Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced security for multi-cloud storage using cryptographic data splitting with dynamic approach

The use of cloud computing has increased rapidly in many organizations. Security is considered to be the most critical aspects in a cloud computing environment due to the sensitive information stored in the cloud for users. The goal of cloud security is mainly focused on the issues related to the data security and privacy aspects in cloud computing. This multi cloud model which is based on partitioning of application system into distinct clouds instead of using single cloud service such as in Amazon cloud service. It will discuss and present the cryptographic data splitting with dynamic approach for securing information. The metadata information is stored in private cloud. This approach prevents the unauthorized data retrieval by hackers and intruders. The results and implementation for the new proposed model is analyzed, in relation to addressing the security factors in cloud computing.
‘What’s all the fuss about play’? Expanding student teachers’ beliefs and understandings of play as pedagogy in practice

ABSTRACT In an attempt to resolve some of the lingering tensions involved in understanding play as learning in practice, a group of Irish student teachers in the final years of their degree programme participated in an intervention known as ‘PLAI’ (Playful Learning Across Ireland). This paper reports on the impact of such an intervention on student teachers’ beliefs and practices about playful learning, drawing on evidence gleaned from a pre- and post-questionnaire survey and qualitatively rich reflective practice diaries. The findings highlight how the student teachers shifted their perceptions from a mere acceptance that all play has value to a greater critical and more expansive appreciation of playing as learning and teaching. In addition, they seemed to have become more conscious of the inherent complexities involved in implementing such a pedagogical approach effectively, suggesting that there is a definite need for play to be ‘fussed’ about in the early years classroom.
Sketch Recognition with Natural Correction and Editing

In this paper, we target at the problem of sketch recognition. We systematically study how to incorporate users' correction and editing into isolated and full sketch recognition. This is a natural and necessary interaction in real systems such as Visio where very similar shapes exist. First, a novel algorithm is proposed to mine the prior shape knowledge for three editing modes. Second, to differentiate visually similar shapes, a novel symbol recognition algorithm is introduced by leveraging the learnt shape knowledge. Then, a novel editing detection algorithm is proposed to facilitate symbol recognition. Furthermore, both of the symbol recognizer and the editing detector are systematically incorporated into the full sketch recognition. Finally, based on the proposed algorithms, a real-time sketch recognition system is built to recognize hand-drawn flowcharts and diagrams with flexible interactions. Extensive experiments show the effectiveness of the proposed algorithms.
A WEB-BASED TOOLKIT FOR LARGE-SCALE ONTOLOGIES

There is no doubt that those large-scale domain ontologies are playing a critical role in building a large variety of semantic-based systems. It’s important and urgent to share and reuse large-scale ontologies to support semantic-based applications in a more efficient way. In this paper, we propose a web-based toolkit for building and reusing large-scale ontologies. The toolkit consists of a web-based ontology editor as well as a modulation-based API for ontology reuse. The web-based ontology editor supports cooperative online development of large-scale ontologies. It distinguishes itself from other editors by an easy-to-use interface. A modulation-based API is implemented for manipulating modulation from large-scale ontologies. It makes it possible to extract frequently-used portions from large-scale ontologies and cache those portions of knowledge in database for potential reuse. Moreover, we have evaluated the performance of the toolkit by simulation and application. In summary, the proposed toolkit is able to support building and reusing large-scale ontologies.
Using a custom Ciona intestinalis genome browser to visualize genomic conservation with Ciona savignyi

We have successfully designed a custom genome browser for visualization of the genome of the invertebrate chordate Ciona intestinalis. We describe the use of the genome browser to visualize the conservation between Ciona intestinalis and a related species, Ciona savignyi. Visualizing genomic conservation between these two organisms is important for determining genes and regulatory regions that differ between these closely related species. We also describe the use of our genome browser in verifying 3UTR predictions for gene targets of an important regulatory molecule called microRNA-124.
Designing Interactions with Multilevel Auditory Displays in Mobile Audio-Augmented Reality

Auditory interfaces offer a solution to the problem of effective eyes-free mobile interactions. In this article, we investigate the use of multilevel auditory displays to enable eyes-free mobile interaction with indoor location-based information in non-guided audio-augmented environments. A top-level exocentric sonification layer advertises information in a gallery-like space. A secondary interactive layer is used to evaluate three different conditions that varied in the presentation (sequential versus simultaneous) and spatialisation (non-spatialised versus egocentric/exocentric spatialisation) of multiple auditory sources. Our findings show that (1) participants spent significantly more time interacting with spatialised displays; (2) using the same design for primary and interactive secondary display (simultaneous exocentric) showed a negative impact on the user experience, an increase in workload and substantially increased participant movement; and (3) the other spatial interactive secondary display designs (simultaneous egocentric, sequential egocentric, and sequential exocentric) showed an increase in time spent stationary but no negative impact on the user experience, suggesting a more exploratory experience. A follow-up qualitative and quantitative analysis of user behaviour support these conclusions. These results provide practical guidelines for designing effective eyes-free interactions for far richer auditory soundscapes.
Di!using acoustic wave spectroscopy of #uidized suspensions

The velocity #uctuations and local strain rate in a #uidized suspension of particles are investigated using the new ultrasonic technique of di! using acoustic wave spectroscopy. DAWS probes the relative motion of the particles at very short length scales down to the inter-particle separation, and allows the spatial correlations of the velocity #uctuations to be probed by varying the transport mean free path of the di! using ultrasonic waves. Our results demonstrate the power of this ultrasonic technique to probe the dynamics of sedimenting particles at larger length scales and Reynolds numbers than can be achieved by light scattering methods. ( 2000 Elsevier Science B.V. All rights reserved.
The QRQW PRAM: accounting for contention in parallel algorithms

We introduce the queue-read, queue-write (QRQW) PRAM model, which permits concurrent reading and writing, but at a cost proportional to the number of readers/writers to a memory location in a given step. Previously, there were no formal complexity models that accounted for the contention to memory locations, despite the large impact of such contentions on the performance of parallel prdgrams. The QRQW PRAM is strictly more powerful than the EREW PRAM. We show a separation of fi between the two models, and present faster and more efficient QRQW algorithms for many basic problems. Nevertheless, we show that the QRQW can be efficiently emulated with only logarithmic slowdown on Valiant’s BSP model, and hence on hypercube-type non-combining networks, even when latency, synchronization, and memory granularity overheads are taken into account. In contrast, efficient emulations for the CRCW PRAM on such networks are only known with polynomial slowdown. Most existing machines obey the queue-read, queue-write rule. We study the impact of the QRQW rule on algorithm design, devising new techniques for low-contention algorithms. Our results include fast and efficient algorithms for computing the OR, leader election, linear compaction, multiple compaction, integer sorting, and CRCW simulation, as well as several lower bounds. Some of the results presented are quite involved and use several novel ideas and techniques that are interesting on their own.
THE ANALYSIS OF BIASES OF COPY NUMBERS FROM AFFYMETRIX SNP ARRAYS

Affymetrix SNP arrays are widely used for both genome-wide association and copy number variation (CNV) studies, both of which depend on accurate copy number estimation. However, depending on the method used to copy number estimation, distortions from the actual copy numbers can occur. Therefore, we demonstrate here several effects that can bias accurate copy number estimation, and we describe how some of these biases can be adjusted by existing methods, while others require further study.
Impact of rising CO2 on emissions of volatile organic compounds: isoprene emission from Phragmites australis growing at elevated CO2 in a natural carbon dioxide spring†

Isoprene basal emission (the emission of isoprene from leaves exposed to a light intensity of 1000 m mol m - 2 s - 1 and maintained at a temperature of 30 ∞ ∞ ∞ C) was measured in Phragmites australis plants growing under elevated CO 2 in the Bossoleto CO 2 spring at Rapolano Terme, Italy, and under ambient CO 2 at a nearby control site. Gas exchange and biochemical measurements were concurrently taken. Isoprene emission was lower in the plants growing at ele- vated CO 2 than in those growing at ambient CO 2 . Isoprene emission and isoprene synthase activity (IsoS) were very low in plants growing at the bottom of the spring under very rich CO 2 and increased at increasing distance from the spring (and decreasing CO 2 concentration). Distance from the spring did not significantly affect photosynthesis mak- ing it therefore unlikely that there is carbon limitation to isoprene formation. The isoprene emission rate was very quickly reduced after rapid switches from elevated to ambi- ent CO 2 in the gas-exchange cuvette, whereas it increased when switching from ambient to elevated CO 2 . The rapidity of the response may be consistent with post-translational modifications of enzymes in the biosynthetic pathway of isoprene formation. Reduction of IsoS activity is inter- preted as a long-term response. Basal emission of isoprene was not constant over the day but showed a diurnal course opposite to photosynthesis, with a peak during the hottest hours of the day, independent of stomatal conductance and probably dependent on external air temperature or tempo- rary reduction of CO 2 concentration. The present experi- ments show that basal emission rate of isoprene is likely to be reduced under future elevated CO 2 levels and allow improvement in the modelling of future isoprene emission rates.
Self-charging of the Eyjafjallajökull volcanic ash plume

Volcanic plumes generate lightning from the electrification of plume particles. Volcanic plume charging at over 1200 km from its source was observed from in situ balloon sampling of the April 2010 Eyjafjallajökull plume over Scotland. Whilst upper and lower edge charging of a horizontal plume is expected from fair weather atmospheric electricity, the plume over Scotland showed sustained positive charge well beneath the upper plume edge. At these distances from the source, the charging cannot be a remnant of the eruption itself because of charge relaxation in the finite conductivity of atmospheric air.
Contextual Method for the Redesign of Existing Software Products

Abstract This article is concerned with the problem of improving software products and investigates how to base that process on solid empirical foundations. Our key contribution is a contextual method that provides a means of identifying new features to support discovered and currently unsupported ways of working and a means of evaluating the usefulness of proposed features. Standard methods of discovery and evaluation, such as interviews and usability testing, gather some of the necessary data but fall short of covering important aspects. The shortcomings of these approaches are overcome by applying an integrated and iterative method for collecting and interpreting data about product usage in context. This article demonstrates its effectiveness when applied to the discovery and evaluation of new features for standard Web clients.
CORE: centrally optimized routing extensions for the IEEE 802.16 MeSH mode

The IEEE 802.16 standard specifies a MeSH mode which permits the deployment of Wireless Mesh Networks (WMNs) supporting carrier-grade QoS. The network operator for such planned WMNs is interested in maximizing the traffic admitted in the WMN and simultaneously supporting QoS. Recently network coding has emerged as a promising technique for increasing the throughput in WMNs. This paper proposes CORE, which addresses the problem of jointly optimizing the routing, scheduling, and bandwidth savings via network coding. Prior solutions are either not applicable in the 802.16 MeSH or computationally too costly to be of practical use in the WMN under realistic scenarios. COREpsilas heuristics, in contrast, are able to compute solutions for the above problem within a operator definable maximum computational cost, thereby enabling the computation and near real-time deployment of the computed solutions. We analyze the performance of COREpsilas heuristics via a thorough simulation study covering the typical usage scenarios for WMNs. The results presented demonstrate that CORE is able to increase the number of flows admitted considerably and with minimal computational costs. Further, the results provide insights into limiting factors for the gains which can be obtained in different usage scenarios.
DESIGN & DEPLOYMENT OF TESTBED BASED ON ICMPv6 FLOODING ATTACK

One of the important protocols in IPv6 implementation is ICMPv6 which is used for neighbor and router discovery. However, this protocol also could be used by attackers to deny network services like ICMPv6 flood attacks which network decreases performance. In ICMPv6 flooding attacks detection, behavioural-based approaches, particularly suffer from the unavailability of the benchmark datasets. This can lead to the lack of precise results evaluation of ICMPv6flooding attack detection systems, comparison, and deployment, which originates from the deficiency of adequate datasets. Most of the datasets in the IPv6 field are from local environment and cannot be used on a large scale due to privacy problems and do not reflect common trends. They also lack some statistical features. Therefore, there is not any available benchmark dataset infected by ICMPv6-based foods for performing a Denial of Service (DoS) attacks against Web servers by using ICMPv6 flooding method. In addition, there is no Web access log infected by ICMPv6-based flood available for researchers. This paper presents the ICMPv6-based flooding attacks testbed to study the behaviour of ICMPv6 flooding attack as well as evaluating different solutions proposed for detecting ICMPv6-based flood of DoS attacks by various researchers
Acquiring Creative Requirements from the Crowd: Understanding the Influences of Personality and Creative Potential in Crowd RE

As a creative discipline, Requirements Engineering (RE), lends importance to understanding the associated human factors. Crowd RE, the approach of acquiring requirements from members of the public-the so-called crowd-emphasizes human factors further. We investigate how human personality and creative potential influence a requirement acquisition task. These factors are of specific importance to Crowd RE because (1) crowd workers are generally not trained in RE, and (2) a key motivation in engaging them is to benefit from their creativity. We propose a sequential Crowd RE process, where workers in one stage review requirements from the previous stage and produce additional requirements. To reduce potential information overload in this process, we propose strategies for selecting requirements from one stage to expose to workers in later stages. We conducted a study on Amazon Mechanical Turk tasking 300 workers with creating requirements via the above sequential process (in the domain of smart home applications for concreteness) and tasking an additional 300 workers to rate the creativity (novelty and usefulness) of those requirements. Our findings offer insights on how to carry out Crowd RE effectively. First, we find that a crowd worker's (1) creative potential, and personality traits of openness and conscientiousness have significant positive influence on the novelty of the worker's ideas, and (2) personality traits of agreeableness and conscientiousness have significant positive influence, but extraversion has significant negative influence on the usefulness of the worker's ideas. Second, we find that exposing a worker to ideas from previous workers cognitively stimulates the worker to produce creative ideas. Third, we identify effective strategies based on personality traits and creative potential for selecting a few requirements from a pool of previous requirements to stimulate a worker.
Applying feature selection to payload-based Web Application Firewalls

Web Application Firewalls (WAFs) analyze the HTTP traffic in order to protect Web applications from attacks. To be effective, WAFs need to analyze the payload of the packets. One of the techniques used for intrusion detection is to extract features from the payload by means of n-grams. An n-gram is a subsequence of n items from a given sequence. The number of n-grams is 256 to the nth power. Since it grows exponentially with n, the curse of dimensionality and computational complexity problem arise. In this paper we propose to apply feature selection in order to reduce the number of features extracted by n-grams and thus to improve the effectiveness of WAFs. We conduct experiments on our own HTTP data set. After extracting n-grams from this data set, we apply the Generic-Feature-Selection (GeFS) measure for intrusion detection [5] to select important features. We use four different classifiers to test the detection accuracy before and after feature selection. The experiments show that we can remove more than 95% of irrelevant and redundant features from the original data set (and thus improve the performance by more than 80% on average), while reducing only slightly (by less than 6%) the accuracy of WAFs.
Sentiment analysis for dialectical Arabic

This article investigates sentiment analysis in Arabic tweets with the presence of dialectical words. Sentiment analysis deals with extracting opinionated phrases from reviews, comments or tweets. i.e. to decide whether a given review or comment is positive, negative or neutral. Sentiment analysis has many applications and is very vital for many organizations. In this article, we utilize machine learning techniques to determine the polarity of tweets written in Arabic with the presence of dialects. Dialectical Arabic is abundantly present in social media and micro blogging channels. Dialectical Arabic presents challenges for topical classifications and for sentiment analysis. One example of such challenges is that stemming algorithms do not perform well with dialectical words. Another example is that dialectical Arabic uses an extended set of stopwords. In this research we introduce a framework that is capable of performing sentiment analysis on tweets written using either Modern Standard Arabic or Jordanian dialectical Arabic. The core of this framework is a dialect lexicon which maps dialectical words into their corresponding Modern Standard Arabic words. The experimentation reveals that the dialect lexicon improves the accuracies of the classifiers.
A network service providing wireless channel information for adaptive mobile applications. I. Proposal

We propose a network service that collects and processes PHY/MAC layer parameters for wireless channel conditions and provides them to adaptive mobile applications in clearly defined abstracted forms to aid them in their adaptation decision-making. This is to overcome one of the major hurdles in deploying powerful adaptive applications for mobile clients: lack of efficient access to wireless channel conditions. We put much of this burden on the proposed wireless channel information (WCI) service so that applications and OSs do not have to access and process wireless PHY/MAC layer parameters that are often specific to wireless interface technologies. This approach is very effective for the upcoming 3G wide-area networks. The WCI service is a network service provided by the wireless access network that communicates directly with adaptive mobile applications in the server network through standard protocols. The WCI service interfaces with various network elements in the wireless access network to collect parameters related to wireless channel conditions for a mobile device. Based on these parameters, the WCI service abstracts clearly defined values of parameters such as bandwidth and latency in formats that applications can use. These definitions are agreed or specified using RDF (resource description framework) or DTD (document type definition) using XML standards. These results are dynamically communicated to adaptive applications in a wired network to aid their adaptation decisions for mobile clients. A simple version of the WCI service has been implemented.
Copy number variations in 6q14.1 and 5q13.2 are associated with alcohol dependence.

BACKGROUND Excessive alcohol use is the third leading cause of preventable death and is highly correlated with alcohol dependence, a heritable phenotype. Many genetic factors for alcohol dependence have been found, but many remain unknown. In search of additional genetic factors, we examined the association between Diagnostic and StatisticalManual of Mental Disorders, Fourth Edition (DSM-IV) alcohol dependence and all common copy number variations (CNVs) with good reliability in the Study of Addiction: Genetics and Environment (SAGE). METHODS All participants in SAGE were interviewed using the Semi-Structured Assessment for the Genetics of Alcoholism, as a part of 3 contributing studies. A total of 2,610 non-Hispanic European American samples were genotyped on the Illumina Human 1M array. We performed CNV calling by CNVPartition, PennCNV, and QuantiSNP, and only CNVs identified by all 3 software programs were examined. Association was conducted with the CNV (as a deletion/duplication) as well as with probes in the CNV region. Quantitative polymerase chain reaction (qPCR) was used to validate the CNVs in the laboratory. RESULTS CNVs in 6q14.1 (p = 1.04 × 10(-6)) and 5q13.2 (p = 3.37 × 10(-4)) were significantly associated with alcohol dependence after adjusting multiple tests. On chromosome 5q13.2, there were multiple candidate genes previously associated with various neurological disorders. The region on chromosome 6q14.1 is a gene desert that has been associated with mental retardation and language delay. The CNV in 5q13.2 was validated, whereas only a component of the CNV on 6q14.1 was validated by qPCR. Thus, the CNV on 6q14.1 should be viewed with caution. CONCLUSIONS This is the first study to show an association between DSM-IV alcohol dependence and CNVs. CNVs in regions previously associated with neurological disorders may be associated with alcohol dependence.