction of kinase-mediated function in the formation of the virus-induced AC and a nonkinase function enhancing the efficacy of viral tegumentation and release.
The Role of Internal Business/IT Alignment and IT Governance for Service Quality in IT Outsourcing Arrangements

This paper theoretically argues and empirically evaluates how a firm's internal alignment and governance processes impact the service quality received from an external IT outsourcing provider. Using data from 154 firms, it is shown that good internal business/IT alignment leads to better and more accurate provider control processes which in turn improve service level agreements. The paper contributes to the literature in linking internal governance with external IT service quality, and by disclosing a largely neglected influence of alignment on governance and control processes.
Cognitive Deficit and Poverty in the First 5 Years of Childhood in Bangladesh

OBJECTIVE: We aimed to determine the timing and size of the cognitive deficit associated with poverty in the first 5 years of life and to examine the role of parental characteristics, pre- and postnatal growth, and stimulation in the home in Bangladeshi children. We hypothesized that the effect of poverty on cognition begins in infancy and is mainly mediated by these factors. METHODS: We enrolled 2853 singletons, a subsample from a pregnancy supplementation trial in a poor rural area. We assessed mental development at 7, 18, and 64 months; anthropometry at birth, 12, 24, and 64 months; home stimulation at 18 and 64 months; and family’s socioeconomic background. In multiple regression analyses, we examined the effect of poverty at birth on IQ at 64 months and the extent that other factors mediated the effect. RESULTS: A mean cognitive deficit of 0.2 (95% confidence interval –0.4 to –0.02) z scores between the first and fifth wealth quintiles was apparent at 7 months and increased to 1.2 (95% confidence interval –1.3 to –1.0) z scores of IQ by 64 months. Parental education, pre- and postnatal growth in length, and home stimulation mediated 86% of the effects of poverty on IQ and had independent effects. Growth in the first 2 years had larger effects than later growth. Home stimulation had effects throughout the period. CONCLUSIONS: Effects of poverty on children’s cognition are mostly mediated through parental education, birth size, growth in the first 24 months, and home stimulation in the first 5 years.
3D Atlas Building in the Context of Head and Neck Radiotherapy Based on Dense Deformation Fields

In this paper we present a methodology to build a computational anatomical atlas based on the analysis of dense deformation fields recovered by the Morphons non-rigid registration algorithm. The anatomical atlas construction procedure is based on the minimization of the effort required to register the whole database to a reference. The suitability of our method is demonstrated for atlas construction of the head and neck anatomy. In this application, CT is the most frequently used modality for the segmentation of organs at risk and clinical target volume. One challenge brought by the use of CT images is the presence of important artefacts caused by dental implants. Such artefacts make the use of most atlas building techniques described in the literature impracticable in this context. The results have shown that our model is faithful for representing the shape variability presented in human nature with the advantage that our anatomical atlas does not have any degree of smoothness.
An evaluation of indoor location determination technologies

The development of real-time locating systems (RTLS) has become an important add-on to many existing location aware systems. While GPS has solved most of the outdoor RTLS problems, it fails to repeat this success indoors. A number of technologies have been used to address the indoor tracking problem. The ability to accurately track the location of people indoors has many applications ranging from medical, military and logistical to entertainment. However, current systems cannot provide continuous real-time tracking of a moving target or lose capability when coverage is poor. The deployment of a real-time location determination system however is fraught with problems. To date there has been little research into comparing commercial systems on the market with regard to informing IT departments as to their performance in various aspects which are important to tracking devices and people in relatively confined areas. This article attempts to provide such a useful comparison by providing a review of the practicalities of installing certain location-sensing systems. We also comment on the accuracies achieved and problems encountered using the position-sensing systems.
Victimization and co-occurring disorders among adolescents

Purpose. The purpose of this study was to evaluate whether severe victimization experiences, and psychological and social resources were shared risk factors for internalizing only, externalizing only, and co-occurring internalizing and externalizing disorders among victimized substance-using adolescents. Method. Data for this cross-sectional study were obtained from a multisite research project. Adolescents, ages 11–18, participated in a comprehensive screening program for substance abuse at 106 Substance Abuse and Mental Health Services Administration (SAMHSA) Center for Substance Abuse Treatment (CSAT)-funded grantee sites throughout the United States. Results. Longer duration/frequent victimization, more than one type of victimization, recent victimization, low self-efficacy beliefs and available sources of emotional support were related to co-occurring internalizing and externalizing disorders. Victimization by a trusted person, however, was only related to internalizing disorders. Conclusion. The findings show that some indicators of severe victimization experiences, psychological and social resources are shared risk factors for internalizing, for externalizing, and for co-occurring internalizing and externalizing problems, thus providing support for the common factors model of co-morbidity. These findings suggest that practitioners in substance abuse treatment must thoroughly assess for severe victimization experiences among adolescents presenting with co-occurring mental health issues. Treatment planning and interventions may focus on helping adolescents cope effectively with their victimization experiences and addressing their MH needs. Particular
Database retrieval : the use of combined dissimilarities

In image retrieval systems, the key point is the description of the set of images. In this paper we show that a representation using a cloud of points offers a flexible description but suffers from class overlap. We propose a novel approach for describing clouds of points based on the support vector data description (SVDD). We show that combining image descriptions using dissimilarities improves the retrieval precision. Further we propose a method to select an efficient and robust subset of classifiers. We investigate the performance of the proposed retrieval technique on a database of 368 images.
Structured Index System at NTCIR Workshop 2: Information Retrieval Methods Using Ordered Co-occurrence of Words and their Dependency Relationships

We propose two Japanese-language information retrieval methods that enhance retrieval effectiveness by using relationships between words. The ﬁrst method uses dependency relationships between words in a sentence, while the second method uses proximity relationships, in particular the ordered co-occurrence information of words in a sentence as an approximation to the dependency relationships between them. We construct these two methods on the Structured Index, which represents dependency relationships be-tween words in a sentence as a set of binary trees. Structured Index is created by morphological analysis, dependency analysis, and compound noun analysis. We show the result of retrieval experiments using NTCIR–2, and discuss the effect of using relationships between words on Japanese information retrieval.