Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Visualization and Analysis of Cerebral Arteriovenous Malformation combining 3D and 4D MR Image Sequences

In this paper methods for visualization and analysis of cerebral arteriovenous malformations (AVM) are presented. Spatiotemporal 4D magnetic resonance angiography (MRA) image datasets and 3D MRA datasets with high spatial resolution were acquired for analyzing AVMs. One of the main tasks is the combination of the information of these 3D and 4D MRA image sequences. Initially, in the 3D MRA dataset the vessel system is segmented and a 3D surface model is generated. Then, in 4D MRA image sequences the temporal intensity curves are analyzed voxelwise and the time point of blood inflow is calculated. These parameters are saved as a 3D dataset representing the dynamic characteristic. After an affine 3D-3D registration of both MRA datasets the color-coded visualization of the temporal information in slice and surface model view with high local resolution becomes possible. The combined visualization of the individual and complicated anatomical structure and the haemodynamic in 3D supports the visual evaluation of the AVM.
Dominated destinations of tourist inside Iraq using personal information and frequency of travel

Tourism today is one of the most important economic and social sectors in the world, which plays a prominent role in the development of countries. This importance has grown as an industry through the social media networks.In this paper, a proposed method has been introduced distinguish the main factors that impact the Frequency of Travel (FoT) among Iraq local tourists. Application (API) graphics and scrapy are utilized to collect information from TripAdvisor social network in a period of (2015-2018). The collected information are reprocessed and coded for the specified nominal data using tied rank. It is important to note that the adopted technique does not lose any data about the attribute and brings different properties beforehand obscure. Data mining ordinal logistic regression is used to extract user's behavior upon local tourism in Iraq. The expected outcome of this work is to discover out the effect of personal information and the type of places on the selection of the local touristic places in Iraq. The collected information was exploited to know the preferred local touristic trends, because there are no statistics on the number of domestic tourists in Iraq. The proposed model was used for analyzing personal information and types of preferred tourism places as a factors affecting frequency of travel in Iraq. The obtained results show the prediction of preferred touristic places by tourists in Iraq.
Engaging students in using 3D printing technology to enhance cognitive structures and thought processes relevant to engineering design

We investigated the thought processes and cognitive structures of senior highschool students and first-year engineering college students with respect to 3D printing-based robotic insect design. First, we conducted a teaching experiment, followed by in-depth interviews, flow-maps and meta-listening activities, to assess the students’ thought processes and cognitive structures with respect to engineering design. This paper presents and discusses the results of this study and the findings can serve as a reference for the future design, development and implementation of related curricula.
Second Order Asymptotics for Quantum Hypothesis Testing

In the asymptotic theory of quantum hypothesis testing, the minimal error probability of the first kind jumps sharply from zero to one when the error exponent of the second kind passes by the point of the relative entropy of the two states in an increasing way. This is well known as the direct part and strong converse of quantum Stein's lemma. Here we look into the behavior of this sudden change and have make it clear how the error of first kind grows smoothly according to a lower order of the error exponent of the second kind, and hence we obtain the second-order asymptotics for quantum hypothesis testing. This actually implies quantum Stein's lemma as a special case. Meanwhile, our analysis also yields tight bounds for the case of finite sample size. These results have potential applications in quantum information theory. Our method is elementary, based on basic linear algebra and probability theory. It deals with the achievability part and the optimality part in a unified fashion.
Inferring Descriptions and Similarity for Music from Community Metadata

We propose methods for unsupervised learning of text profiles for music from unstructured text obtained from the web. The profiles can be used for classification, recommendation, and understanding, and may be used in conjunction with existing methods such as audio analysis and collaborative filtering to improve performance. A formal method for analyzing the quality of the learned profiles is given, and results indicate that they perform well when used to find similar artists.
A performance evaluation framework for fair solutions in ad hoc networks

Fairness in multihop ad hoc networks has received considerable attention in the literature. Many schemes have been proposed, which attempt to compute the ``optimal'' bit rates of the transmitting mobile nodes so that a certain fairness criterion is met. As the related literature indicates, there is a trade-off between fairness and efficiency, since fairness schemes typically reduce the channel utilization. Also, it is questionable whether certain fairness schemes have a positive or negative impact on the QoS of certain user services. So far, there has been limited research on the impact of the varying short-term allocations of these protocols, due to their inherent features and also nodes mobility, on the user-perceived QoS (and social welfare) for services of long duration. In this paper, we introduce an assessment framework, based on history-dependent utility functions that can be used as a holistic performance evaluation tool of these fairness schemes. These functions quantify the satisfaction that the ad hoc users obtain from the way their long-lived service sessions are allocated bandwidth, due to the behavior of the MANETs fair schemes. This way we can unambiguously compare the performance of various fair solutions whose maximization goals are inherently different (max-min fairness, proportional fairness, etc.). Finally, we demonstrate the usefulness of this framework by applying it on different protocols.
A kNN query processing algorithm using a tree index structure on the encrypted database

With the adoption of cloud computing, database outsourcing has emerged as a new platform. Due to the serious privacy concerns in the cloud, database need to be encrypted before being outsourced to the cloud. Therefore, various kNN query processing techniques have been proposed over the encrypted database. However, the existing schemes are either insecure or inefficient. So, we, in this paper, propose a new secure kNN query processing algorithm. Our algorithm guarantees the confidentiality of both the encrypted data and a user's query record. To achieve the high query processing efficiency, we also devise an encrypted index search scheme which can perform data filtering without revealing data access patterns. We show from our performance analysis that the proposed scheme outperforms the existing scheme in terms of a query processing cost while preserving data privacy.
Modeling Team-Development Lifecycle in Public Administration Courses

Abstract During the course of their academic experience, public administration students are expected to work as teams in order to complete projects and embrace a team-based philosophy for addressing public needs. Traditional team-development pedagogy omits a critical piece for future public administrators – developing team-development skills and competence through explicit reflection, modeling, and analysis of the team-development lifecycle. This paper demonstrates how modeling the team development lifecycle within a course setting — forming, storming, norming, performing, and adjourning (Tuckman, 1965; Tuckman & Jensen, 1977) — encourages students to explore the team-development process, and to experience and reflect on corresponding emotional and behavioral responses at the various team-development stages. By explicitly modeling the strategies in the context of an entire class serving as a single team, students develop a greater confidence and competence to engage future team-development opportunities. This article (a) articulates a strategy for how to model the team-development lifecycle in public administration courses, (b) identifies anticipated affective responses, and (c) offers examples of lessons learned, so that instructors can apply this pedagogical approach.
Building multi-device, adaptive thin-client web user interfaces with Extended Java Server Pages

We describe a new approach to providing adaptable thin client interfaces for web-based systems that allows a developer to specify a web-based interface using a device-independent mark-up language embedded in conventional Java Server Pages. At run-time this single interface description is used to automatically provide an interface for multiple web devices e.g. desk-top HTML and mobile WML-based systems, as well as highlight, hide or disable interface elements depending on the current user and user task. Our approach allows developers to more easily construct and maintain web-based user interfaces than other current approaches while utilising their existing server-side web components. We describe the software architecture of our system, its implementation using Java Server Page custom tag libraries, and an example application of our technique. We report our experiences using the technology to build three web-based applications and the results of two empirical studies of its effectiveness.
Characterization of attribute reduction of decision system through matroid theory

Attribute reduction is an important issue in rough sets. It has been widely used in pattern recognition, machine learning and data mining. Many mathematical theories, such as fuzzy sets, lattice and matrix, have been applied to study the issue for constructing more effective reduction algorithms. In this paper, the attribute reduction in the decision system is conducted under matroid theory. The matroid approximation space is proposed to build a bridge between the decision system and the matroid. In this way, a single valued decision system is represented by several matroids directly. By using the circuits of these matroids, the concept of equivalence class is formulated equivalently with the matroidal approach and then the lower and the upper matroidal approximations are established. Furthermore, some basic concepts of attribute reduction in rough sets are redescribed in the context of matroid approximation space. Finally, for any two subsets of condition attributes in a consistent decision system, a sufficient condition is proposed to judge whether the positive regions of them with respect to the decision attribute are equal.
Measuring the effect of transaction costs for investment in irrigation pumps: application of the unobserved stochastic threshold model to the case of Nigeria.

Small-scale private irrigation schemes (SPRI) have been the driving force behind the expansion of irrigated areas in Nigeria, despite government efforts to promote large-scale public irrigation schemes. SPRI allows adjustment of irrigation schedules in accordance with observed crop needs. The irrigated area in Nigeria is, however, far below its potential and an increase in farmersi? ½ investment in irrigation is essential. While Nigerian farmersi? ½ low level of investment in irrigation may be partly due to low returns, it is also the result of high transaction costs associated specifically with making such an investment. Although reducing transaction costs is important because the reduction provides farmers with a more enabling environment, transaction costs are often unobservable and little is known about what factors contribute to them. This article empirically assesses the effect of unobserved transaction costs for Nigerian farmersi? ½ when investing in irrigation pumps, using the baseline survey data for the Second Fadama Development Program (Fadama II). The results indicate that the unobserved transaction costs are higher for female landless farmers, with higher dependency ratio and residing far from town. The results suggest that the unobserved transaction costs can be as important as the factors determining the profitability of irrigation pump, emphasizing the importance of reducing transaction costs in addition to improving the environment for higher return from irrigation investment.
Mapping quantal touch using 7 Tesla functional magnetic resonance imaging and single-unit intraneural microstimulation

Using ultra-high field 7 Tesla (7T) functional magnetic resonance imaging (fMRI), we map the cortical and perceptual responses elicited by intraneural microstimulation (INMS) of single mechanoreceptive afferent units in the median nerve, in humans. Activations are compared to those produced by applying vibrotactile stimulation to the unit’s receptive field, and unit-type perceptual reports are analyzed. We show that INMS and vibrotactile stimulation engage overlapping areas within the topographically appropriate digit representation in the primary somatosensory cortex. Additional brain regions in bilateral secondary somatosensory cortex, premotor cortex, primary motor cortex, insula and posterior parietal cortex, as well as in contralateral prefrontal cortex are also shown to be activated in response to INMS. The combination of INMS and 7T fMRI opens up an unprecedented opportunity to bridge the gap between first-order mechanoreceptive afferent input codes and their spatial, dynamic and perceptual representations in human cortex. DOI: http://dx.doi. org/10.7554/eLife.12812. 001
Session variability in Automatic Speaker Verification

This paper explores the use of mismatch condition in speaker variability applied to Automatic Speaker Verification (ASV) defined as a classification task to decide whether a proclaimed identity is true or not. This paper proposes to model mismatch conditions in speaker variability from session to another. It was shown that the speaker recognition accuracy deteriorates when there is an acoustic mismatch between the speech obtained during training and testing. The target speakers are modeled using vector quantization (VQ) approach based on multiples session codebooks, and then compared it to baseline vector quantization. The present study demonstrates that the session variability for target speaker improve the performance of ASV system and the several codebooks for target speaker (set of session codebooks) give better results. The performance of these models is evaluated on the Arabic speaker verification dataset.
Divide and Conquer : A Mixture-Based Approach to Regional Adaptation for MCMC

The efficiency of Markov chain Monte Carlo (MCMC) algorithms can vary dramatically with the choice of simulation parameters. Adaptive MCMC (AMCMC) algorithms allow the automatic tuning of the parameters while the simulation is in progress. A multimodal target distribution may call for regional adaptation of Metropolis-Hastings samplers so that the proposal distribution varies across regions in a partition of the sample space. Establishing such a partition is not straightforward and, in many instances, the learning required for its specification takes place gradually, as the simulation proceeds. In the case in which the target distribution is approximated by a mixture of Gaussians, we propose an adaptation process which involves fitting the mixture using the available samples via an online EM algorithm and, based on the current mixture parameters, constructing the regional adaptive algorithm with online recursion (RAPTOR). The method is compared with other regional AMCMC samplers and is tested on simulated as well as real data examples.
The Impact of Evolutionary Driving Forces on Human Complex Diseases: A Population Genetics Approach

Investigating the molecular evolution of human genome has paved the way to understand genetic adaptation of humans to the environmental changes and corresponding complex diseases. In this review, we discussed the historical origin of genetic diversity among human populations, the evolutionary driving forces that can affect genetic diversity among populations, and the effects of human movement into new environments and gene flow on population genetic diversity. Furthermore, we presented the role of natural selection on genetic diversity and complex diseases. Then we reviewed the disadvantageous consequences of historical selection events in modern time and their relation to the development of complex diseases. In addition, we discussed the effect of consanguinity on the incidence of complex diseases in human populations. Finally, we presented the latest information about the role of ancient genes acquired from interbreeding with ancient hominids in the development of complex diseases.
Multibiometric Database Retrieval Method Based on Index Code

— Multibiometrics use of multiple biometric sources for human recognition, mitigates some of the limitations of unimodal biometric systems by increasing recognition accuracy, imparting fault-tolerance, and enhancing security. These databases are used extensively, thereby requirement of efficient technique for searching and retrieving relevant identities from large biometric database. Searching out a biometric information for associate degree identity is usually done by comparing the probe(input) image against every stored identity in the database and generating a ranked list of candidate identities. thorough matching against an large range of identities will increase the latency of the system and should additionally reduce the accuracy of identification. index code is obtained by computing match scores between a biometric input images and fixed set of reference images. Candidate identities are retrieved supported the similarity between the index code of the probe image and people of the identities within the info. we have propose a technique for generating fixed-length codes for classification biometric databases . The proposed technique is extended to retrieve pertinent identities from multimodal databases. New representation schemes that allow quicker search and, therefore, shorter response time are required.
Summarizing Control Flow of Callbacks for Android API Methods

Ensuring the reliability and security of Android apps is important considering the large Android market and the critical usage of Android apps. To analyze and test Android apps, we need to know program paths, i.e., the control flow of callbacks implemented in the apps. One of the challenges to identify such information is the extensive use of the Android API methods in the apps. These methods can invoke multiple callbacks, and the control flow of these callbacks is context-sensitive in that different callback sequences may be invoked at different API call sites. To address the challenge, in this paper, we design a summary representation for an Android API method that aims to capture the control flow of callbacks in the API methods as well as the conditions under which the callbacks are invoked. We developed a static demand-driven analysis to automatically generate such summaries. To show the usefulness of the summaries, we construct the apps’ control flow graphs (CFGs) and apply infeasible path detection on the CFGs. Our experiments show that we are able to generate the API summaries that are compact and reusable, and by replacing the API calls with the summaries we generated, we obtained the apps’ CFGs with paths up to 10 callbacks for a set of Android apps under study. Comparing to the dynamic traces generated, we verified that such paths contain valid callback sequences. The API summaries and the CFGs of the apps computed for this work are all available at: http: //www.cs. iastate.edu/~weile/research/lithium.html
Emerging Memory Technologies

The six articles in this special section focus on emerging memory technologies. Technology scaling of traditional memory technologies, such as SRAM and DRAM, is increasingly constrained by fundamental technology limits. The recent research progress of various emerging memory device technologies, such as three-dimensional integrated memory, phase-change RAM, spin-transfer-torque magnetoresistive RAM, and resistive RAM, has drawn tremendous attentions from both academy and industry. These technologies bring many research opportunities and challenges for novel architectures, systems, applications, design tools, compilers, and programming models and languages. As these emerging memory technologies are maturing, it is important for us to understand their pros and cons for improving the performance, power, reliability, and scalability of future computer systems.
Psychiatric disease as a risk factor in fast-track hip and knee replacement

Abstract Recent studies suggest that patients with psychiatric disorders tend to do worse than patients without a psychiatric diagnosis when undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA). Whether this is due to their psychiatric condition, pharmacological treatment, a combination of the two, or something else has not been thoroughly analyzed—and there are no internationally accepted guidelines for perioperative management of psychiatric patients. This overview summarizes our current knowledge on perioperative risks in patients with preoperative psychiatric disorders and the possible role of psychotropic drugs in the perioperative course. This will be useful when planning future strategies for improvement of surgical outcome following hip and knee arthroplasty.
Development and Validation of the Post-Dissolution Relational Communication Index

ABSTRACT Relational dissolution is a distressing life event. Dissolution is further complicated when communication between ex-partners is inefficient, unpredictable, and strained. This examination uncovers the aspects of postdissolutional communication in a 2-part study. In Study 1, 271 participants experiencing a breakup completed surveys regarding their communication with an ex-romantic partner. The study empirically operationalizes these behaviors in the Post-Dissolution Relational Communication Index and reports on the factor structure, reliability, and convergent validity of the 2-factor solution produced. Both factors were significantly correlated with participants’ reports of communication satisfaction with a former relationship partner and the perceived seriousness of the relationship. In Study 2, self-reports from 151 participants who had experienced a divorce provided support for its use with divorced couples. A third factor was identified illustrating differences between nonmarital and marital ex-partners. Implications for postdissolution relationships and satisfaction with former partners are addressed. Furthermore, suggestions for practice are discussed.
An Effective Framework for Chinese Syntactic Parsing

This paper presents an effective framework for Chinese syntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsing algorithm, and integrates the idea of the beam search strategy of N best algorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally, the contrasting experiment results are given. Keywords—syntactic parsing, PCFG, pruning, evaluation model.