Robust PCPs of Proximity, Shorter PCPs, and Applications to Coding

In Information Retrieval it is well-known that the complexity of processing boolean queries depends on the size of the intermediate results, which could be huge (and are typically on disk) even though the size of the final result may be quite small. In the case of inverted files the most time consuming operation is the merging or intersection of the list of occurrences [1]. We propose, the Keyword tree (K-tree) and forest, efficient structures to handle boolean queries in keyword-based information retrieval. Extensive simulations show that K-tree is orders-of-magnitude faster (i.e., far fewer I/O's) for boolean queries than the usual approach of merging the lists of occurrences and incurs only a small overhead for single keyword queries. The K-tree can be efficiently parallelized as well. The construction cost of K-tree is comparable to the cost of building inverted files.

The goal of property testing is to quickly distinguish between objects which satisfy a property and objects that are ϵ-far from satisfying the property. There are now several general results in this area which show that natural properties of combinatorial objects can be tested with constant query complexity, depending only on ϵ and the property, and not on the size of the object being tested. The upper bound on the query complexity coming from the proof techniques are often enormous and impractical. It remains a major open problem if better bounds hold.Hoppen, Kohayakawa, Moreira, and Sampaio conjectured and Klimosova and Kral' proved that hereditary permutation properties are strongly testable, i.e., can be tested with respect to Kendall's tau distance. The query complexity bound coming from this proof is huge. Even for testing a single forbidden subpermutation it is of Ackermann-type in 1/ϵ. We give a new proof which gives a polynomial bound in 1/ϵ for testing a single forbidden subpermutation.Maybe surprisingly, for testing with respect to the rectangular distance, we prove there is a universal (not depending on the property), polynomial in 1/ϵ query complexity bound for two-sided testing hereditary properties of sufficiently large permutations. We further give a nearly linear bound with respect to a closely related metric which also depends on the smallest forbidden subpermutation for the property. Finally, we show that several different permutation metrics of interest are related to the rectangular distance, yielding similar results for testing with respect to these metrics.

The main contribution of this work is a rate amplification procedure for LCC. Our procedure converts any q-query linear LCC, having rate ρ and, say, constant distance to an asymptotically good LCC with qpoly(1/ρ) queries. Our second contribution is a distance amplification procedure for LDC that converts any linear LDC with distance δ and, say, constant rate to an asymptotically good LDC. The query complexity only suffers a multiplicative overhead that is roughly equal to the query complexity of a length 1/δ asymptotically good LDC. This improves upon the poly(1/δ) overhead obtained by the AEL distance amplification procedure [2, 1]. Our work establishes that the construction of asymptotically good LDC and LCC is reduced, with a minor overhead in query complexity, to the problem of constructing a vanishing rate linear LCC and a (rapidly) vanishing distance linear LDC, respectively.

It has recently been shown that first-order- and datalog-rewritability of ontology-mediated queries (OMQs) with expressive ontologies can be checked in NExpTime using a reduction to CSPs. In this paper, we present a case study for OMQs with Boolean conjunctive queries and a fixed ontology consisting of a single covering axiom \(A \sqsubseteq F \sqcup T\), possibly supplemented with a disjointness axiom for T and F. The ultimate aim is to classify such OMQs according to their data complexity: \(\textsc {AC}^0\), L, NL, P or coNP. We report on our experience with trying to distinguish between OMQs in P and coNP using the reduction to CSPs and the Polyanna software for finding polymorphisms.

Despite advancing search technologies, information overload has not yet been solved. Getting an overview of information or explorative access to information becomes increasingly difficult with the exponentially increasing amount of information. Search result visualizations, especially for faceted browsing, aim at supporting users to find their way through large document collections. We propose Facets cape, a novel visualization for navigation and refinement of search results allowing users to visually construct complex boolean search queries for narrowing down the search space. This visualization combines Voronoi subdivision and a tag cloud representation of the search facets. Further it includes a preview of action (query preview) and interactions to allow users to focus on important aspects of the data for the task at hand. In a comparative user study with 15 users we compared the visualization to a standard faceted browsing interface for different types of search tasks. The study revealed that participants used the unfamiliar interface as efficiently and effectively as the familiar tree-like display. Results indicate that the Facets cape is a promising way of supporting users in exploring the faceted search space.

With the growing emphasis on sustainability and circular economy principles in industrial sectors, the effective utilization of waste-derived and abundantly available natural resources has become imperative. Renewable lignocellulosic fibers such as jute fiber (JF), banana fiber (BaF), coconut coir (CC), and pineapple leaf fiber (PALF) serve as viable reinforcements for developing eco-friendly polymer composites. In this study, hybrid natural fiber (NF) composites were fabricated using the hand lay-up method with varying weight percentages of alkaline-treated JF, CC, BaF, and PALF. Alkaline treatment improved fiber–matrix interfacial bonding by reducing hydroxyl groups and enhancing surface roughness, which significantly contributed to improved mechanical and thermal performance. Mechanical testing revealed that the composite containing 20% JF, 20% CC, and 10% PALF exhibited superior properties, achieving a tensile strength of 85.8 MPa, flexural strength of 134.5 MPa, impact strength of 23.3 J/m2, and hardness of 72.6 Shore D. Fourier transform infrared spectroscopy (FTIR) confirmed successful alkaline treatment through reduced hydroxyl group intensity and improved fiber–matrix compatibility. Atomic force microscopy (AFM) further revealed increased surface roughness (Ra = 31.43 nm), indicating enhanced interfacial adhesion. To predict mechanical performance, machine learning (ML) regression models including linear regression, multilinear regression, decision tree, and random forest were developed using experimental data. Among these, the random forest model demonstrated the highest predictive capability, achieving R2 values of 0.968 for tensile strength, 0.939 for flexural strength, 0.941 for impact strength, and 0.962 for hardness, along with the lowest error metrics (mean absolute error and root mean squared error). These results highlight its suitability for accurate prediction of mechanical properties in fiber-reinforced composites. Furthermore, dynamic mechanical analysis (DMA) revealed enhanced viscoelastic behaviour in treated fiber composites, while thermogravimetric analysis (TGA) confirmed excellent thermal stability up to 690 °C in JF/CC/PALF-reinforced samples.

We consider testing directed graphs for being Eulerian in the orientation model introduced in [15]. Despite the local nature of the property of being Eulerian, it turns out to be significantly harder for testing than other properties studied in the orientation model. We show a non-constant lower bound on the query complexity of 2-sided tests and a linear lower bound on the query complexity of 1-sided tests for this property. On the positive side, we give several 1-sided and 2-sided tests, including a sub-linear query complexity 2-sided test for general graphs. For special classes of graphs, including bounded-degree graphs and expander graphs, we provide improved results. In particular, we give a 2-sided test with constant query complexity for dense graphs, as well as for expander graphs with a constant expansion parameter.

In this paper, we propose a novel polar code construction scheme, suitable for the underwater acoustic (UWA) multi-user communication system using orthogonal frequency division multiplexing (OFDM). We use the polar codes because the code rate of a polar code can be arbitrarily designed. Moreover, the polar codes can also be used to create a nested code structure, divided into several subsets (codebook). We exploit this feature of the polar codes and place the information bits in the codebook to avoid superimposition of all the users. This helps to eliminate the influence of the power allocation coefficient and make full use of the power of the transducer at the transmitted node. Furthermore, the proposed scheme maximizes the utilization efficiency of the OFDM subcarrier resource for each user by avoiding null pilot tones that are usually required for channel equalization in the traditional schemes. The proposed scheme also does not depend on the channel state information (CSI) as prior information as each user can decode their own data independently by using their own codebook without successive interference cancellation (SIC). The simulation and tank experiment results demonstrate that the proposed scheme can significantly guarantee the reliability of all the users, and reduces the complexity of the receiver, thus making it most suitable for the downlink UWA multi-user communication systems.

In order to achieve very strong inter-ballistic requirements, a unusual free standing rocket motor propellant grain was designed, with variable channel diameter. Due to its very high length, it was expected for the grain to be exposed to dangerous combination of different loads during the design phase. Structural analysis of viscoelastic propellant grain is always very complex and it differs substantially from an elastic analysis, because the propellant mechanical properties depend on temperature and strain rate. The most complex case in the analysis occurs when multiple loads operate simultaneously. In this paper, the structural analysis has been done during the initial period of rocket flight, when the grain is under very fast load due to acceleration and at the same time under a slow load due to surface pressure, created as a result of temperature dilatation. In the absence of data on mechanical properties of the new propellant composition, the properties over the whole time-temperature range were estimated comparing by a similar composition that have been completely tested earlier. Using finite element method (ANSYS program) two different design solutions were examined and the more reliable one was adopted.

With the rapid development of digital economy, enterprises need to make financial management activities and development decisions based on a large number of financial data and information. This also exposes the shortcomings of the traditional financial analysis and processing mode in adaptability, functionality and efficiency. In this regard, based on the actual needs of enterprises, this paper will put forward a set of construction scheme of enterprise financial data visualization analysis system, give full play to the practical application advantages of data mining technology in the era of big data, change the original processing methods, and provide an efficient, reliable and convenient new way for enterprise financial data analysis. The whole system adopts B/S architecture design, the client design is based on VUE framework, and the server construction is based on Django framework, and the financial data is analyzed, mined and visually displayed by using Numpy, Pandas, Matplotlib and other class libraries in Python environment. Practice has proved that the system can support users to call K-means, Decision Tree, Logistic and other algorithm models online for multi-dimensional analysis of financial data, which realizes an important supplement to traditional financial analysis, and achieves the purpose of improving financial management efficiency and assisting enterprise development decision-making.

A comment on the article by William D. Nordhaus in this volume.

This paper presents a numerical investigation of the material elastic properties for short-length mostly in-plane random fiber composites, based on microscale geometrical modeling. The particular case considered is that of materials in which the majority of fibers’ orientations are contained or slightly deviate from a dominant plane. Representative volume elements for two types of random fiber composite material geometries with different fiber aspect ratios and volume fractions are generated using a novel technique. The elastic properties of the equivalent homogeneous material are determined using direct three-dimensional finite element analysis. A windowing-type analysis is employed to investigate the influence of the fiber distribution homogeneity on the homogenized elastic properties. The results are compared and validated using two alternative approaches — first, by orientation averaging of the stiffness tensor of the equivalent unidirectional composite determined by direct FEM analysis and, second, by employing the laminated random strand method.

The article compares the two distribution automation systems built 10 years before with now in Jinan Power Supply Company. The old distribution automation system put into operation in July 2002, named iES-DMS1000. From the actual use and maintenance of this system, we summarize the problems of this system. Learn from the experience and lessons of the old distribution network systems, we state the construction of the intelligent distribution automation system building in Jinan Power Supply Company now. Breaking the previous systems' construction of island, it can come true that many related information systems can interconnect with each other in the new distribution system. That is the innovation for Control Integration, connecting the various systems with the new distribution automation system, In the end of this article, we abstract the characteristics and experiences of the distribution automation system building in the Jinan Power Supply Company now. And we set up the experience and recommendations of the system setup and maintenance.

Design from recycling: A complex mixed plastic waste case study

The prevalence and availability of cloud infrastructures has made them the de facto solution for storing and archiving data, both for organizations and individual users. Nonetheless, the cloud's wide spread adoption is still hindered by dependability and security concerns, particularly in applications with large data collections where efficient search and retrieval services are also major requirements. This leads to an increased tension between security, efficiency, and search expressiveness. In this paper we tackle this tension by proposing BISEN, a new provably-secure boolean searchable symmetric encryption scheme that improves these three complementary dimensions by exploring the design space of isolation guarantees offered by novel commodity hardware such as Intel SGX, abstracted as Isolated Execution Environments (IEEs). BISEN is the first scheme to support multiple users and enable highly expressive and arbitrarily complex boolean queries, with minimal information leakage regarding performed queries and accessed data, and verifiability regarding fully malicious adversaries. Furthermore, BISEN extends the traditional SSE model to support filter functions on search results based on generic metadata created by the users. Experimental validation and comparison with the state of art shows that BISEN provides better performance with enriched search semantics and security properties.