Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic-Based Recommendation Across Heterogeneous Domains

Cross-domain recommendation has attracted wide research interest which generally aims at improving the recommendation performance by alleviating the cold start problem in collaborative filtering based recommendation or generating a more comprehensive user profiles from multiple domains. In most previous cross-domain recommendation settings, explicit or implicit relationships can be easily established across different domains. However, many real applications belong to a more challenging setting: recommendation across heterogeneous domains without explicit relationships, where neither explicit user-item relations nor overlapping features exist between different domains. In this new setting, we need to (1) enrich the sparse data to characterize users or items and (2) bridge the gap caused by the heterogenous features in different domains. To overcome the first challenge, we proposed an optimized local tag propagation algorithm to generate descriptive tags for user profiling. For the second challenge, we proposed a semantic relatedness metric by mapping the heterogenous features onto their concept space derived from online encyclopedias. We conducted extensive experiments on two real datasets to justify the effectiveness of our solution.
Experiments on Unsupervised Chinese Word Segmentation and Classification

There are several problems encountered for Chinese language processing as Chinese is written without word delimiters. The difficulty in defining a word makes it even harder. This paper explores the possibility of automatically segmenting Chinese character sequences into words and classifying these words through distributional analysis in contrast with the usual approaches that depends on dictionaries.
An efficient scalar multiplication algorithm for ECC in WSNs

Wireless sensor networks (WSNs) facilitate real time monitoring in many commercial and military surveillance applications. These applications automatically call for a high level of security in such networks. Public key cryptographic (PKC) techniques such as Elliptic Curve Cryptography (ECC) provide a flexible interface to ensure security, requiring no pre-distribution of keys. However, ECC is very compute-intensive, owing to the computationally complex elliptic curve point multiplication operation. This work presents a technique to speed up the elliptic curve point multiplication operation, achieving a cost reduction of about 48% over the double and add algorithm and about 40% over the width-w Non Adjacent Form (NAF) algorithm. Additionally, results of its software implementation are presented.
Multiple Intelligences and Motivational Orientations in Learning EFL

The main purpose of this study is to determine the dominant types of multiple intelligences and motivational orientations of students in learning English as a Foreign Language (EFL). To achieve this objective, two research tools were used namely, survey questionnaire and focused group discussion (FGD). For quantitative data, the researcher used a standardized Multiple Intelligences Inventory by Walter McKenzie (1999) and a questionnaire on Motivational Orientations in Learning EFL. For qualitative data, FGD sessions with selected AMAIUB students were conducted. The participants of the study were 165 AMA International University-Bahrain (AMAIUB) students for the Academic Year 2011-2012 and were categorized according to sex and programme enrolled. Results of the study revealed that the dominant types of intelligences of AMAIUB students are existential, bodily-kinesthetic, and intrapersonal. When grouped as to programme enrolled, the Business Informatics, International Studies, and Informatics Engineering students have existential; Mechanical Engineering students have visual-spatial; Computer Science students have intrapersonal and the Medicine students have naturalistic. When grouped as to sex, male students’ dominant types of intelligences are existential, intrapersonal, and bodily-kinesthetic while female students have existential, bodily-kinesthetic, and intrapersonal. Further, results showed that AMAIUB students have the integrative or intrinsic motivational orientation in learning EFL. When grouped as to sex, both male and female students have integrative or intrinsic motivational orientation in learning EFL. As to their programme enrolled, Business Informatics, International Studies, Mechatronics Engineering, and Computer Science students have integrative or intrinsic motivational orientation in learning EFL while the Informatics Engineering students have instrumental or extrinsic. The Medicine students have both integrative and instrumental orientations. As ascertained in this study, there were no significant differences on the students’ types of intelligences when grouped as to sex. However, a significant difference in the types of intelligence was found when the students are categorized as to the programme enrolled, specifically, on the Naturalist type of intelligence between the Medicine and Computer Science and International Studies students. Moreover, there were no significant differences on the students’ motivational orientations in learning EFL when they were grouped as to programme enrolled and sex. In the basis of the findings, the following conclusions were drawn: Sex is not a correlate of the types of multiple intelligences. Programme enrolled is a significant determinant of the types multiple of intelligences. Sex does not affect the motivational orientations in learning EFL. Programme enrolled does not affect the motivational orientations in learning EFL. Keywords: Multiple Intelligences, EFL, Motivational Orientations in Learning in English
Performance Evaluation of Parallel S-Trees

The S-tree is a dynamic height-balanced tree similar in structure to B+trees. S-trees store fixed length bit-strings, which are called signatures. Signatures are used for indexing textbases, relational, object oriented and extensible databases as well as in data mining. In this article, methods of designing multi-disk B-trees are adapted to S-trees and new methods of parallelizing S-trees are developed. The resulting structures aim at achieving performance gain by accessing two or more disks simultaneously. In addition, two different searching techniques that exploit parallel disk accessing are devised. Performance results of experiments based on the new structures and searching techniques are also presented and discussed.
Shannon and Hubbard Were Friends? Provocations in Creative Browsing and Friends in Scholarly Discord

On the face of it, the idea of Claude Shannon and L. Ron Hubbard being friends in any sense seems nearly preposterous. One the father of Information Science as a discipline that had deep impact on communication and much of the fundamental infrastructure of modern life; the other a college drop out of some literary talent who founded a religion with a bizarre hagiographic narrative. Yet, there is a letter from Shannon to Warren McCulloch with the phrase “I am writing on behalf of a friend L. Ron Hubbard. ” What are we to make of such a line?
Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme (GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to-patient variability in GBM dynamics and responsiveness to therapy. Using computational models that account for the unique geometry and kinetics of individual patients' tumors, we developed a method for assessing treatment response that discriminates progression-free and overall survival following therapy for GBM. Applying these models as untreated virtual controls, we generate a patient-specific “Days Gained” response metric that estimates the number of days a therapy delayed imageable tumor progression. We assessed treatment response in terms of Days Gained scores for 33 patients at the time of their first MRI scan following first-line radiation therapy. Based on Kaplan-Meier analyses, patients with Days Gained scores of 100 or more had improved progression-free survival, and patients with scores of 117 or more had improved overall survival. Our results demonstrate that the Days Gained response metric calculated at the routinely acquired first post-radiation treatment time point provides prognostic information regarding progression and survival outcomes. Applied prospectively, our model-based approach has the potential to improve GBM treatment by accounting for patient-to-patient heterogeneity in GBM dynamics and responses to therapy.
Applying Artificial Neural Networks for analysis of geotechnical problems

The paper presents a discussion of some applications of Artificial Neural Networks (ANNs) in geo-engineering using the analysis of the following six geotechnical problems, related mainly to prediction and classification purposes: 1) prediction of Overconsolidation Ratio (OCR), 2) determination of potential soil liquefaction, 3) prediction of foundation settlement, 4) evaluation of piles bearing capacity, 5) prediction of compaction parameters for cohesive soils, 6) compaction control of embankments built of cohesionless soils. The problems presented are based on the applications of the Multi-Layered Perceptron (MLP) neural networks.
Chandra Observation of Luminous and Ultraluminous X-Ray Binaries in M101

X-ray binaries in the Milky Way are among the brightest objects in the X-ray sky. With the increasing sensitivity of recent missions, it is now possible to study X-ray binaries in nearby galaxies. We present data on six luminous sources in the nearby spiral galaxy M101 obtained with the Chandra ACIS-S. Of these, five appear to be similar to ultraluminous sources in other galaxies, while the brightest source, P098, shows some unique characteristics. We present our interpretation of the data in terms of an optically thick outflow and discuss implications.
Production-guided concurrency debugging

Concurrency bugs that stem from schedule-dependent branches are hard to understand and debug, because their root causes imply not only different event orderings, but also changes in the control-flow between failing and non-failing executions. We present Cortex: a system that helps exposing and understanding concurrency bugs that result from schedule-dependent branches, without relying on information from failing executions. Cortex preemptively exposes failing executions by perturbing the order of events and control-flow behavior in non-failing schedules from production runs of a program. By leveraging this information from production runs, Cortex synthesizes executions to guide the search for failing schedules. Production-guided search helps cope with the large execution search space by targeting failing executions that are similar to observed non-failing executions. Evaluation on popular benchmarks shows that Cortex is able to expose failing schedules with only a few perturbations to non-failing executions, and takes a practical amount of time.
A Schematic Analysis on Selective-RDF Database Stores

RDF has gained great interest in both academia and industry as an important language to describe graph data. With the increasing amount of RDF data which is becoming available, efficient and scalable nowadays has become a challenge to achieve the semantic web vision. The RDF model has attracted the attention of the database community and researchers to propose various methods to store and query the RDF data efficiently. However, current RDF database suffer from several problems, like, poor performance behavior for querying RDF data. This paper provides a comparative analysis made on selective RDF databases storages. It provides a precise study on the various means of having a persistent storage and access of RDF graphs. Recently there has been a major development on initiatives in query processing, access protocols and triple-store technologies. In the evaluation the use of a nonmemory and a non-native store Sesame, a native store Allegro graph and Jena API a main-memory based RDF storage system, specifically designed to support fast semantic association discovery. The framework and applications with the ability to store and to query RDF data are analyzed and investigated. Moreover, this paper gives an overview of the features of techniques for storing RDF data and the main purpose of study is to find suitable storage system to store RDF data.
Assessment of electrocardiography, echocardiography, and heart rate variability in dynamic and static type athletes

Background: Over the last two decades, morphological cardiac changes induced by athletic conditioning have been of great interest. Therefore, several studies have been orchestrated to delineate electrocardiography (ECG), echocardiography, and heart rate variability (HRV) findings in athletes. Purpose: To assess the ECG, echocardiography, and HRV in a group of dynamic and static type athletes. Methods: Fifty professional athletes (20 static and 30 dynamic exercise athletes) and 50 healthy nonathletes (control group) were recruited. Standard 12-lead ECG and transthoracic echocardiography was performed on all athletes and the control group. Through echocardiography, variables including left ventricular (LV) end-diastolic/systolic diameter, LV mass, and left atrial volume index were measured. In addition, both the athletes and the control group underwent ECG Holter monitoring for 15 minutes and several parameters related to HRV (time and frequency domain) were recorded. Results: The most common ECG abnormalities among the athletes were sinus bradycardia and incomplete right bundle branch block. LV end-diastolic diameter and left atrial volume index were significantly greater in the dynamic athletes (P < 0.001). LV end-systolic diameter was significantly lower in the static group (P < 0.001). LV mass of the dynamic and static athletes was significantly greater than that of the controls (P < 0.001). Among the ECG Holter monitoring findings, the dynamic athletes had lower systolic blood pressure than the controls (P = 0.01). Heart rate was lowest in the control group (P < 0.001). Conclusion: The most common ECG abnormalities among adolescent Iranian athletes were sinus bradycardia and incomplete right bundle branch block. Static exercise seemed to reduce LV end-systolic diameter, while dynamic exercise resulted in increased LV end-diastolic diameter and left atrial volume index. Additionally, Iranian athletes showed no differences in HRV parameters, excluding heart rate and systolic blood pressure, compared with the nonathletes.
The clinical significance of aldosterone in ESRD: Part II.

Sir, I would like to thank Lars Weiss for his interesting comments regarding my Editorial Comment [1] from over a year ago! However, I do have some difficulty accepting one or two of his arguments. While one cannot completely exclude the possibility of different pharmacodynamics between epoetin alfa and epoetin beta, I feel it is unlikely that a difference in intravenous (i.v.) half-life of 6.8±2.7 h for i.v. epoetin alfa and 8.8±2.2 h for i.v. epoetin beta, along with 19.4±10.7 h for subcutaneous (s.c.) epoetin alfa and 24.2±11.2 h for s.c. epoetin beta [2] can really make a substantial difference to biological activity. There may be other differences between epoetin alfa and epoetin beta previously unrecognized, but it would be surprising if such subtle differences in pharmacokinetics in a study conducted in healthy volunteers translated into an enhanced clinical efficacy. However, I do accept completely Weiss’s comment that inclusion criteria including only iron-replete and welldialysed patients should be ‘regarded as standard in trials of dialysis patients’. As I said in my Editorial Comment [1], and in a follow-up Reply Letter [3], it is always difficult to extrapolate results from scientific studies into everyday clinical practice. While one cannot criticize the inclusion criteria in either the Swedish [4] or Italian [5] studies, the experience of Jones et al. [6] and Geddes and Woo [7] testify to this. I also disagree with Weiss’s comment that a Kt/V of >1 and a ferritin level of >200mg/l are the ‘norm’ in dialysis units; I accept the unpublished data from the Swedish Society of Nephrology, but it is well known that Sweden boasts some of the best results in renal anaemia management in Europe (as reported in the ESAM survey [8]), and the experience in other countries in Europe falls far short of the results that Weiss quotes. Thus, I still feel that we should be cautious about extrapolating results from wellcontrolled clinical trials into everyday clinical practice in our dialysis units. Finally, although half-lives aren’t everything, before getting too excited about a possible difference between 19.4 and 24.2 h for s.c. administration of epoetin alfa and epoetin beta, respectively, one should not forget that the half-life for s.c. darbepoetin alfa is substantially greater at 48.8±12.7 h [9].
Reading Out Visual Information from Populations of Neurons in Inferior Temporal and Prefrontal Cortex

The ability of primates to recognize visual objects is believed to be based on a series of transformations of visual information that occur as signals travel down the ventral pathway from primary visual cortex (V1) through inferior temporal cortex (IT) and ultimately on to prefrontal cortex (PFC) where decision making circuitry is believed to reside. Thus, a key component to understanding how object recognition occurs is to determine how visual information is represented in these different cortical areas, as well as how these representations change with time in the course of recognizing an object.
A Genetic Algorithm for Constrained Statistical Matching

Constrained statistical matching is a process of merging record instances between two source files such that no record instance would be used in a match more than once and that the overall distance cost of all record-pairs (matches) is minimized. This study presents a Genetic Algorithm (GA) as an alternative to a greedy algorithm of record linkage performed by sequentially finding the cheapest match for every record in one file with any of the remaining unmatched records in the other. The GA, designed initially as a solution to a special case of Linear Transportation Problem of Operations Research, used an adjacency list as a chromosomal representation, a population size of 40, a 90% selection probability, and a 50% crossover and mutation probabilities combined. The resulting computer programs were made to run on varying problem sizes mostly to verify GA’s convergence to possibly global minimum -cost solution, and empirical results confirmed its ability in obtaining, under certain conditions, the global minimum, a situation that can not be arrived at via a straight-forward greedy algorithm. In all cases, however, GA – which entails creation and maintenance of a set of solutions (populations) per iteration – showed slower performance compared with greedy algorithm as the number of records to match is increased significantly. Finally, the strengths of both algorithms were combined experimentally, resulting to better performance and quality of solution, and the test results showed that the matching costs found by greedy algorithm w ere reduced significantly by a GA that use seeding process via a greedy heuristic, i.e. from 411 down to 375, 541 to 496, 680 down to 627, and 15379 to 15156, for record sizes 100x300, 150x450, 200x600, and 19195x39615, respectively. Hence, this investigation provides compelling evidence of GA’s ability to find near-optimal solution, which cannot be obtained by traditional greedy search algorithm.
Handling Expiration of Multigranular Temporal Objects

A well-known problem of temporal databases is that the amount of stored data tends to increase very fast. Moreover, detailed data are useful when they are acquired but they often become less relevant after some time. In most cases, after a period of time only summarized data need to be kept, whereas detailed data expire and can be removed from the database. Multigranular temporal databases enhance the expressive power of temporal databases by supporting temporal attributes at different levels of detail. However, in existing approaches the level of detail of an attribute, that is its granularity, depends only on the attribute semantics and does not depend on how recent the attribute values are. This paper proposes an approach supporting the aggregation of different portions of the value of a temporal attribute at different levels of detail, and the deletion or the transfer to tertiary storage of old values at a given level of detail, in order to minimize disk storage occupancy. In the proposed multigranular temporal object-oriented data model, the expiration of attribute values at a given granularity can be specified, together with the action to take when data expire: either aggregation to a coarser granularity, or deletion of values, or both.
Robust speaker recognition using microphone arrays

This paper investigates the use of microphone arrays in handsfree speaker recognition systems. Hands-free operation is preferable in many potential speaker recognition applications, however obtaining acceptable performance with a single distant microphone is problematic in real noise conditions. A possible solution to this problem is the use of microphone arrays, which have the capacity to enhance a signal based purely on knowledge of its direction of arrival. The use of microphone arrays for improving the robustness of speech recognition systems has been studied in recent times, however little research has been conducted in the area of speaker recognition. This paper discusses the application of microphone arrays to speaker recognition applications, and presents an experimental evaluation of a hands-free speaker verification application in noisy conditions.
Towards Model-Driven Engineering Support for Service Evolution

In the field of Service-Oriented Architecture (SOA) evolution is a key issue given the non-trivial nature of updating widely distributed and heterogeneous systems. With this in mind, in this work we used some of the technologies developed in the context of the Eclipse Modeling Framework (EMF) to provide a proof of concept of the possible synergy between Model-Driven Engineering (MDE) and Service Orientation. In particular, we present a DSL toolkit for modeling the structural part of Abstract Service Descriptions (ASDs) and the reasoning mechanism that assesses whether two versions of a service are compatible with respect to its consumers.
Symmetrical Color-Spatial Feature for Medical Image Retrieval

Color feature of an image is one of the most common used features in content-based image retrieval (CBIR) systems. Combining the traditional colorhistogram with some spatial information will greatly increase the accuracy of color features. One advantage of color feature is that it is independent to the distortion of an image. However, with the introduction of the spatial information, this advantage will disappear. In this paper, we proposed a new symmetrical color-spatial method based on square loop. Experiment results show that the method has good performance when 90 or 180 degree rotation and flip. Its good efficiency makes it suitable for large numbers of images retrieval.