A Comparison between Term-Independence Retrieval Models for Ad Hoc Retrieval

In Information Retrieval, numerous retrieval models or document ranking functions have been developed in the quest for better retrieval effectiveness. Apart from some formal retrieval models formulated on a theoretical basis, various recent works have applied heuristic constraints to guide the derivation of document ranking functions. While many recent methods are shown to improve over established and successful models, comparison among these new methods under a common environment is often missing. To address this issue, we perform an extensive and up-to-date comparison of leading term-independence retrieval models implemented in our own retrieval system. Our study focuses on the following questions: (RQ1) Is there a retrieval model that consistently outperforms all other models across multiple collections; (RQ2) What are the important features of an effective document ranking function? Our retrieval experiments performed on several TREC test collections of a wide range of sizes (up to the terabyte-sized Clueweb09 Category B) enable us to answer these research questions. This work also serves as a reproducibility study for leading retrieval models. While our experiments show that no single retrieval model outperforms all others across all tested collections, some recent retrieval models, such as MATF and MVD, consistently perform better than the common baselines.

The Potential Mechanisms of AMOC Multidecadal Periods in CMIP6/CMIP5 Preindustrial Simulations

Observations, theoretical analyses, and climate models show that the period of multidecadal variability of the Atlantic Meridional Overturning Circulation (AMOC) is related to westward temperature propagations in the subpolar North Atlantic, which is modulated by oceanic baroclinic Rossby waves. Here, we find major periods of AMOC variability of 12-28 years and associated westward temperature propagations in the preindustrial simulations of 9 CMIP6/CMIP5 models. Comparison with observations shows that the models reasonably simulate ocean stratifications in turn oceanic Rossby waves in the subpolar North Atlantic. The timescales of Rossby waves propagating on a static background flow across the subpolar North Atlantic basin overestimate the AMOC periods. The mean flow effects involving westward geostrophic self-advection and eastward mean advection largely shorten and greatly improve the estimate of AMOC periods through increasing Rossby wave speeds. Our results illustrate the importance of considering mean flow effects on Rossby wave propagations in the estimate of AMOC periods.

Soft Computing Techniques for Appraisal of Potentially Toxic Elements from Jalandhar (Punjab), India

The contamination of potentially toxic elements (PTEs) in agricultural soils is a serious concern around the globe, and modelling approaches is imperative in order to determine the possible hazards linked with PTEs. These techniques accurately assess the PTEs in soil, which play a pivotal role in eliminating the weaknesses in determining PTEs in soils. This paper aims to predict the concentration of Cu, Co and Pb using neural networks (NNs) based on multilayer perceptron (MLP) and boosted regression trees (BT). Statistical performance estimation factors were rummage-sale to measure the performance of developed models. Comparison of the coefficient of correlation and root mean squared error suggest that MLP-established models perform better than BT-based models for predicting the concentration of Cu and Pb, whereas BT models perform better than MLP established models at predicting the concentration of Co.

Advantages and disadvantages of blockchain-based electronic voting systems with homomorphic encryption

The work examines the phenomenon of electronic voting and advantages and disadvantages of such systems. Particular attention is paid to the electronic voting systems that use block chain technologies in their scheme. The purpose of the publication is to create a theoretical model of the electronic voting system, which will include all stages of the elections. In this work, a study and analysis of the existing electronic voting systems were carried out, the requirements for the creation of electronic voting systems were substantiated. Possible attacks on both conventional electronic voting systems and options using the block chain were given. The advantages of the work include theoretical and practical models, comparison and study of possible attacks on various types of electronic voting systems.

A mixed 0-1 programming approach for multiple attribute strategic weight manipulation based on uncertainty theory

In practical multiple attribute decision making (MADM) problems, the interest groups or individuals intentionally set attribute weights to achieve their own benefits. In this case, the rankings of different alternatives are changed strategically, which is called the strategic weight manipulation in MADM. Sometimes, the attribute values are given with imprecise forms. Several theories and methods have been developed to deal with uncertainty, such as probability theory, interval values, intuitionistic fuzzy sets, hesitant fuzzy sets, etc. In this paper, we study the strategic weight manipulation based on the belief degree of uncertainty theory, with uncertain attribute values obeying linear uncertain distributions. It allows the attribute values to be considered as a whole in the operation process. A series of mixed 0-1 programming models are constructed to set a strategic weight vector for a desired ranking of a particular alternative. Finally, an example based on the assessment of the performance of COVID-19 vaccines illustrates the validity of the proposed models. Comparison analysis shows that, compared to the deterministic case, it is easier to manipulate attribute weights when the attribute values obey the linear uncertain distribution. And a further comparative analysis highlights the performance of different aggregation operators in defending against the strategic manipulation, and highlights the impacts on ranking range under different belief degrees.

Innovations in Acheulean Biface production at la Noira (France) during Middle Pleistocene in Western Europe

The archaeological sequence of la Noira (Centre region, France) yielded two phases of occupation: ca 700 ka (stratum a) and ca 450 ka (stratum c). No site between these two dates has yet been discovered in the area, and this chronological period has thus been interpreted as a gap in settlement from MIS 16 to MIS 12, two crucial phases of occupation in Western Europe, before and after the long glacial event MIS 12 which record the onset of the Acheulean in Europe and earliest evidence of innovations from MIS 12 considered as a shift in human evolution. Here, we compare these two levels and track technological innovations during this time, combining technological analysis with geometric morphometrics with the use of 3D models comparison of the Large Cutting Tools (LCTs). Stratum a yielded an Early Acheulean, one of the few evidence in Europe presents tools with mainly short shaping sequences on local millstone slabs, with special attention to tips, but with clear management of tool volume. Stratum c, dated to the MIS 11, differs in that both local millstone and flints from distant sources show longer shaping sequences, the use of soft hammers for several series of removals on tools, combined with final regularizing retouch on entire edges. The morphometric approach shows a morphological transition from oval to teardrop shapes for the thinnest tools. Our data suggest a clear technological filiation between strata a and c and in la Noira populations from MIS 16 and MIS 12, as suggested for innovations of core technologies and land-use patterns, and raise question on local human behavioral evolution over the Middle Pleistocene in Western Europe.

Acoustic decoupling for structural elements by affixed supports - inherent contradiction or perfect complement? Restrained vibration isolation supports - a critical review

Restrained vibration isolation supports balance efficient isolation performance and stability for the supporting body under present loads. Necessary and beneficially for noise and vibration isolation applications with stringent stability requirements, such as full building isolation with potential uplift, interior partition sway bracing, curtain walls, elevator rail isolation, and mechanical vibration isolation, the performance of restrained vibration isolators are often misunderstood or oversimplified. This paper investigates the general vibration isolation theory used to create the analytical model for restrained isolation supports, intricacies of vibration isolation materials which may cause reality to diverge from well-known models, comparison of theory to laboratory testing, and a review of common uses/applications for these types of vibration isolation solutions, and recommendation to avoid undesired results from common pitfalls associated with restrained isolation supports implementation and installations.

Models Comparison And Validation With the Experimental Nano- Scale Silicon Substrate Based Annealed Pt/HfO2/Pt Resistive Random Access Memory Cell

Metal oxide resistive random access memory (RRAM) is a novel device that provides an alternate solution for existing CMOS memory devices. In RRAM, correlate the experimental result with a simulated result by a unique model is a critical task. This work focused on the validation of silicon substrate-based fabricated single layer annealed and electroformed at 80oC ambient temperature (A-80) RRAM cell. The experimental result concludes that the proposed Pt/HfO2/Pt device provides the forming voltage of 3.8 V, Vset = 1.7 V, and Vreset=-0.8 V. Switching results are compared with the simulated result which is working based on non-linear ion drift, Yakopcic and voltage threshold adaptive memristor (VTEAM) models. VTEAM model gives a closure relationship with experimental data and well suited for our fabricated device. Further, the VTEAM model is modified to contribute accurate results and one of the standard model metrics, accuracy is analysed for a modified VTEAM model. Statistical analysis proves that, the mean error percentage of modified VTEAM and VTEAM models against experimental outcomes are 21.4% and 25.3 % respectively