Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data

– Significant hike in amount of data is observed in past couple of years. Now, it’s the era of Big Data, where Volume, Velocity & Variety are major components of data sets. This expansion in total data and its overall usage has inspired more to data owners to migrate their data sets to cloud. This migration is sort of outsourcing. Hence, data owners outsource their data management systems from local sites to commercial public cloud. Public cloud offers economic solutions to many problems observed and provides awesome flexibility to data owners. But as the responsibility of data owners has reduced, their risk for data security has increased proportionately. Data owners can enjoy full advantage of cloud computing only if they are able to address very real secrecy and security concerns that come with storing sensitive personal information. For real secrecy, user data and their identity should remain hidden from Cloud service provider (CSP) and to protect secrecy of data, it has be encrypted before outsourcing. This encrypted data is outsourced and blocks CSP from understanding the data. As the number of data users are significantly higher, feature for an encrypted cloud data search is of great importance. Also, by considering the large number of data users and documents in the cloud, it is also important for this search service to be capable to permit multi-keyword search query and should provide results similarity ranking to meet the effective need of data retrieval search and not often distinguish the search outcomes. In this system, we define and solve the challenging problem of secrecy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict secrecy requirements for such a secure cloud data utilization system to be implemented in real. We first propose a basic idea for the Multi-keyword Ranked Search over Encrypted cloud data (MRSE) [1]. It is based on two components, first Secure Inner Product Computation and efficient similarity measure of coordinate matching. It matches as many results as possible and captures relevance of data documents in response to the search query. Later we have explained two considerably improved MRSE schemes that accomplishes various stringent secrecy requirements [2] in two unlike threat models. Unidentified ID is assigned to the user which offers better security to the data uploaded on cloud server is done.
Speaker Clustering Based on Non-Negative Matrix Factorization Using Gaussian Mixture Model in Complementary Subspace

Speech feature variations are mainly attributed to variations in phonetic and speaker information included in speech data. If these two types of information are separated from each other, more robust speaker clustering can be achieved. Principal component analysis transformation can separate speaker information from phonetic information, under the assumption that a space with large within-speaker variance is a "phonetic subspace" and a space within-speaker variance is a "phonetic sub-space". We propose a speaker clustering method based on non-negative matrix factorization using a Gaussian mixture model trained in the speaker subspace. We carried out comparative experiments of the proposed method with conventional methods based on Bayesian information criterion and Gaussian mixture model in an observation space. The experimental results showed that the proposed method can achieve higher clustering accuracy than conventional methods.
Paper proposed for the Special Session on European projects IEEE Multimedia Systems ’ 99 Multi Modal Verification for Teleservices and Security Applications ( AC 102-M 2 VTS )

G. Richard, Y. Menguy, I. Guis, N. Suaudeau, J. Boudy, P. Lockwood Matra Nortel Communications, Rue JP Timbaud, 78392 Bois d’Arcy, France C. Fernández, F. Fernández, D. Garcia-Plaza, Ibermática, Avenida del Partenon, 16-18, Campo de las Naciones, 28042 Madrid, Spain C. Kotropoulos, A. Tefas, I. Pitas, Aristotle University of Thessaloniki, PO BOX 451, Thessaloniki 54006, Greece R. Heimgartner, P. Ryser, Cerberus, CH 8708 Mannedorf,Switzerland C. Beumier, P. Verlinde, Royal Military School, , Belgium S. Pigeon Université Catholique de Louvain, Belgium G. Matas, J. Kittler, University of Surrey J. Bigün, Y. Abdeljaoued, Ecole Polytechnique Fédérale de Lausanne, Switzerland E. Meurville, L. Besacier, M. Ansorge,
Reused Page Management for Log-Structured Flash Storage Systems.

Based on the planar polygon shape classification, we propose a method—Standardized Binary String Descriptor of Convex Polygon—for classification of convex polygons, making it more precise. Thus, the model database space is pruned and the number of shape models compared with, when doing match query and similarity query, is reduced. Furthermore, the number of equivalence class of convex polygon formula based on SBSDCP classification is presented.
Investigating the Performance of Naive- Bayes Classifiers and K- Nearest Neighbor Classifiers

Probability theory is the framework for making decision under uncertainty. In classification, Bayes' rule is used to calculate the probabilities of the classes and it is a big issue how to classify raw data rationally to minimize expected risk. Bayesian theory can roughly be boiled down to one principle: to see the future, one must look at the past. Naive Bayes classifier is one of the mostly used practical Bayesian learning methods. K-nearest neighbor is a supervised learning algorithm where the result of new instance query is classified based on majority of k-nearest neighbor category. The classifiers do not use any model to fit and only based on memory/training data. In this paper, after reviewing Bayesian theory, the naive Bayes classifier and k-nearest neighbor classifier is implemented and applied to a dataset "credit card approval" application. Eventually the performance of these two classifiers is observed on this application in terms of the correct classification and misclassification and how the performance of k-nearest neighbor classifier can be improved by varying the value of k.
Lecture 6: Topic Models

with the most likely topic assignments FIGURE 4. The analysis of a document from Science. Document similarity was computed using Eq. (4); topic words were computed using Eq. (3). the assignment of words to topics in the abstract of the article, and the top ten most similar articles. 3. POSTERIOR INFERENCE FOR LDA The central computational problem for topic modeling with LDA is approximating the posterior in Eq. (2). This distribution is the key to using LDA for both quantitative tasks, such as prediction and document generalization, and the qualitative exploratory tasks that we discuss here. Several approximation techniques have been developed for LDA, including mean field variational inference (Blei et al., 2003), collapsed variational inference (Teh et al., 2006), expectation propagation (Minka and Lafferty, 2002), 8 D. M. BLEI AND J. D. LAFFERTY and Gibbs sampling (Steyvers and Griffiths, 2006). Each has advantages and disadvantages: choosing an approximate inference algorithm amounts to trading off speed, complexity, accuracy, and conceptual simplicity. A thorough comparison of these techniques is not our goal here; we use the mean field variational approach throughout this chapter. 3.1. Mean field variational inference. The basic idea behind variational inference is to approximate an intractable posterior distribution over hidden variables, such as Eq. (2), with a simpler distribution containing free variational parameters. These parameters are then fit so that the approximation is close to the true posterior. The LDA posterior is intractable to compute exactly because the hidden variables (i.e., the components of the hidden topic structure) are dependent when conditioned on data. Specifically, this dependence yields difficulty in computing the denominator in Eq. (2) because one must sum over all configurations of the interdependent N topic assignment variables z1:N . In contrast to the true posterior, the mean field variational distribution for LDA is one where the variables are independent of each other, with and each governed by a different variational parameter: (5) q(E θ1:D, z1:D,1:N , E β1:K ) = K ∏ k=1 q( E βk | E λk) D ∏
On Variable-Scale Piecewise Stationary Spect ASR

A fixed scale (typically 25ms) short time spectral analysis of speech signals, which are inherently multi-scale in nature (typically vowels last for 40-80ms while stops last for 10-20ms), is clearly sub-optimal for time-frequency resolution. Based on the usual assumption that the speech signal can be modeled by a time-varying autoregressive (AR) Gaussian process, we estimate the largest piecewise quasi-stationary speech segments, based on the likelihood that a segment was generated by the same AR process. This likelihood is estimated from the Linear Prediction (LP) residual error. Each of these quasi-stationary segments is then used as an analysis window from which spectral features are extracted. Such an approach thus results in a variable scale time spectral analysis, adaptively estimating the largest possible analysis window size such that the signal remains quasi-stationary, thus the best temporal/frequency resolution tradeoff. The speech recognition experiments on the OGI Numbers95 database, show that the proposed variablescale piecewise stationary spectral analysis based features indeed yield improved recognition accuracy in clean conditions, compared to features based on minimum cross entropy spectrum [1] as well as those based on fixed scale spectral analysis.
Experiences and Results from a New High Performance Network and Application Monitoring Toolkit

Physics Data Grid are developing tools to meet these needs. An additional challenge is the evaluation and fine-tuning of these applications, as well as support for long term monitoring, performance analysis, and troubleshooting. In September 2001, SLAC started the development of a toolkit for studying the available bandwidth as measured by various network sensing tools and comparing that with the bandwidth achievable by various bulk data transfer applications. This study has provided experience in the challenges of deploying and using the sensor tools and transfer applications, as well as information for fine tuning the applications and analyzing their performance. The results presented in this paper include the deployment challenges, techniques for optimizing the duration of measurements, the impacts of throughput on CPU utilization, optimizing windows and parallel streams, the impact on other users, comparisons of various throughput measurement techniques, patterns of throughput behaviors, forecasting, and comparisons of active and passive measurements. We finish up with possible avenues for future development.
Pricing in computer networks: reshaping the research agenda

As the Internet makes the transition from research testbed to commercial enterprise, the topic of pricing in computer networks has suddenly attracted great attention. Much of the discussion in the network design community and the popular press centers on the usage-based vs. flat pricing debate. The more academic literature has largely focused on devising optimal pricing policies; achieving optimal welfare requires charging marginal congestion costs for usage. In this paper we critique this optimality paradigm on three grounds: (1) marginal cost prices may not produce sufficient revenue to fully recover costs and so are perhaps of limited relevance, (2) congestion costs are inherently inaccessible to the network and so cannot reliably form the basis for pricing, and (3) there are other, more structural, goals besides optimality, and some of these goals are incompatible with the global uniformity required for optimal pricing schemes. For these reasons, we contend that the research agenda on pricing in computer network should shift away from the optimality paradigm and focus more on structural and architectural issues. Such issues include allowing local control of pricing policies, fostering interconnection, handling multicast appropriately, and allowing receivers to pay for transmission. To illustrate our point, we describe how these goals might be accomplished in the context of a different pricing paradigm: edge pricing. In addition, we argue that in the context of this edge pricing paradigm, usage-based pricing and flat pricing are not radically different but instead both reside along the single continuum of usage-constraining pricing policies.
Bison and Cattle Grazing Impacts on Baseflow Suspended Sediment Concentrations within Grassland Streams

Prior to European colonization and the introduction of cattle, bison were the prominent grazing ungulates throughout North American grasslands. Yet, relative zoogeomorphic impacts between bison and cattle on grassland streams remain largely unknown. Utilizing a paired watershed study design, we compared baseflow suspended sediment concentrations across ten watersheds and four grazing treatments (ungrazed, bison-grazed, moderately stocked cattle-grazed, and intensively stocked cattle-grazed) in the Flint Hills subregion of the Great Plains. Additionally, we determined whether periods of increased thermal stress led to higher sediment concentrations within each treatment. Water samples were analyzed for total suspended solids (TSS, mg/L), nonvolatile suspended solids (NVSS, mg/L), and percentage organic matter (POM, percent). Intensively stocked cattle-grazed treatments produced significantly higher TSS and NVSS concentrations relative to ungrazed (TSS p = 0.012, NVSS p < 0.01) and bison-grazed treatments (TSS p = 0.082, NVSS p < 0.01). Moderately stocked cattle-grazed treatments contained significantly higher NVSS concentrations relative to bison-grazed treatments (p = 0.057). Bison-grazed and ungrazed treatments contained similar sediment concentrations (TSS and NVSS p > 0.10). Additionally, intensively and moderately stocked cattle-grazed treatments showed a significant increase in sediment concentrations with increasing temperature (p = 0.024 and p = 0.08, respectively), whereas bison-grazed and ungrazed treatments did not (p > 0.10). At the subdaily timescale, the highest sediment concentrations within cattle-grazed treatments and the greatest difference in sediment concentrations between cattle-grazed and ungrazed treatments coincided with the hottest daily temperatures, further highlighting that cattle-grazing impacts are influenced by thermal conditions.
Temporal Trends in Stroke Management and Outcomes between 2011 and 2020: Results from a Nationwide Multicenter Registry

Background: There have been significant advancements in the treatment of ischemic stroke including stent retrievers for endovascular thrombectomy, new oral anticoagulants for atrial fibrillation, dual antiplatelet therapy for stroke prevention, and statins for atherosclerotic stroke. This study aims to evaluate temporal trends of these treatments and related clinical outcomes through a decade-long trend analysis, utilizing data from a comprehensive, national, multicenter stroke registry. We also seek to identify areas in need of improvement. Methods: This analysis involved patients with ischemic stroke or transient ischemic attack registered prospectively in the Clinical Research Center for Stroke-Korea-National Institute of Health (CRCS-K-NIH) registry between 2011 and 2020. We examined temporal trends in risk factors, etiologic subtypes, acute management strategies, and outcomes for up to one year post-stroke. Generalized linear mixed models were employed to account for center clustering. Results: Among 77,662 patients over 10 years, the average age increased by 2.2 years in men and 2.4 years in women. Notably, in-hospital neurological deterioration, 3-month and 1-year mortality, and cumulative incidence of recurrent stroke within one year showed significant decreases over time after adjustments for age, sex, and initial stroke severity (Ptrend? s < 0.01). However, functional outcomes at 3 months and 1 year remained unchanged. The use of endovascular thrombectomy increased from 5.4% in 2011 to 10.6% in 2020. There was also an increase in the prescription of anticoagulants for atrial fibrillation, dual antiplatelet therapy, statins, and stroke unit care. Contrarily, the rate of intravenous thrombolysis showed a slight decline. Conclusions: This study points to a reduction in mortality and risk of recurrent stroke over the past decade, paralleling enhancement in acute and preventive stroke management. Nevertheless, the decline in use of intravenous thrombolysis and the stagnation of functional outcomes may signal the need for further investigation to identify underlying causes of these trends and counterstrategies to mitigate risks.
Retrieving Diverse Social Images at MediaEval 2014: Challenge, Dataset and Evaluation

This paper provides an overview of the Retrieving Diverse Social Images task that is organized as part of the MediaEval 2014 Benchmarking Initiative for Multimedia Evaluation. The task addresses the problem of result diversification in the context of social photo retrieval. We present the task challenges, the proposed data set and ground truth, the required participant runs and the evaluation metrics.
Air Absorbed Dose Rate Measurements and External Dose Assessment by Car-Borne Survey in the Gold Mining Areas of Betare-Oya, Eastern-Cameroon

In order to assess radiological exposure of the public due to natural occurring radioactive materials from gold mining areas of Betare-Oya and vicinity, Eastern Cameroon, a preliminary study was carried out in 2015 for laboratory measurements of activity concentrations of primordial radionuclides. In terms of annual effective dose, results revealed a mean value of 0.34 mSv y –1 . However, it was necessary to make air absorbed dose rate contour map for a detailed evaluation of external dose. For this purpose, a car-borne survey using a 3-in × 3-in NaI(Tl) scintillation spectrometer was carried out in Betare-Oya and vicinity. Absorbed dose rates in air ranged from 23 to 80 nGy h –1 with a mean value of 44 ± 7 nGy h –1 . The average values of activity concentrations in soil of 40 K, 238 U and 232 Th were 197 ± 21 Bq kg –1 , 37 ± 13 Bq kg –1 and 32 ± 7 Bq kg –1 respectively. 232 Th was found to be the main contributor to the absorbed dose rate in air from outdoor terrestrial radiation in the study areas with a mean value of 43%. External annual effective dose ranged from 0.17 to 0.60 mSv y –1 with a mean value of 0.33 ± 0.05 mSv y –1 , in agreement with the result (0.34 mSv y –1 ) of the previous study performed in the same areas using (cid:74)(cid:68)(cid:80)(cid:80)(cid:68)(cid:3)(cid:86)(cid:83)(cid:72)(cid:70)(cid:87)(cid:85)(cid:82)(cid:80)(cid:72)(cid:87)(cid:85)(cid:92)(cid:3)(cid:76)(cid:81)(cid:3)(cid:79)(cid:68)(cid:69)(cid:82)(cid:85)(cid:68)(cid:87)(cid:82)(cid:85)(cid:92)(cid:3)(cid:73)(cid:82)(cid:85)(cid:3)(cid:85)(cid:68)(cid:71)(cid:76)(cid:82)(cid:68)(cid:70)(cid:87)(cid:76)(cid:89)(cid:76)(cid:87)(cid:92)(cid:3)(cid:80)(cid:72)(cid:68)(cid:86)(cid:88)(cid:85)(cid:72)(cid:80)(cid:72)(cid:81)(cid:87)(cid:86)(cid:3)(cid:76)(cid:81)(cid:3)(cid:86)(cid:82)(cid:76)(cid:79)(cid:3)(cid:86)(cid:68)(cid:80)(cid:83)(cid:79)(cid:72)(cid:86)(cid:17)(cid:3)(cid:55)(cid:75)(cid:76)(cid:86)(cid:3)(cid:86)(cid:88)(cid:85)(cid:89)(cid:72)(cid:92)(cid:3)(cid:191)(cid:85)(cid:86)(cid:87)(cid:3)(cid:68)(cid:81)(cid:71)(cid:3)(cid:90)(cid:76)(cid:71)(cid:72)(cid:79)(cid:92)(cid:3)(cid:85)(cid:72)(cid:89)(cid:72)(cid:68)(cid:79)(cid:72)(cid:71)(cid:3)(cid:68)(cid:81)(cid:3) aspect of natural radiation exposures in soil mining areas of Eastern Cameroon.
The EMBL Nucleotide Sequence Database

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/), maintained at the European Bioinformatics Institute (EBI), incorporates, organizes and distributes nucleotide sequences from public sources. The database is a part of an international collaboration with DDBJ (Japan) and GenBank (USA). Data are exchanged between the collaborating databases on a daily basis to achieve optimal synchrony. The web-based tool, Webin, is the preferred system for individual submission of nucleotide sequences, including Third Party Annotation (TPA) and alignment data. Automatic submission procedures are used for submission of data from large-scale genome sequencing centres and from the European Patent Office. Database releases are produced quarterly. The latest data collection can be accessed via FTP, email and WWW interfaces. The EBI's Sequence Retrieval System (SRS) integrates and links the main nucleotide and protein databases as well as many other specialist molecular biology databases. For sequence similarity searching, a variety of tools (e.g. FASTA and BLAST) are available that allow external users to compare their own sequences against the data in the EMBL Nucleotide Sequence Database, the complete genomic component subsection of the database, the WGS data sets and other databases. All available resources can be accessed via the EBI home page at http://www.ebi. ac.uk.
Determination of Specific Emission Factors of Residential for Carbon Footprint Estimation and Mapping in Banyuwangi District

Increasing concentration of CO 2 in the atmosphere occurred due to human activities, one of which is the residential sector. In an effort to overcome the problem of increased concentrations of greenhouse gases, the Government of Indonesia launched the first step action plan to mitigate climate change by doing GHG inventory in accordance with the IPCC guidelines. To increase the accuracy in conducting an inventory, each country was encouraged to draw up specific emission factors. This study aims to determine the residential sector of specific emission factors and analyze the distribution of emissions by mapping the carbon footprint. Calculation method was using the IPCC. Activity data was fuel for cooking in urban and rural areas. The results of the questionnaire showed a different pattern of household fuel consumption in urban and rural areas, households in urban areas generally use LPG, whereas in the rural areas wear LPG and firewood. From the results obtained by analysis, the value of specific emission factor of fuel use for cooking in urban areas 0,3855 tons of CO 2 / household.year, in rural areas 1,7776 tons of CO 2 /household.year. The result of calculation and mapping shows higher carbon footprint of fuel in rural areas due to the use of firewood.