Entire Table Research Articles

LORE++: Logical location regression network for table structure recognition with pre-training

Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Current approaches address this issue by either predicting the adjacency of detected cells or direct generation of structural sequences. Nonetheless, these approaches either count on additional heuristic rules for post-processing, or involve the generation of extremely long-range sequences that lead to computational intricacy. In this paper, We redefine TSR as a LOgical location REgression paradigm, which effectively captures inherent logical dependencies and constraints among table cells. Correspondingly, we propose LORE, a novel approach for TSR. LORE simultaneously predicts accurate geometric coordinates of table cells and the logical structures of the entire table. Our proposed LORE is conceptually simpler, easier to train, and more accurate than other TSR paradigms. Moreover, to enhance the model’s spatial and logical representation capabilities, we propose two pre-training tasks, resulting in an upgraded version named LORE++. The incorporation of pre-training is proven to enjoy significant advantages, leading to a substantial enhancement in terms of accuracy, generalization, and few-shot capability compared to its predecessor. Experiments on standard benchmarks demonstrate the superiority of LORE++, which highlights the potential and promising prospect of the logical location regression paradigm for TSR.

A method to accelerate computational efficiency by more than two orders of magnitude for Monte Carlo simulations of electron-solid interactions

A method has been developed to increase computational efficiency in Monte Carlo simulations of electron transport and interactions in matter. The method serves as the computational engine for the open-source code AMCSET (Aggie Monte Carlo Simulations of Electron and Ion Transport). The key is to combine n consecutive neighboring free flying distances into groups. Within each group, both flying distance and Mott scattering angles are obtained using Monte Carlo sampling under an equal energy approximation. This reduces the number of integrations of the tabulated differential Mott scattering cross-section in scattering angle selection, i.e., from 1000 to 1 if n = 1000. The method increases efficiency by more than 100 times. At the same time, the calculation still guarantees accuracy in calculating electron trajectory, excitation/ionization energy deposition, elastic scattering energy deposition, and displacement creation. For demonstration, 10 MeV electron bombardments of pure Fe with n up to 1000 are used as examples. The method, due to the availability of tabulated scattering cross-sections, is applicable for targets of the entire elemental table up to Z = 118, and for electron energies up to 900 MeV.

Kinematic Analysis and Research on the "Push Shot" Action of Table Football

In order to reveal the kinematic characteristics of the "push shot" technique in table football, this article analyzes and studies the kinematics of the "push shot" technique in table football using the three-dimensional motion analysis method, conducts experimental measurements of the push shot technique in table football players, and analyzes and studies its kinematic parameters. When completing the entire table football technical movement, the upper limbs need to rotate and cooperate with the vertical axis and coronal axis of the torso, ultimately forming a wrist compression movement to the fingers and wrists. When athletes complete technical movements, whether it is dribbling or shooting, the flexibility of their wrists is extremely high. Therefore, during practice, it is necessary to strengthen the training of the wrist and small muscle groups of the fingers, and pay attention to the practice of instant force application. Both the joints of the upper and lower limbs are very important. Therefore, during athlete training, it is necessary to strengthen the strength of the body's joints.

Geometric Mean Type of Proportional Reduction in Variation Measure for Two-Way Contingency Tables

Traditional analysis of two-way contingency tables with explanatory and response variables focuses on the independence of two variables. However, if the variables do not show independence or a clear relationship, the analysis shifts to the degree of association. Various measures have been proposed to calculate the degree of association. One is the proportional reduction in variation (PRV) measure. This measure describes the PRV from the marginal distribution to the conditional distribution of the response variable. Although conventional PRV measures can assess the association of the entire contingency table, they cannot accurately assess the association for each explanatory variable. In this paper, we propose a geometric mean type of PRV (geoPRV) measure, which aims to sensitively capture the association of each explanatory variable to the response variable. Our approach uses a geometric mean, and enabling analysis without underestimating the values when the cells in the contingency table are partially biased. The geoPRV measure can be constructed using any function that satisfies specific conditions. This approach has practical advantages, and in special cases, conventional PRV measures can be expressed as geometric mean types.

Numerical convergence of electromagnetic responses with the finite-amplitude method

The response of a nucleus to an electromagnetic probe is a key quantity to simulate photabsorption or photodeexcitation processes. For large calculations at the scale of the entire mass table, this response can be estimated by linear response theory. Thanks to the introduction of the finite-amplitude method (FAM), calculations are computationally efficient. In this paper, we investigate in more details the convergence of FAM calculations of the response function as a function of the parameters controlling the numerical implementation of the theory. We show that the response is much less sensitive to the details of the single-particle basis than, e.g., Hartree-Fock-Bogoliubov calculations.

Electron Oscillation-Induced Splitting Electroluminescence from Nano-LEDsfor Device-Level Encryption.

Data security is a major concern in digital age, which generally relies on algorithm-based mathematical encryption. Recently, encryption techniques based on physical principles are emerging and being developed, leading to the new generation of encryption moving from mathematics to the intersection of mathematics and physics. Here, device-level encryption with ideal security is ingeniously achieved using modulation of the electron-hole radiative recombination in a GaN-light-emitting diode (LED). When a nano-LED is driven in the non-carrier injection mode, the oscillation of confined electrons can split what should be a single light pulse into multiple pulses. The morphology (amplitude, shape, and pulse number) of those history-dependent multiple pulses that act as carriers for transmitted digital information depends highly on the parameters of the driving signals, which makes those signals mathematically uncrackable and can increase the volume and security of transmitted information. Moreover, a hardware and software platform are designed to demonstrate the encrypted data transmission based on the device-level encryption method, enabling recognition of the entire ASCII code table. The device-level encryption based on splitting electroluminescence provides an encryption method during the conversion process of digital signals to optical signals and can improve the security of LED-based communication.

Finding recently persistent flows in high-speed packet streams based on cuckoo filter

In high-speed networks, flow-level traffic measurement is an essential tool to understand how network bandwidth is consumed and support the detection of anomalous traffic. While many prior work focuses on tracking the frequent flows (a.k.a. heavy hitters), in this paper, we put more focus on tracking the persistent flows, which jointly consider the frequency, duration and regularity of the packet arrival events of a flow. Although this more generalized metric called persistence has been defined before, it is still unknown how to use limited memory on data plane to monitor the top-k persistent flows in a recent time interval. In this paper, we propose an algorithm named PFD-DW built upon cuckoo filter (an improved version of hash table with better memory efficiency), to monitor the top-k persistent flows under the time-decaying window. It can be regarded as a variant of cuckoo filter, which transforms each bucket into a bucket-level min-heap. Its advantage is that, when the table is full and a packet of a new flow arrives, it can select the least persistent flow along the cuckoo kicking path as the victim of flow replacement. We deliberately avoid the scanning of the entire table to keep the high time efficiency. Based on real-world network traffic traces, we evaluate the performance of our DAKP-CF, a degraded version of PFD-DW that only considers each flow’s packet arrival frequency. The results show that it outperforms the existing algorithms for the top-k frequent flow identification task. It provides nearly 98% identification accuracy with roughly 50% less memory cost. We also evaluate our PFD-DW algorithm for the more generalized task of identifying the recently persistent flows. It provides 93% identification rate of top-3000 persistent flows using only 576KB memory, while attaining 1.5% persistence estimation error. Its memory cost is reduced by 97% than another proposed solution PFD-SW under sliding time window. We have also developed a prototype of PFD-DW, based on the Fd.io VPP software switch accelerated by Intel DPDK.

A Fuzzy Neural Network Controller Using Compromise Features for Timeliness Problem

When the control rules of traditional fuzzy controller are determined, it comes to be time-consuming and laborious to adjust for different usage conditions. Therefore, the timeliness cannot be guaranteed to solve the timeliness problem, and a fuzzy controller with modifiable factors is designed. While the entire control table is affected by the modifiable factors selection table, all previous control parameters need to be reset. In light of above problems, this paper firstly proposes new fuzzy controller design methods, which retain strengths of traditional controller and controller with modifiable factors. It effectively overcomes the shortcomings of the two controllers mentioned above, and only need to adjust the compromise factor for different working conditions of proposed controller, which is more convenient and efficient. Secondly, the proposed fuzzy controller also adopts a four-layer neural network to optimize the control rules of compromise to improve control precision and system robustness. Finally, the excellent characteristics of proposed controller are verified through simulation research, and the simulation result proves the proposed fuzzy controller has the advantages of higher control precision and smaller transition.

Design parameters and landing impacts of snow park jumps in Switzerland

ObjectivesDesign parameters and landing impacts for selected snow park jumps in Switzerland were compared with the parameters recommended to increase the jumps’ safety by the Swiss Council for Accident Prevention (BFU). High impact zones were identified to help snow park shapers optimize the design of their jumps. A rough estimate of the influence of snow hardness on landing impacts was also provided. DesignDuring the 2020/2021 winter season three-dimensional geometries of 23 jumps were captured using differential global navigation satellite system and terrestrial laser scanning. A point mass model was used to numerically calculate trajectories. The equivalent fall height (eFH) was used to quantify landing impacts and an empiric snow-deformation function was applied to take the effect of snow hardness into consideration. Workshops were held to discuss results and transfer findings. Methods2D-profiles of the jumps were estimated by projecting the captured 3D position data onto the longitudinal cross-section plane. Table and landing geometry were smoothed and interpolated to a spatial resolution of 0.1 ​m, while the kicker was fitted with a 2nd order polynomial. Trajectories were numerically calculated for take-off speeds from 6 to 17.6 ​m ​s−1 including aerodynamic forces using the Runge-Kutta method. The calculated eFH at the landing points were used to divide the landing into low-impact, medium-impact, and high-impact zones. ResultsMedium sized jumps had a low-impact zone of sufficient length (>6 ​m) and eFH smaller than 1.5 ​m throughout the entire table meeting the BFU recommendations. Nevertheless, critical eFH larger than 1.5 ​m, were obtained when take-off speeds increased by only 1.14 ​m ​s−1. Large jumps had low-impact zone lengths in accord with the recommendations (>9 ​m), but high eFH (2.3–3.4 ​m) occurred for table landings. 10 of the 13 XL-jumps had long low-impact zones of approximately 12–15 ​m. Besides the risk of high impact landings towards the end of the landing area, as found similarly for the smaller jumps, portions of XL-jumps had very high eFH (2.6–4.6 ​m) for table landings. ConclusionsThe study confirmed the existing BFU recommendations of size categories, design parameters and landing impacts limits as prevalent and practicable and provided knowledge for future safety recommendations. Modifying table geometries and taking measures to limit the in-run speeds would help reduce landing impacts, and the hazard due to hard snow conditions should also be considered.

Online schema evolution is (almost) free for snapshot databases

Modern database applications often change their schemas to keep up with the changing requirements. However, support for online and transactional schema evolution remains challenging in existing database systems. Specifically, prior work often takes ad hoc approaches to schema evolution with "patches" applied to existing systems, leading to many corner cases and often incomplete functionality. Applications therefore often have to carefully schedule downtimes for schema changes, sacrificing availability. This paper presents Tesseract, a new approach to online and transactional schema evolution without the aforementioned drawbacks. We design Tesseract based on a key observation: in widely used multi-versioned database systems, schema evolution can be modeled as data modification operations that change the entire table, i.e., data-definition-as-modification (DDaM). This allows us to support schema almost "for free" by leveraging the concurrency control protocol. By simple tweaks to existing snapshot isolation protocols, on a 40-core server we show that under a variety of workloads, Tesseract is able to provide online, transactional schema evolution without service downtime, and retain high application performance when schema evolution is in progress.

One Truth Prevails: A Deep-learning Based Single-Trace Power Analysis on RSA–CRT with Windowed Exponentiation

In this paper, a deep-learning based power/EM analysis attack on the state-of-the-art RSA–CRT software implementation is proposed. Our method is applied to a side-channel-aware implementation with the Gnu Multi-Precision (MP) Library, which is a typical open-source software library. Gnu MP employs a fixed-window exponentiation, which is the fastest in a constant time, and loads the entire precomputation table once to avoid side-channel leaks from multiplicands. To conduct an accurate estimation of secret exponents, our method focuses on the process of loading the entire precomputation table, which we call a dummy load scheme. It is particularly noteworthy that the dummy load scheme is implemented as a countermeasure against a simple power/EM analysis (SPA/SEMA). This type of vulnerability from a dummy load scheme also exists in other cryptographic libraries. We also propose a partial key exposure attack suitable for the distribution of errors inthe secret exponents recovered from the windowed exponentiation. We experimentally show that the proposed method consisting of the above power/EM analysis attack, as well as a partial key exposure attack, can be used to fully recover the secret key of the RSA–CRT from the side-channel information of a single decryption or a signature process.

HCFTL: A Locality-Aware Flash Translation Layer for Efficient Address Translation

In modern solid-state drives (SSDs), a flash translation layer (FTL) is the core engine performing the logical-to-physical address translations. However, the increasing capacity of SSDs requires a large DRAM space to hold the mapping table in a page-level FTL. Due to the limited size of built-in DRAM, existing FTL schemes selectively cache some active mapping entries in DRAM, while store the entire mapping table on flash. However, the low cache hit ratio introduced by the traditional mapping entry eviction policy degrades the access performance of SSDs. In this article, we propose a novel FTL, hot-clusterity FTL (HCFTL), to improve the hit ratio of cached mapping table (CMT) of SSDs with limited cache space. HCFTL clusters mapping entries, which are newly evicted from the cache, into dynamic translation pages (DTPs). Reading entries from DTPs will increase the CMT hit ratio due to spatial and temporal localities. Because the logical page numbers (LPNs) in a DTP are not consecutive, we introduce two different efficient index structures to speedup the lookup of mapping entries in DTPs. Furthermore, to make the DTP index highly accurate, we additionally allocate an auxiliary cache to buffer the mapping entries newly evicted from CMT, and produce dynamic pages with minimum difference between the maximal and the minimal LPNs of entries in those pages. Our experiments show that HCFTL can improve the CMT hit ratio by up to 41.1% and decrease the system response time by up to 33.3%, compared to baseline FTL schemes.

Structured encryption for knowledge graphs

We investigate the problem of structured encryption (STE) for knowledge graphs (KGs) where the knowledge of data can be efficiently and privately queried. Presently, the application of natural language processing (NLP) for knowledge-based search is gradually emerging. Compared with the traditional search based only on keywords of documents—symmetric searchable encryption (SSE), the knowledge-based search system transforms the latent knowledge contained in documents into a semantic network as a knowledge base, which greatly improves the accuracy and relevance of search results. In order to develop a knowledge-based search, the contents of documents are analyzed and extracted using KG techniques (e.g. multi-relational graph (MG) and property graph (PG)), and then all encrypted nodes and edges in a KG constitute the entire index table and database. This paper proposes the first STE for KGs with CQA2-security to search on protected knowledge, where KGs include MGs and PGs. In general, the latter is more complex than the former, but it can represent more abundant knowledge. Experimental results show that the index construction time of our schemes is about 1.9s and the query time is about 190 ms. Our sensitivity analysis shows that the performance of our proposed schemes is greatly influenced by the number of edges and nodes, but less by the number of properties.

Analyzing land disputes as an influencing social factor responsible for low agricultural productivity in Pakistani society

The development of a society depends upon the social cohesion of all its institutions. Likewise, the growth of agriculture is also relying on the peaceful environment of the society. This particular study was conducted to know about the negative effects of land disputes on agricultural productivity in two districts (Charsadda and Mardan) of Pakistan. A sample of 384 farmers were selected through multistage random sampling method. The data from these farmers were collected through a well-designed interview schedule adopted from the literature review, following the ethics of research and culture of the area. Results showed that the association between land disputes and net income from agricultural production was found non-significant & positive (p=0.992; = 0.039) for the high socio-economic group, highly significant and negative (P=0.000; = -0.204) for middle socio-economic group, however, was non-significant and negative (P=0.523 & Tc= -0.162) for low-income groups. Value of level of significance and Tc for entire table show highly significant and negative (P=0.000 & Tc= -0.131) association between land disputes and agricultural productivity for all the three socio-economic groups which indicated a spurious relationship based on socio-economic statuses of the respondents. The study recommended that correction, computerization, and regular updation of land records may overcome land disputes which would also aid in the avoidance of wastage of financial, social, and time resources and its positive utilization in agricultural production.

The binary Gold function and its c-boomerang connectivity table

Here, we give a complete description of the entire c-Boomerang Connectivity Table for the Gold function over finite fields of even characteristic, by using double Weil sums. As a by-product, we generalize a result of Boura and Canteaut (IACR Trans. Symmetric Cryptol. 2018(3) : 290–310, 2018) for the classical boomerang uniformity (see also the extended abstract by Eddahmani and Mesnager at the Boolean Functions and their Applications (BFA 2021) conference).

The genetic code is very close to a global optimum in a model of its origin taking into account both the partition energy of amino acids and their biosynthetic relationships

We used the Moran's I index of global spatial autocorrelation with the aim of studying the distribution of the physicochemical or biological properties of amino acids within the genetic code table. First, using this index we are able to identify the amino acid property - among the 530 analyzed - that best correlates with the organization of the genetic code in the set of amino acid permutation codes. Considering, then, a model suggested by the coevolution theory of the genetic code origin - which in addition to the biosynthetic relationships between amino acids took into account also their physicochemical properties - we investigated the level of optimization achieved by these properties either on the entire genetic code table, or only on its columns or only on its rows. Specifically, we estimated the optimization achieved in the restricted set of amino acid permutation codes subject to the constraints derived from the biosynthetic classes of amino acids, in which we identify the most optimized amino acid property among all those present in the database. Unlike what has been claimed in the literature, it would appear that it was not the polarity of amino acids that structured the genetic code, but that it could have been their partition energy instead. In actual fact, it would seem to reach an optimization level of about 96% on the whole table of the genetic code and 98% on its columns. Given that this result has been obtained for amino acid permutation codes subject to biosynthetic constraints, that is to say, for a model of the genetic code consistent with the coevolution theory, we should consider the following conclusions reasonable. (i) The coevolution theory might be corroborated by these observations because the model used referred to the biosynthetic relationships between amino acids, which are suggested by this theory as having been fundamental in structuring the genetic code. (ii) The very high optimization on the columns of the genetic code would not only be compatible but would further corroborate the coevolution theory because this suggests that, as the genetic code was structured along its rows by the biosynthetic relationships of amino acids, on its columns strong selective pressure might have been put in place to minimize, for example, the deleterious effects of translation errors. (iii) The finding that partition energy could be the most optimized property of amino acids in the genetic code would in turn be consistent with one of the main predictions of the coevolution theory. Since the partition energy is reflective of the protein structure and therefore of the enzymatic catalysis, the latter might really have been the main selective pressure that would have promoted the origin of the genetic code. Indeed, we observe that the β-strands show an optimization percentage of 95.45%; so it is possible to hypothesize that they might have become the object of selection during the origin of the genetic code, conditioning the choice of biosynthetic relationships between amino acids. (iv) The finding that the polarity of amino acids is less optimized than their partition energy in the genetic code table might be interpreted against the physicochemical theories of the origin of the genetic code because these would suggest, for example, that a very high optimization of the polarity of amino acids in the code could be an expression of interactions between amino acids and codons or anticodons, which would have promoted its origin. This might now become less sustainable, given the very high optimization that is instead observed in favor of the partition energy but not polarity. Finally, (v) the very high optimization of the partition energy of amino acids would seem to make a neutral origin of error minimization, i.e. of the ability of the genetic code to buffer, for example, the deleterious effects of translation errors, very unlikely. Indeed, an optimization of about 100% would seem that it might not have been achieved by a simple neutral process, but this ability should probably have been generated instead by the intervention of natural selection. In actual fact, we show that the neutral theory of the origin of error minimization has been falsified for the model analyzed here. Therefore, we will discuss our observations within the theories proposed to explain the origin of the organization of the genetic code, reaching the conclusion that the coevolution theory is the most strongly corroborated theory.

Novel approach to transform UML Sequence diagram to Activity diagram

Unified Modelling Language (UML) is currently accepted as a defacto standard language for modeling the software in the software industry. It will allow to implement object oriented concepts to model the software system. It provides a complete pictographic representation of software. Broadly these UML diagrams are classified into two groups viz. Structural diagrams and Behavioral diagrams. The sequence diagrams and Activity diagrams belongs to the second group i.e. behavioral diagrams. The sequence diagram represents the sequence of messages flowing from one object to another and activity diagram represents the flow of activities one after the other in a system. In this paper, we are proposing an automated tool which transforms the sequence diagram (which is represented in the table format) into activity diagram. The sequence diagram which is represented in the three column table called sequence table comprises various components of sequence diagram like objects, interactions, messages, alternations, iterations, loops, etc. The proposed tool reads the sequence table and converts the entire table components into the equivalent Activity table. Further the tool reads the activity table and then transforms to its equivalent activity diagram.

Effect of solid–gas damping on dynamic characteristics of aerostatic guideway

In order to study the influence mechanism of the motion accuracy of the air static pressure guide system, this article combines the internal transmission law of the driving part of the table and the coupling analysis of solid damping and micro-scale gas damping and establishes the stepping motor, ball screw, nut, and motion table. The four-degree-of-freedom operation model was used to study the response simulation and dynamic characteristics of the entire table under the influence of various components. Combined with the damping characteristics extracted from the experiment, the influence mechanism of micro-gap solids and gas damping on the motion accuracy of the air-floating table is analyzed, and the optimal structural scheme that can effectively improve the accuracy and stability is proposed to improve the performance of the air-floating table and ultra-precision machine tools, processing accuracy to solve key technical problems in improving nano-machining accuracy.

Simple and Generic Constructions of Succinct Functional Encryption

We propose simple and generic constructions of succinct functional encryption. Our key tool is exponentially-efficient indistinguishability obfuscator (XIO), which is the same as indistinguishability obfuscator (IO) except that the size of an obfuscated circuit (or the running-time of an obfuscator) is slightly smaller than that of a brute-force canonicalizer that outputs the entire truth table of a circuit to be obfuscated. A “compression factor” of XIO indicates how much XIO compresses the brute-force canonicalizer. In this study, we propose a significantly simple framework to construct succinct functional encryption via XIO and show that XIO is a powerful enough to achieve cutting-edge cryptography. In particular, we prove the followings: Single-key weakly succinct secret-key functional encryption (SKFE) is constructed from XIO (even with a bad compression factor) and one-way function. Single-key weakly succinct public-key functional encryption (PKFE) is constructed from XIO with a good compression factor and public-key encryption. Single-key weakly succinct PKFE is constructed from XIO (even with a bad compression factor) and identity-based encryption.

Sorting Out Fuzzy Transportation Problems via ECCT and Standard Deviation

A well-organized arithmetical procedure entitled standard deviation is employed to find the optimum solution in this paper. This technique has been divided into two parts. The first methodology deals with constructing the entire contingency cost table, and the second deals with optimum allocation. In this work, the method of magnitude is used for converting fuzzy numbers into crisp numbers as this method is better than the existing methods. This technique gives a better optimal solution than other methods. A numerical example for the new method is explained, and the authors compared their method with existing methods such as north west corner method, least cost method, and Vogel's approximation method.