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Alan Turing's "Computing Machinery and Intelligence," published in 1950, is one of the founding texts in the field of artificial intelligence (AI), although the term was not coined until 1958, 4 years after his death. From the treatment of human intelligence as computational and the brain as mechanical to the comparison of animals to machines to the disregard for the materiality of computers to programming as a stand-in for procreation to fiction-inspired science, many of the core tenets that have shaped the field of AI have their origins in Turing's paper. A close analysis of the paper exposes some of the problematic logic underlying these tenets that are now proving damaging for both society and the planet. [ABSTRACT FROM AUTHOR]

The recent adoption of deep learning-based models for the processing and coding of multimedia signals has brought noticeable gains in performance, which have established deep learning-based solutions as the uncontested state-of-the-art both for computer vision tasks, targeting machine consumption, as well as, more recently, coding applications, targeting human visualization. Traditionally, applications requiring both coding and computer vision processing require first decoding the bitstream and then applying the computer vision methods to the decompressed multimedia signals. However, the adoption of deep learning-based solutions enables the use of compressed domain computer vision processing, with gains in performance and computational complexity over the decompressed domain approach. For point clouds (PCs), these gains have been demonstrated in the single available compressed domain computer vision processing solution, named Compressed Domain PC Classifier, which processes JPEG Pleno PC coding (PCC) compressed streams using a PC classifier largely compatible with the state-of-the-art spatial domain PointGrid classifier. However, the available Compressed Domain PC Classifier presents strong limitations by imposing a single, specific input size which is associated to specific JPEG Pleno PCC configurations; this limits the compression performance as these configurations are not ideal for all PCs due to their different characteristics, notably density. To overcome these limitations, this paper proposes the first Adaptive Compressed Domain PC Classifier solution which includes a novel adaptive bridge model that allows to process the JPEG Pleno PCC encoded bit streams using different coding configurations, now maximizing the compression efficiency. Experimental results show that the novel Adaptive Compressed Domain PC Classifier allows JPEG PCC to achieve better compression performance by not imposing a single, specific coding configuration for all PCs, regardless of its different characteristics. Moreover, the added adaptability power can achieve slightly better PC classification performance than the previous Compressed Domain PC Classifier and largely better PC classification performance (and lower number of weights) than the PointGrid PC classifier working in the decompressed domain. [ABSTRACT FROM AUTHOR]

This present paper is inspired by one of the questions posed by Okeke (Results Math 78(96):1-30, 2023, see Remark 2.10b). In particular, we aim to develop a robust computer code based on the theoretical results obtained in Okeke (2023), which determines the polynomial solutions of the following functional equation, 0.1 ∑ i = 1 n γ i F (a i x + b i y) = ∑ j = 1 m (α j x + β j y) f (c j x + d j y) , for all x , y ∈ R , γ i , α j , β j ∈ R , and a i , b i , c j , d j ∈ Q , and their special forms. The primary motivation for writing such a computer code is that solving even simple equations belonging to class (0.1) needs long and tiresome calculations. Therefore, one of the advantages of such a computer code is that it allows us to solve complicated problems quickly, easily, and efficiently. Additionally, the computer code will significantly improve the level of accuracy in calculations. Along with that, there is also the factor of speed. We point out that the computer code will operate with symbolic calculations provided by the programming language Python, which means that it does not contain any numerical or approximate methods, and it yields the exact solutions of the equations considered. [ABSTRACT FROM AUTHOR]

This commentary on John Symons' and Jack Horner's paper, besides sharing its main argument, challenges the authors' statement that there is no effective method to evaluate software-intensive systems as a distinguishing feature of software intensive science. It is underlined here how analogous methodological limitations characterise the evaluations of empirical systems in non-software intensive sciences. The authors' claim that formal methods establish the correctness of computational models rather than of the represented programme is here compared with the empirical adequacy problem typifying the model-based reasoning approach in physics, and the remark that testing all the paths of a software-intensive system is unfeasible is related to the enumerative induction problem in the justification of empirical law-like hypotheses in non-software intensive sciences. [ABSTRACT FROM AUTHOR]

The inverse degree index, also called inverse index, first attracted attention through numerous conjectures generated by the computer programme Graffiti. Since then its relationship with other graph invariants has been studied by several authors. In this paper we obtain new inequalities involving the inverse degree index, and we characterize graphs which are extremal with respect to them. In particular, we obtain several inequalities relating the inverse degree index with the first and second Zagreb indices, the general first and second Zagreb indices, the Forgotten index, the general sum-connectivity index, the Sombor index and the misbalance indeg index, and several parameters of the molecular graph as the number of vertices, the number of edges, the minimum degree and the maximum degree. Also, we compute the inverse degree index for some classes of chemical graphs. Furthermore, some applications are given to the study of the physicochemical properties of three classes of compounds: polyaromatic hydrocarbons, polychlorobiphenyls, and octane isomers. [ABSTRACT FROM AUTHOR]

Slope stability is an important problem in the field of geotechnical engineering. In order to widen the application range of upper bound limit analysis in engineering practice, this paper analyzes layered distribution characteristics of slope soil and establishes horizontal layers slope failure mechanism which satisfies the separation of velocity, then proposes calculation method for external force power and internal energy dissipation power using discrete algorithm. On this basic, this paper prepares cycle flow of slope stability analysis by upper bound limit principle and strength reduction principle, and develops stability analysis system by computer programming technology. Taking typical mine excavation slope as engineering background and calculates stability coefficient corresponding to different slope angles and evaluate analysis results accuracy by combining with limit equilibrium method. The results show that the stability coefficient error rate of two methods is between 3 and 5%, which can satisfy requirements of engineering practice. Moreover, stability coefficient obtained by upper bound limit analysis is an upper limit solution, and calculation errors are easy to eliminate, so it has certain applicability in slope engineering practice. [ABSTRACT FROM AUTHOR]

This special section is devoted to a selection of papers that appeared originally in the Proceedings of TACAS 2001, the 7th International Conference on Tools and Algorithms for the Construction and Analysis of Systems [1] which took place in Genova, Italy in April 2001 as a constituent event of the European joint conferences on theory and Practice of Software. All papers present approaches, tools and algorithms that aim at extending the scope of formal techniques (coverage of systems specifications, data structures, size, and their trade-offs) for validation, verification, and testing of software systems. They are by no means a complete account of the numerous ways in which real software and software systems may become subject to rigorous investigation, but they provide an interesting sampling of novel approaches towards scalability of formal methods-based validation. [ABSTRACT FROM AUTHOR]

In Sweden, as in many other countries, programming has been added to the curriculum in recent years. This paper explores how and under what conditions programming is transformed into teaching in technology education. Teachers in grade 7–9 were interviewed about what and how they teach about programming in the context of technology education, and what influenced the choices they made. Data was analysed using content analysis. The results suggest that teachers mainly see programming as a medium to explore and understand technological systems and construction work. The results further implies that teachers are uncertain of what programming means in terms of practices and concepts, and how programming knowledge can be assessed. The process of transformation presents teachers with several challenges, related to their own knowledge of programming, quality of teaching materials, and knowing pupils' prior knowledge about programming. In addition, the results indicate that technology teachers work in isolation. In consequence, the intended interdisciplinary collaboration between technology and mathematics teachers on programming is largely absent. [ABSTRACT FROM AUTHOR]

Metaphors in gesture and speech play a pivotal role in the way that programming concepts are presented in the classroom. However, little is known about the function of teachers' metaphors in practice. This study aims to explore teachers' use of metaphors in gesture and speech in a lecture on programming. Based on video observations of three upper secondary teachers, we employ Metaphor Identification Procedure (MIP) and Metaphor Identification for Gesture Guidelines (MIG-G) as methodological tools for identifying metaphoric speech and gestures related to programming concepts. The results of the study reveal that the gestures of the three teachers mainly function in two ways: (1) to add spatial properties to a programming concept and (2) to provide additional imagery for a programming concept. Consequently, the gestures identified in this study reduce the communicative burden of teachers' speech. Furthermore, the study reveals that teachers' gestures serve as means for making abstract concepts more tangible. For example, gestures concerning the abstract term "data" can generally be related to an object that could be received or moved. Hence, despite its metaphorical origin, data could be considered a graspable aspect of programming. Furthermore, spatial gestures enable the teachers to communicate programming processes in a tangible way, for example assigning programming processes a forward direction. Theoretical implications, potential implications for teaching and future research are discussed in the paper. [ABSTRACT FROM AUTHOR]

This paper proposes a synchronous measurement system of four position-independent geometric errors (PIGEs) and two position-dependent geometric errors (PDGEs) for the rotary axis in five-axis machine tools. The measuring instruments used in this system include a touch-trigger probe and two standard calibration spheres. The main contribution of this paper simultaneously and directly measures four PIGEs and two PDGEs (axial and angular positioning errors) through only one measuring process. It is expected to improve the deficiencies of previous studies measuring PIGEs and PDGEs separately. The geometric errors of the C-axis of a mill-turn machine tool MT-540 were analyzed. The calculation process includes the establishment of the mathematical model of the machine and geometric error equations. The least squares method was used to solve the linear overdetermined system and calculate the values of the geometric errors. Before solving the geometric errors, the accuracy of the calculation process was verified by using the simulated method. The simulation results also confirm the feasibility of this measurement system. Then the data obtained from the experiments were used to calculate the geometric errors of the machine tool. During the experiments, the calibration procedure of the touch-trigger probe was calibrated. After the calibration procedure was completed, the mechanical coordinate values of the two standard calibration balls were measured. The geometric error equations were programmed on a computer, and the data of calibration spheres obtained from the experimental measurements were substituted into the program to calculate the four PIGEs and two PDGEs. [ABSTRACT FROM AUTHOR]

The inverse degree index, also called inverse index, first attracted attention through numerous conjectures generated by the computer programme Graffiti. Since then its relationship with other graph invariants has been studied by several authors. In this paper we obtain new inequalities involving the inverse degree index, and we characterize graphs which are extremal with respect to them. Also, a QSPR study of this index and its exponential extension was performed. [ABSTRACT FROM AUTHOR]

We seek a unified and distinctive citation description of both journals and individuals. The journal impact factor has a restrictive definition that constrains its extension to individuals, whereas the h-index for individuals can easily be applied to journals. Going beyond any single parameter, the shape of each negative slope Hirsch curve of citations vs. rank index is distinctive. This shape can be described through five minimal parameters or 'flags': the h-index itself on the curve; the average citation of each segment on either side of h; and the two axis endpoints. We obtain the five flags from real data for two journals and 10 individual faculty, showing they provide unique citation fingerprints, enabling detailed comparative assessments. A computer code is provided to calculate five flags as the output, from citation data as the input. Since papers (citations) can form nodes (links) of a network, Hirsch curves and five flags could carry over to describe local degree sequences of general networks. [ABSTRACT FROM AUTHOR]

We are interested in understanding how university students learn to use programming as a tool for "authentic" mathematical investigations (i.e., similar to how some mathematicians use programming in their research work). The theoretical perspective of the instrumental approach offers a way of interpreting this learning in terms of development of schemes by students; these development processes are called instrumental geneses. Nevertheless, how these schemes evolve has not been fully explained. In this paper, we propose to enrich the theoretical frame of the instrumental approach by a model of scheme evolution and to use this new approach to investigate learning to use programming for pure and applied mathematics investigation projects at the university level. We examine the case of one student completing four investigation projects as part of a course workload. We analyze the productive and constructive aspects of the student's activity and the dynamic aspect of the instrumental geneses by identifying the mobilization and evolution of schemes. We argue that our approach constitutes a new theoretical and methodological contribution deepening the understanding of students' instrumented learning processes. Identifying instrumented schemes illuminates in particular how mathematical knowledge and programming knowledge are combined. The analysis in terms of scheme evolutions reveals which characteristics of the situations lead to such evolutions and can thus inform the design of teaching. [ABSTRACT FROM AUTHOR]

Despite major improvements over the past several decades in computer methods for analyzing and synthesizing exploration and site investigation geological data for engineering purposes, which should have decreased project risk, unexpected failures and construction problems still occur. Often, this unexpectedness can be tied back to inadequate structural geological understanding of actual site-specific conditions. Part of this diminished appreciation of structural geological controls on rockmass behaviour can likely be attributed to inappropriate use of computational geostatistics, block modelling and geomechanics computer codes, without significant structural geological input. Part may be because of inadequate domaining in the raw data analysis phase, such that no differentiation was ever made between uncertainties due to true natural variability versus those due to data inadequacy. Modelled data error issues cannot easily be resolved once mixing and smearing of parameters have occurred as a result of earlier inappropriate synthesis of an uncontrolled database. The increased use, industry-wide, of inadequately calibrated, often totally unverified, geomechanics computer modelling for design of civil or mining projects is a worrying trend that needs reversing. Much more attention needs to be paid to properly sub-dividing project sites into realistic geological entities through use of rigorous geological structural domaining techniques, such that much better understanding is gained of project-specific geological risk. This in turn will lead to improved reliability and representativeness in project geomechanical parameter selection for use in design. This paper attempts to set out some guidelines to help practitioners undertake more rigorous domaining, as an aid to parameter selection for design. [ABSTRACT FROM AUTHOR]

This document is a guest editorial for a special issue of the journal "Programming & Computer Software" titled "Recent Trends on Advanced Computing: The Converging Technologies." The issue features research and practical implementation results from researchers and industry experts in computer science, engineering, and technology. The papers cover a range of topics including microservices, software quality, user engagement on social media, non-functional requirements, medical software architecture, fallacies in political speeches, intelligent learning environments, and more. The guest editors for this special issue are Prof. Dr. Andrei Tchernykh, Prof. Reyes Juárez Ramírez, Dr. Esteban Mocskos, and Prof. Sergio Nesmachnow. [Extracted from the article]

Models of natural supersymmetry give rise to a weak scale m weak ∼ m W , Z , h ∼ 100 GeV without any (implausible) finetuning of independent contributions to the weak scale. These models, which exhibit radiatively driven naturalness (RNS), are expected to arise from statistical analysis of the string landscape wherein large soft terms are favored, but subject to a not-too-large value of the derived weak scale in each pocket universe of the greater multiverse. The string landscape picture then predicts, using the Isajet SUSY spectra generator Isasugra, a statistical peak at m h ∼ 125 GeV with sparticles generally beyond current LHC search limits. In this paper, we investigate how well these conclusions hold up using other popular spectra generators: SOFTSUSY, SPHENO and SUSPECT (SSS). We built a computer code DEW4SLHA which operates on SUSY Les Houches Accord files to calculate the associated electroweak naturalness measure Δ EW . The SSS generators tend to yield a Higgs mass peak ∼ 125 –127 GeV with a superparticle mass spectra rather similar to that generated by Isasugra. In an Appendix, we include loop corrections to Δ EW in a more standard notation. [ABSTRACT FROM AUTHOR]

Sand control measures in horizontal wells are mainly based on screens. Horizontal wells have a certain length of horizontal displacement and the kick-off section with large curvature. Therefore, it is necessary to evaluate the safety of the screen downhole run before it runs into the hole, in order to minimize the running risk. In this paper, the pipe string is divided into sections, and the equivalent force for each elementary section is analyzed. Then, the axial force and friction resistance of the pipe string are calculated. According to the buckling criterion of the string and the mechanical strength theory, this paper evaluates whether the screen can safely and smoothly run down to the bottom of the well. This analytical method of solving the physical model is feasible and easy to understand and can be implemented using computer programming applications. [ABSTRACT FROM AUTHOR]

Coding is defined as the "process of assigning a code (command/rule)" (http://Techopedia.com) that allows a machine or a person to act or move (McLennan, https://www.naeyc.org/resources/pubs/tyc/feb2017/creating-coding-stories-and-games, 2017). Though machines operated by a coding system are common in children's everyday lives, there has been a lack of resources on how to expose young children to coding in a developmentally appropriate manner. This paper aims to address this gap in the field of early education by providing developmentally appropriate guidelines for teachers of young children to utilize when implementing coding in their classrooms. Specifically, this paper focuses on unplugged coding activities that do not involve computers or computer programming and presents practical examples of tasks with algorithm designs, including a detailed step-by-step instruction set for solving a problem or completing a task (Tynker, https://www.tynker.com/blog/articles/ideas-and-tips/how-to-explain-algorithms-to-kids/, 2019). This paper presents coding practices that involve children's daily lives, incorporating sequential and directional commands and coding grids (coding sheet). [ABSTRACT FROM AUTHOR]

The cumulative damage effects of surrounding rock under single full-face blasting and multiple full-face blasting of a large cross-section tunnel are comparatively studied in this paper. The damage processes of the single and multiple full-face blasting of the tunnel are simulated by the established rock damage model embedded into the LS-DYNA computer code through its user subroutines and a cumulative damage simulation technology in the LS-DYNA. The simulation results are verified against field test data. The results demonstrate that the numerically predicted peak particle velocity (PPV) of the surrounding rock under multiple full-face blasting is more consistent with field test data than that under single full-face blasting, which indicates the advantages of multiple full-face blasting in comparison to single full-face blasting in simulating the blasting process of a tunnel. The maximum damage depth in the middle of the tunnel invert is mostly affected by multiple full-face blasting. Both the maximum damage depth and the maximum PPV occur in the middle of the tunnel invert under single and multiple full-face blasting. Based on the defined damage threshold Dcr and the modeled maximum damage depth of the surrounding rock, the influence of initiation sequence on the critical PPV for rock damage is analyzed, and a critical PPV of rock damage is proposed to provide a safety criterion for tunnel blasting excavation. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is one of the most powerful platforms that incorporates several other technological components within itself. The IoT ecosystem comprises devices, communications, protocols, analytics, cloud, automation, etc. Its magnitude keeps on increasing with the addition of tools and services. While IoT has many advantages like connectivity, efficiency, and convenience, it is a known fact that privacy and security issues are prevalent in the IoT network. To minimize the security and privacy issues, we propose a blockchain-based solution. In this paper, we design policies based on smart contacts, which is a self-enforcing agreement embedded in computer code managed by a blockchain. We propose three different policies: Hardware and Device Security Policies, Access and Authentication policies, and Application security for the IoT network. Since blockchain-based solutions ensure trust and stability, this may be one of the most robust techniques to alleviate the IoT network's security and privacy issues. Also, we calculate the throughput and latency of the IoT enabled blockchain network and compare the power consumption of the IoT device at the time of data request with other proposed systems. [ABSTRACT FROM AUTHOR]

During a conventional multiple-point statistics simulation, the algorithm may not find a matched neighborhood in the training image for some unsimulated pixels. These pixels are referred to as the dead-end pixels; the existence of the dead-end pixels means that multiple-point statistics simulation is not a simple sequential simulation. In this paper, the multiple-point statistics simulation is cast as a combinatorial optimization problem, and the efficient backtracking algorithm is developed to solve this optimization problem. The efficient backtracking consists of backtracking, forward checking, and conflict-directed backjumping algorithms that are introduced and discussed in this paper. This algorithm is applied to simulate multiple-point statistics properties of some synthetic training images; the results show that no anomalies occurred in any of the produced realizations as opposed to previously published methods for solving the dead-end pixels. In particular, in simulating a channel system, all the channels generated by this method are continuous, which is of paramount importance in fluid flow simulation applications. The results also show that the presence of hard data does not degrade the quality of the generated realizations. The presented method provides a robust algorithmic framework for performing MPS simulation. [ABSTRACT FROM AUTHOR]

The research of developing efficient methodologies for constructing optimal experimental designs has been very active in the last decade. Uniform design is one of the most popular approaches, carried out by filling up experimental points in a determinately uniform fashion. Applications of coding theory in experimental design are interesting and promising. Quaternary codes and their binary Gray map images attracted much attention from those researching design of experiments in recent years. The present paper aims at exploring new results for constructing uniform designs based on quaternary codes and their binary Gray map images. This paper studies the optimality of quaternary designs and their two and three binary Gray map image designs in terms of the uniformity criteria measured by: the Lee, wrap-around, symmetric, centered and mixture discrepancies. Strong relationships between quaternary designs and their two and three binary Gray map image designs are obtained, which can be used for efficiently constructing two-level designs from four-level designs and vice versa. The significance of this work is evaluated by comparing our results to the existing literature. [ABSTRACT FROM AUTHOR]

It is one of fundamental theorems in graph theory that every even graph has a circuit decomposition. This classical result for ordinary graphs is extended in this paper for uniform bridgeless hypergraphs if the degree of every vertex is even. One of major open problems for shortest circuit cover was a conjecture proposed by Itai and Rodeh (Automata, Languages and Programming, Lecture Notes in Computer Science, vol. 62, pp. 289-299. Springer, Berlin, 1978) that every bridgeless graph G has a circuit cover of total length at most |E|+|V|-1. This conjecture was solved by Fan (J Combin Theory Ser B 74:353-367, 1998) for ordinary graphs, and is extended in this paper for bridgeless hypergraphs. [ABSTRACT FROM AUTHOR]

This paper reports on a four-year project that aims to raise the abstraction level through the use of model-driven engineering (MDE) techniques in the development of scientific applications relying on high-performance computing. The development and maintenance of high-performance scientific computing software is reputedly a complex task. This complexity results from the frequent evolutions of supercomputers and the tight coupling between software and hardware aspects. Moreover, current parallel programming approaches result in a mixing of concerns within the source code. Our approach relies on the use of MDE and consists in defining domain-specific modeling languages targeting various domain experts involved in the development of HPC applications, allowing each of them to handle their dedicated model in a both user-friendly and hardware-independent way. The different concerns are separated thanks to the use of several models as well as several modeling viewpoints on these models. Depending on the targeted execution platforms, these abstract models are translated into executable implementations by means of model transformations. To make all of these effective, we have developed a tool chain that is also presented in this paper. The approach is assessed through a multi-dimensional validation that focuses on its applicability, its expressiveness and its efficiency. To capitalize on the gained experience, we analyze some lessons learned during this project. [ABSTRACT FROM AUTHOR]

In traditional preference-based multi-objective optimization, the reference points in different regions often impact the performance of the algorithms so that the region of interest (ROI) cannot easily be obtained by the decision maker (DM). In dealing with many-objective optimization problems, the objective space is filled with non-dominated solutions in terms of the Pareto dominance relationship, since the dominance relationship cannot differentiate the mutual relationship between the solutions. To solve the above problems, this paper proposes a new selection mechanism with two main steps. First, we construct a preference radius to divide the whole population into two distinct parts: a dispreferred solution set and a preferred solution set. Second, the algorithm selects the optimal solutions in the preferred solution set by means of the Pareto dominance relationship. If the number of the obtained solutions does not satisfy the quantity's upper limit, it selects those dispreferred solutions which have smaller distances to the reference direction until the number matches the size of the population. Experimental results show that the algorithm applying the mechanism is able to adapt to different reference points in varying regions in objective space. Moreover, it assists the DM in obtaining different sizes of ROI by adjusting the length of the radius of ROI. In dealing with many-objective problems, the mechanism can dramatically contribute to the convergence of an algorithm proposed in this paper, in comparison with other two state-of-the-art algorithms: g-dominance and r-dominance. Thus, this paper provides a new way to deal with user preference-based multi-objective optimization problems. [ABSTRACT FROM AUTHOR]

Over recent years, evolutionary computation research has begun to emphasize the issue of generalization. Instead of evolving solutions that are optimized for a particular problem instance, the goal is to evolve solutions that can generalize to various different scenarios. This paper compares objective-based search and novelty search on a set of generalization oriented experiments for a navigation task using grammatical evolution (GE). In particular, this paper studies the impact that the training set has on the generalization of evolved solutions, considering: (1) the training set size; (2) the manner in which the training set is chosen (random or manual); and (3) if the training set is fixed throughout the run or dynamically changed every generation. Experimental results suggest that novelty search outperforms objective-based search in terms of evolving navigation behaviors that are able to cope with different initial conditions. The traditional objective-based search requires larger training sets and its performance degrades when the training set is not fixed. On the other hand, novelty search seems to be robust to different training sets, finding general solutions in almost all of the studied conditions with almost perfect generalization in many scenarios. [ABSTRACT FROM AUTHOR]

This paper draws attention to the growing adoption of web and mobile apps in the enterprise, typically supported by digital storage in the cloud. While these developments offer several advantages, they also pose challenges for workers who must make sense of increasingly complex software configurations – with apps accessible from multiple devices (typically supporting different features or capabilities) and used alongside legacy enterprise software. We investigate how workers navigate these environments through a qualitative study of the work practices of employees in an app-enhanced organization. Our findings focus on two sets of practices. The first involves appraising what software programs and software/device combos offer what features, what we refer to as software calculus. The second involves orienting towards data formats and database structures that underlie specific software programs and their interactions with specific devices, what we label data thinking. Building on prior work on the role of materiality in CSCW, our findings set out a call for further attention to the material and lively dimensions of software and the emergent challenges they pose for contemporary work practices. [ABSTRACT FROM AUTHOR]

This paper focuses on the evaluation of the seismic performance of Cerere, the central sculpture of Bartolomeo Ammannati's Juno Fountain, currently located in Florence, at the Museum of Bargello. A 3D geometrical model based on a laser scanner survey has been obtained and employed to build the finite element model (FEM) used in the analyses. The seismic response of the sculpture has been checked by performing different dynamic analyses, applying three three-dimensional spectrum-compatible ground motions, and using different computer codes and assumptions. The considered numerical models differ from each other regarding the material behavior (linear and non-linear) and the connection between the statue and its pedestal. The obtained results reveal that this latter assumption affects very much the dynamic response of the system. The role played by the possible assumptions regarding the number of components constituting the seismic input and the amount of friction between the pedestal and the statue are also discussed. [ABSTRACT FROM AUTHOR]

Rock strength variation is closely related to its microstructure. With the development of computer technology, the numerical model of rocks can be constructed via computer programming, and the numerical simulation avoids a mass of redundant experimental tests and usually limited by the samples retrieved from the sub-surfaces. In previous studies, the microstructure in the numerical model is generated randomly. In this paper, a novel methodology for generating the polycrystalline rock microstructure by a Voronoi grain-based model with particle growth is proposed. The 3D Voronoi tessellations in this numerical model generation procedure do not consist of random poly-crystals; the distribution of the poly-crystals varies in shapes and sizes, which represent different mineral grains, and is determined by petrographic data with the 3D particle growth method. The uniaxial compression tests and tension tests are simulated via a combined FDEM and cohesive crack propagation model. The results demonstrate that the numerical simulation agrees well with the experimental study. More importantly, the fracture patterns in the micro-scale are gained, similar to the results obtained from laboratory experiments. The novel Voronoi grain-based model with the particle growth method can reconstruct the microstructure of polycrystalline rocks and provide further information in understanding the micro-behaviors of rock materials. [ABSTRACT FROM AUTHOR]

von Neumann architecture based computers isolate computation and storage (i.e. data is shuttled between computation blocks (processor) and memory blocks). The to-and-fro movement of data leads to a fundamental limitation of modern computers, known as the Memory wall. Logic in-Memory (LIM)/In-Memory Computing (IMC) approaches aim to address this bottleneck by directly computing inside memory units thereby eliminating energy-intensive and time-consuming data movement. Several recent works in literature, propose realization of logic function(s) directly using arrays of emerging resistive memory devices (example- memristors, RRAM/ReRAM, PCM, CBRAM, OxRAM, STT-MRAM etc.), rather than using conventional transistors for computing. The logic/embedded-side of digital systems (like processors, micro-controllers) can greatly benefit from such LIM realizations. However, the pure storage-side of digital systems (example SSDs, enterprise storage etc.) will not benefit much from such LIM approaches as when memory arrays are used for logic they lose their core functionality of storage. Thus, there is the need for an approach complementary to existing LIM techniques, that's more beneficial for the storage-side of digital systems; one that gives compute capability to memory arrays not at the cost of their existing stored states. Fundamentally, this would require memory nanodevice arrays that are capable of storing and computing simultaneously. In this paper, we propose a novel 'Simultaneous Logic in-Memory' (SLIM) methodology which is complementary to existing LIM approaches in literature. Through extensive experiments we demonstrate novel SLIM bitcells (1T-1R/2T-1R) comprising non-filamentary bilayer analog OxRAM devices with NMOS transistors. Proposed bitcells are capable of implementing both Memory and Logic operations simultaneously. Detailed programming scheme, array level implementation, and controller architecture are also proposed. Furthermore, to study the impact of proposed SLIM approach for real-world implementations, we performed analysis for two applications: (i) Sobel Edge Detection, and (ii) Binary Neural Network- Multi layer Perceptron (BNN-MLP). By performing all computations in SLIM bitcell array, huge Energy Delay Product (EDP) savings of ≈75× for 1T-1R (≈40× for 2T-1R) SLIM bitcell were observed for edge-detection application while EDP savings of ≈3.5× for 1T-1R (≈1.6× for 2T-1R) SLIM bitcell were observed for BNN-MLP application respectively, in comparison to conventional computing. EDP savings owing to reduction in data transfer between CPU ↔ memory is observed to be ≈780× (for both SLIM bitcells). [ABSTRACT FROM AUTHOR]

This paper explores the history of ELIZA, a computer programme approximating a Rogerian therapist, developed by Jospeh Weizenbaum at MIT in the 1970s, as an early AI experiment. ELIZA's reception provoked Weizenbaum to re-appraise the relationship between 'computer power and human reason' and to attack the 'powerful delusional thinking' about computers and their intelligence that he understood to be widespread in the general public and also amongst experts. The root issue for Weizenbaum was whether human thought could be 'entirely computable' (reducible to logical formalism). This also provoked him to re-consider the nature of machine intelligence and to question the instantiation of its logics in the social world, which would come to operate, he said, as a 'slow acting poison'. Exploring Weizenbaum's 20th Century apostasy, in the light of ELIZA, illustrates ways in which contemporary anxieties and debates over machine smartness connect to earlier formations. In particular, this article argues that it is in its designation as a computational therapist that ELIZA is most significant today. ELIZA points towards a form of human–machine relationship now pervasive, a precursor of the 'machinic therapeutic' condition we find ourselves in, and thus speaks very directly to questions concerning modulation, autonomy, and the new behaviorism that are currently arising. [ABSTRACT FROM AUTHOR]

In the context of computer experiments, metamodels are largely used to represent the output of computer codes. Among these models, Gaussian process regression (kriging) is very efficient see e.g Snelson (Flexible and efficient Gaussian process models for machine learning. ProQuest LLC, Ann Arbor, MI. Thesis (Ph.D.)–University of London, University College London, London, 2008). In high dimension that is with a large number of input variables, but with few observations, the estimation of the parameters with a classical anisotropic kriging can be completely inaccurate. Because there are equal numbers of ranges and input variables the optimization space becomes too large compared to available information. One way to overcome this drawback is to use an isotropic kernel that only depends on one parameter. However this model is too restrictive. The aim of this paper is twofold. Our first objective is to propose a smooth kernel with as few parameters as warranted. We introduce a kernel which is a tensor product of few isotropic kernels built on well-chosen subgroup of variables. The main difficulty is to find the number and the composition of the groups. Our second objective is to propose algorithmic strategies to overcome this difficulty. Four forward strategies are proposed. They all start with the simplest isotropic kernel and stop when the best model according to BIC criterion is found. They all show very good accuracy results on simulation test cases. But one of them is more efficient. Tested on a real data set, our kernel shows very good prediction results. [ABSTRACT FROM AUTHOR]

The MadGraph5_aMC@NLO framework aims to automate all types of leading- and next-to-leading-order-accurate simulations for any user-defined model that stems from a renormalisable Lagrangian. In this paper, we present all of the key ingredients of such models in the context of supersymmetric theories. In order to do so, we extend the FeynRules package by giving it the possibility of dealing with different renormalisation options that are relevant to supersymmetric models. We also show how to deal with the problem posed by the presence of narrow resonances, thus generalising the so-called on-shell subtraction approaches. We extensively compare our total rate results with those of both Prospino2 and Resummino, and present illustrative applications relevant to the 13 TeV LHC, both at the total-rate and differential levels. The computer programmes that we have used to obtain the predictions presented here are all publicly available. [ABSTRACT FROM AUTHOR]

Cascaded helical flux compression generators (Cascaded-HFCG) are widely used to produce powerful current pulses in many industries, while there is no specific method to design these generators in any books or articles. In this paper, firstly some mechanical and electrical criteria are described, and then an algorithm is proposed based on these criteria. A computer code is written using MATLAB based on the proposed algorithm and some programs are prepared in COMSOL to calculate electrical parameters of the generators which can be used in the design procedure. The validity of the proposed algorithm is verified by simulation. [ABSTRACT FROM AUTHOR]

Aiming at efficient similarity search, hash functions are designed to embed high-dimensional feature descriptors to low-dimensional binary codes such that similar descriptors will lead to binary codes with a short distance in the Hamming space. It is critical to effectively maintain the intrinsic structure and preserve the original information of data in a hashing algorithm. In this paper, we propose a novel hashing algorithm called Latent Structure Preserving Hashing (LSPH), with the target of finding a well-structured low-dimensional data representation from the original high-dimensional data through a novel objective function based on Nonnegative Matrix Factorization (NMF) with their corresponding Kullback-Leibler divergence of data distribution as the regularization term. Via exploiting the joint probabilistic distribution of data, LSPH can automatically learn the latent information and successfully preserve the structure of high-dimensional data. To further achieve robust performance with complex and nonlinear data, in this paper, we also contribute a more generalized multi-layer LSPH (ML-LSPH) framework, in which hierarchical representations can be effectively learned by a multiplicative up-propagation algorithm. Once obtaining the latent representations, the hash functions can be easily acquired through multi-variable logistic regression. Experimental results on three large-scale retrieval datasets, i.e., SIFT 1M, GIST 1M and 500 K TinyImage, show that ML-LSPH can achieve better performance than the single-layer LSPH and both of them outperform existing hashing techniques on large-scale data. [ABSTRACT FROM AUTHOR]

The future Internet is expected to connect billions of people, things and services having the potential to deliver a new set of applications by deriving new insights from the data generated from these diverse data sources. This highly interconnected global network brings new types of challenges in analysing and making sense of data. This is why machine learning is expected to be a crucial technology in the future, in making sense of data, in improving business and decision making, and in doing so, providing the potential to solve a wide range of problems in health care, telecommunications, urban computing, and others. Machine learning algorithms can learn how to perform certain tasks by generalizing examples from a range of sampling. This is a totally different paradigm than traditional programming language approaches, which are based on writing programs that process data to produce an output. However, choosing a suitable machine learning algorithm for a particular application requires a substantial amount of time and effort that is hard to undertake even with excellent research papers and textbooks. In order to reduce the time and effort, this paper introduces the TCDC (train, compare, decide, and change) approach, which can be thought as a 'Machine Learning as a Service' approach, to aid machine learning researchers and practitioners to choose the optimum machine learning model to use for achieving the best trade-off between accuracy and interpretability, computational complexity, and ease of implementation. The paper includes the results of testing and evaluating the recommenders based on the TCDC approach (in comparison with the traditional default approach) applied to 12 datasets that are available as open-source datasets drawn from diverse domains including health care, agriculture, aerodynamics and others. Our results indicate that the proposed approach selects the best model in terms of predictive accuracy in 62.5 % for regression tests performed and 75 % for classification tests. [ABSTRACT FROM AUTHOR]

The travelling salesman problem (TSP) is a well-known NP-hard problem. It is difficult to efficiently find the solution of TSP even with the large number of gene instances. Evolutionary approaches such as genetic algorithm have been widely applied to explore the huge search space of TSP. However, the feasibility constraints of TSP make it difficult to devise an effective crossover method. In this paper, we propose an improved constructive crossover for TSP. As the performance of graphics processing units (GPUs) rapidly improves, GPU-based acceleration is increasingly required for complex computation problems. Unfortunately, the constructive crossover methods cannot be easily implemented in a parallel fashion because each gene element of offspring is dependent on the previous element in the gene string. In this paper, we propose a more effective method with which large number of genes can evolve effectively by exploiting the parallel computing power of GPUs and an effective parallel approach to genetic TSP where crossover methods cannot be easily implemented in parallel fashion. [ABSTRACT FROM AUTHOR]

This paper presents a memory model with nonoverlapping memory areas (regions) for the deductive verification of C programs. This memory model uses a core language that supports arbitrary nesting of structures, unions, and arrays into other structures and allows reducing the number of user-provided annotations as a result of region analysis. This paper also describes semantics of the core language and normalizing transformations for translating an input annotated C program into a program in the core language. In addition, an encoding is proposed for modeling the memory state of a core-language program with logical formulas as described by the model semantics of the core language. For the model semantics, the soundness and completeness theorems are proved. Additional constraints on the typing context of the core-language terms are described that determine the result of the region analysis enabling the complete modeling of a limited class of programs without using additional annotations. A proof sketch for the theorem stating completeness of the proposed region analysis for a limited class of programs is presented. [ABSTRACT FROM AUTHOR]

This paper presents a study on the dynamic modeling of a high-speed over-constrained press machine. The main contribution of the paper is the development of an efficient approach to perform the dynamic analysis of a planner over-constrained mechanism. The key idea is the establishment of a more general methodology, which is to gain a deformation compatibility equation for the over-constrained mechanism on the basis of the deformation compatibility analysis at each position of the mechanisms. And this equation is then used together with the force/moment equilibrium equations obtained by the D'Alembert principle to form a total equation for the dynamics of the over-constrained mechanism. The approach is applied to a particular press machine to validate the effectiveness of the approach, and in the meantime to provide some useful information for the improvement of the design of this press machine. [ABSTRACT FROM AUTHOR]

In principal component analysis (PCA), the first few principal components possibly reveal interesting systematic patterns in the data, whereas the last may reflect random noise. The researcher may wonder how many principal components are statistically significant. Many methods have been proposed for determining how many principal components to retain in the model, but most of these assume non-standardized data. In agricultural, biological and environmental applications, however, standardization is often required. This article proposes parametric bootstrap methods for hypothesis testing of principal components when variables are standardized. Unlike previously proposed methods, the proposed parametric bootstrap methods do not rely on any asymptotic results requiring large dimensions. In a simulation study, the proposed parametric bootstrap methods for standardized data were compared with parallel analysis for PCA and methods using the Tracy–Widom distribution. Parallel analysis performed well when testing the first principal component, but was much too conservative when testing higher-order principal components not reflecting random noise. When variables are standardized, the Tracy–Widom distribution may not approximate the distribution of the largest eigenvalue. The proposed parametric bootstrap methods maintained the level of significance approximately and were up to twice as powerful as the methods using the Tracy–Widom distribution. SAS and R computer code is provided for the recommended methods. Supplementary materials accompanying this paper appear online [ABSTRACT FROM AUTHOR]

One of the main problems of coding theory is to construct codes with best possible parameters. Cyclic codes and their various generalizations, such as quasi-twisted codes, have been a fruitful source in achieving this goal. Recently, a new generalization of cyclic codes that are known as skew cyclic codes have been introduced and some new codes obtained from this class. Unlike many other types of codes considered in algebraic coding theory, skew cyclic codes require one to work in a non-commutative ring called skew polynomial ring. In this paper, we present some new linear codes obtained from the class of skew cyclic codes and describe computational challenges in working with this class of codes. [ABSTRACT FROM AUTHOR]

The inverse degree index, also called inverse index, first attracted attention through numerous conjectures generated by the computer programme Graffiti. Since then, its relationship with other graph invariants has been studied by several authors. In this paper, we obtain new inequalities involving the inverse degree index, and we characterize graphs which are extremal with respect to them. [ABSTRACT FROM AUTHOR]

Low-level parallel programming is a tedious and error-prone task, especially when combining several programming models such as OpenMP, MPI, and CUDA. Algorithmic skeletons are a well-known high-level solution to these issues. They provide recurring building blocks such as map, fold, and zip, which are used by the application programmer and executed in parallel. In the present paper, we use the skeleton library Muesli in order to solve hard optimization problems by applying swarm intelligence (SI)-based metaheuristics. We investigate, how much hardware can reasonably be employed in order to find quickly a good solution using Fish School Search (FSS), which is a rather new and innovative SI-based metaheuristic. Moreover, we compare the implementation effort and performance of low-level and high-level implementations of FSS. [ABSTRACT FROM AUTHOR]

Dataflow programming consists in developing a program by describing its sequential stages and the interactions between them. The runtime systems supporting this kind of programming are responsible for exploiting the parallelism by concurrently executing the different stages as soon as their dependencies are met. In this paper we introduce a new parallel programming model and framework based on the dataflow paradigm. It presents a new combination of features that allows to easily map programs to shared or distributed memory, exploiting data locality and affinity to obtain the same performance than optimized coarse-grain MPI programs. These features include: It is a unique one-tier model that supports hybrid shared- and distributed-memory systems with the same abstractions; it can express activities arbitrarily linked, including non-nested cycles; it uses internally a distributed work-stealing mechanism to allow Multiple-Producer/Multiple-Consumer configurations; and it has a runtime mechanism for the reconfiguration of the dependences and communication channels which also allows the creation of task-to-task data affinities. We present an evaluation using examples of different classes of applications. Experimental results show that programs generated using this framework deliver good performance in hybrid distributed- and shared-memory environments, with a similar development effort as other dataflow programming models oriented to shared-memory. [ABSTRACT FROM AUTHOR]

Memristor crossbars are capable of implementing learning algorithms in a much more energy and area efficient manner compared to traditional systems. However, the programmable nature of memristor crossbars must first be explored on a smaller scale to see which memristor device structures are most suitable for applications in reconfigurable computing. In this paper, we demonstrate the programmability of memristor devices with filamentary switching based on LiNbO3, a new resistive switching oxide. We show that a range of resistance values can be set within these memristor devices using a pulse train for programming. We also show that a neuromorphic crossbar containing eight memristors was capable of correctly implementing an OR function. This work demonstrates that lithium niobate memristors are strong candidates for use in neuromorphic computing. [ABSTRACT FROM AUTHOR]

In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set {-1,0,1} as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation. [ABSTRACT FROM AUTHOR]

Reversible data hiding in the encrypted domain (RDH-ED) reversibly encode and decode information to an encrypted cover medium without decrypting it. With the rapid development of multimedia applications, 3D models are considered as potential cover media for reversible data hiding due to their intrinsic capacity and potential applications in various areas such as military and medicine. In this paper, we propose a two-tier RDH-ED framework for 3D mesh models using the homomorphic Paillier cryptosystem. Two homomorphic properties of the underlying cryptosystem are utilized to propose a two-tier RDH-ED framework for end-to-end authentication and cloud data management. The proposed framework is successfully implemented on various simple and dense meshes. The performance evaluation of the proposed framework shows high embedding rates. Furthermore, it produces high-quality directly decrypted meshes from which information bits are extracted error-free and the original meshes are recovered losslessly. [ABSTRACT FROM AUTHOR]

The erasure code improves the data reliability by encoding the original data into the redundant data, which shows higher storage efficiency compared with the replication. However, the update of the erasure-coded data brings large complexity due to the complicated operations of data transmission and data computation, especially at the context of multiple updates. This poses a new challenge for adopting the erasure codes in distributed storage systems: how to timely and efficiently update the erasure-coded data. However, existing update schemes of erasure codes are inadequate to meet the requirement of efficiency and adaptivity, since their serial and independent update techniques lead to a low update throughput and high overhead. In this paper, we propose a cooperative update scheme for multiple updates with erasure codes, called Coop-U, which updates the data block eagerly and cooperatively updates the parity blocks in bulk. Specifically, we propose a three-layer update structure to ensure the generality, which could support the update with diverse data sizes and coding parameters. For efficiency, we propose a workload-aware grouping algorithm to group the nodes to be updated and dynamically adjust the group size according to the update workload. Moreover, a cooperative data processing algorithm is proposed to organize the data transmission and computation among layers. Furthermore, a time-aware prediction algorithm is proposed to trigger the update for parity data in bulk at a given threshold. For adaptivity, we propose a cache-based failure processing algorithm to reconstruct the failed data and restore the paused update. To evaluate the performance of Coop-U, we implement Coop-U on HDFS-RAID and conduct testbed experiments on different update schemes. Extensive experiments confirm that Coop-U reduces the update time by 47 and 35% on average compared with the typical update schemes Data-R and Full-W, respectively. [ABSTRACT FROM AUTHOR]

The second generation Intel Xeon Phi processor codenamed Knights Landing (KNL) have recently emerged with 2D tile mesh architecture and the Intel AVX-512 instructions. However, it is very difficult for general users to get the maximum performance from the new architecture since they are not familiar with optimal cache reuse, efficient vectorization, and assembly language. In this paper, we illustrate several developing strategies to achieve good performance with C programming language by carrying out general matrix-matrix multiplications and without the use of assembly language. Our implementation of matrix-matrix multiplication is based on blocked matrix multiplication as an optimization technique that improves data reuse. We use data prefetching, loop unrolling, and the Intel AVX-512 to optimize the blocked matrix multiplications. When we use a single core of the KNL, our implementation achieves up to 98% of SGEMM and 99% of DGEMM using the Intel MKL, which is the current state-of-the-art library. Our implementation of the parallel DGEMM using all 68 cores of the KNL achieves up to 90% of DGEMM using the Intel MKL. [ABSTRACT FROM AUTHOR]

The results of testing formula simplification tools are presented in the first part of this paper. In the second part, an algorithm for constructing canonical forms of linear semi-algebraic formulas is described. The main result of the study is the definition of the canonical form of a linear semi-algebraic formula that has the property of uniqueness and other useful properties. An algorithm for constructing such a formula is described. [ABSTRACT FROM AUTHOR]