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We compare Fresco's analysis of the Turing machine-based notion of computation with that of others, in particular with functional programming and with the reversible computing paradigm of Toffoli and others. We conclude that, although much useful philosophical work can be done by the sort of analysis that Fresco proposes, there is, nevertheless, always likely to be a number of individually viable but different accounts of computation. [ABSTRACT FROM AUTHOR]

The digital transfer of the mind to a computer system (i.e., mind uploading) requires representing the mind as a finite sequence of bits (1s and 0s). The classic "stored-program computer" paradigm, in turn, implies the equivalence between program and data, so that the sequence of bits themselves can be interpreted as a program, which will be algorithmically executed in the receiving device. Now, according to a previous proof, on which this paper is based, a computational or algorithmic machine, however complex, cannot be free (in the sense of 'self-determined'). Consequently, a finite sequence of bits cannot adequately represent a free mind and, therefore, a free mind cannot be digitally transferred, quod erat demonstrandum. The impossibility of making this transfer, as demonstrated here, should be a concern especially for those who wish to achieve it. Since we intend this to be a rigorous demonstration, we must give precise definitions and conditions of validity. The most important part of the paper is devoted to explaining the meaning and reasonableness of these definitions and conditions (for example that being truly free means being self-determined). Special attention is paid, also, to the philosophical implications of the demonstration. Finally, this thesis is distinguished from other closely related issues (such as other possible technological difficulties to "discretize" the mind; or, whether it is possible to transfer the mind from one material support to another one in a non-digital way). [ABSTRACT FROM AUTHOR]

Advances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a means to improve the accuracy and efficiency of identifying images. In this study, we will analyze various regression techniques and their applications in computer image recognition, as well as the resulting performance improvements through detailed examples and data analysis. This paper deals with the problems related to visual image processing in outdoor unstructured environment. Finally, the heterogeneous patterns are converted into the same pattern, and the heterogeneous patterns are extracted from the fusion features of data modes. The simulation results show that the perception ability and recognition ability of outdoor image recognition in complex environment are improved. [ABSTRACT FROM AUTHOR]

Triage is a system used to prioritise patients as they enter the emergency department (ED) based on their need for urgent care. In recent decades, EDs have becoming increasingly overcrowded, leading to longer pre-triage waiting times for patients. E-triage interventions like kiosks have been proposed as a solution to overcrowding. We conducted a literature review into the effectiveness of kiosks in improving triage efficiency. After rigorously searching five biomedical databases and screening candidate articles in Endnote, we identified nine papers pertaining to the introduction of kiosks in emergency departments. Six articles had positive findings—with E-triage interventions improving some aspect of the triage process—such as reducing pre-triage times. Conversely, only three articles reported negative findings, such as low uptake. Consequently, EDs should consider introducing kiosks to complement the current nurse-led triage process and thereby promote better patient outcomes. [ABSTRACT FROM AUTHOR]

This paper aims to highlight the life of computer technologies to understand what kind of 'technological intentionality' is present in computers based upon the phenomenological elements constituting the objects in general. Such a study can better explain the effects of new digital technologies on our society and highlight the role of digital technologies by focusing on their activities. Even if Husserlian phenomenology rarely talks about technologies, some of its aspects can be used to address the actions performed by the digital technologies by focusing on the objects' inner 'life' thanks to the analysis of passive synthesis and phenomenological horizons in the objects. These elements can be used in computer technologies to show how digital objects are 'alive.' This paper focuses on programs developed through high-order languages like C++ and unsupervised learning techniques like 'Generative Adversarial Model.' The phenomenological analysis reveals the computer's autonomy within the programming stages. At the same time, the conceptual inquiry into the digital system's learning ability shows the alive and changeable nature of the technological object itself. [ABSTRACT FROM AUTHOR]

This paper explores and ultimately affirms the surprising claim that artificial intelligence (AI) can become part of the person, in a robust sense, and examines three ethical and legal implications. The argument is based on a rich, legally inspired conception of persons as free and independent rightholders and objects of heightened protection, but it is construed so broadly that it should also apply to mainstream philosophical conceptions of personhood. The claim is exemplified by a specific technology, devices that connect human brains with computers and operate by AI-algorithms. Under philosophically reasonable and empirically realistic conditions, these devices and the AI running them become parts of the person, in the same way as arms, hearts, or mental capacities are. This transformation shall be called empersonification. It has normative and especially legal consequences because people have broader and stronger duties regarding other persons (and parts of them) than regarding things. Three consequences with practical implications are: (i) AI-devices cease to exist as independent legal entities and come to enjoy the special legal protection of persons; (ii) therefore, third parties such as manufacturers or authors of software lose (intellectual) property rights in device and software; (iii) persons become responsible for the outputs of the empersonified AI-devices to the same degree that they are for desires or intentions arising from the depths of their unconscious. More generally, empersonification marks a new step in the long history of human–machine interaction that deserves critical ethical reflection and calls for a stronger value-aligned development of these technologies. [ABSTRACT FROM AUTHOR]

Michael Somos discovered several theta-function identities of various levels by computer and offered no proof for them. These identities highly resemble some of Ramanujan's identities. The main focus of this paper is to prove some of these theta-function identities, in particular those of level 6 that have been discovered using computational searches. Some of the the Somos identities that we are discussing in this paper cannot be expressed in the form of P −−Q type. Furthermore, we establish certain colored partition identities for them. [ABSTRACT FROM AUTHOR]

CitcomCu is a numerical simulation software for mantle convection in the field of geodynamics, which can simulate thermo-chemical convection in a three-dimensional domain. Due to the increasing demand for high-precision simulations and larger application scales, larger-scale computing systems are needed to solve this problem. However, the parallel efficiency of CitcomCu on large-scale heterogeneous parallel computing systems is difficult to improve, especially it cannot adapt to the current mainstream heterogeneous high-performance computing architecture with CPUs and accelerators. In this paper, we propose an geodynamics numerical simulation parallel computing framework using heterogeneous computing architecture based on the Tianhe new-generation high-performance computer. Firstly, the data partitioning mode of CitcomCu was optimized based on the large-scale heterogeneous computing architecture to reduce the overall communication overhead. Secondly, the iterative solution algorithm of CitcomCu was improved to speed up the solution process. Finally, the NEON instruction set based on SIMD is used for the sparse matrix operations in the solution process to improve parallel efficiency. Based on our parallel computing framework, the optimized CitcomCu was deployed and tested on the Tianhe new-generation high-performance computer. Experimental data showed that the performance of the optimized program was 3.3975 times higher than that of the unoptimized program on a single node. Compared with 50,000 computational cores, the parallel efficiency of the unoptimized program on one million computational cores was 36.75%, while the parallel efficiency of the optimized program was improved by 16.22% and reached 42.71%. In addition, the optimized program can be executed on 40 million computational cores, with a parallel efficiency of 36.54%. [ABSTRACT FROM AUTHOR]

Objective : To compare the agreement between anxiety, depression and supportive care needs data obtained using a touchscreen computer survey with traditional pen-and-paper surveys. Methods : The sample consisted of 1304 consecutive patients attending the medical or radiation oncology outpatient department in two public cancer treatment centres. Of the 357 eligible patients, 355 (99%) consented to participate and 350 (98%) completed both touchscreen computer and pen-and-paper versions of the Hospital Anxiety and Depression Scale (HADS) and short-form Supportive Care Needs Survey (SCNS-short). Results : Simple κ values indicated moderate agreement ($\{\backslash bar\; X\}$ = 0.57) between the two modes of survey administration for most HADS items. Simple κ coefficients indicated only fair agreement ($\{\backslash bar\; X\}$ = 0.28) when a simplified response option format was used in the computerised SCNS-short. When the paper and computerised survey used the same response format, simple kgr; coefficients increased and indicated moderate agreement ($\{\backslash bar\; X\}$ = 0.44) for most SCNS-short items. κ Coefficients indicated at least moderate agreement (κ > 0.41) in identifying patients with elevated levels of anxiety and depression; there were no significant differences in the proportion of patients identified with elevated levels of anxiety and depression according to computer survey compared to paper survey. Prevalence-adjusted bias-adjusted κ (PABAK) coefficients indicated at least moderate agreement ($\{\backslash bar\; X\}$ = 0.79) in identifying participants with moderate/high levels of unmet needs. However, participants tended to report lower levels of unmet needs with a simplified response format in the computerised SCNS-short compared to the paper survey. This was not observed when the response format of the computerised SCNS-short replicated the paper survey. Conclusions : Despite the advantages that computerised surveys offer for simplifying survey presentation, current results suggest the need to exactly replicate the question and response option format of the original paper survey to ensure the data collected are equivalent. This finding is particularly important given the potential application of computerised surveys in the clinical setting to quickly assess and identify patients' concerns requiring intervention by health care providers. [ABSTRACT FROM AUTHOR]

Border tracking in binary images is an important operation in many computer vision applications. The problem consists in finding borders in a 2D binary image (where all of the pixels are either 0 or 1). There are several algorithms available for this problem, but most of them are sequential. In a former paper, a parallel border tracking algorithm was proposed. This algorithm was designed to run in Graphics Processing units, and it was based on the sequential algorithm known as the Suzuki algorithm. In this paper, we adapt the previously proposed GPU algorithm so that it can be executed in multicore computers. The resulting algorithm is evaluated against its GPU counterpart. The results show that the performance of the GPU algorithm worsens (or even fails) for very large images or images with many borders. On the other hand, the proposed multicore algorithm can efficiently cope with large images. [ABSTRACT FROM AUTHOR]

The Hopf oscillator is a nonlinear oscillator that exhibits limit cycle motion. This reservoir computer utilizes the vibratory nature of the oscillator, which makes it an ideal candidate for reconfigurable sound recognition tasks. In this paper, the capabilities of the Hopf reservoir computer performing sound recognition are systematically demonstrated. This work shows that the Hopf reservoir computer can offer superior sound recognition accuracy compared to legacy approaches (e.g., a Mel spectrum + machine learning approach). More importantly, the Hopf reservoir computer operating as a sound recognition system does not require audio preprocessing and has a very simple setup while still offering a high degree of reconfigurability. These features pave the way of applying physical reservoir computing for sound recognition in low power edge devices. [ABSTRACT FROM AUTHOR]

Quantum Monte Carlo (QMC) techniques are widely used in a variety of scientific problems and much work has been dedicated to developing optimized algorithms that can accelerate QMC on standard processors (CPU). With the advent of various special purpose devices and domain specific hardware, it has become increasingly important to establish clear benchmarks of what improvements these technologies offer compared to existing technologies. In this paper, we demonstrate 2 to 3 orders of magnitude acceleration of a standard QMC algorithm using a specially designed digital processor, and a further 2 to 3 orders of magnitude by mapping it to a clockless analog processor. Our demonstration provides a roadmap for 5 to 6 orders of magnitude acceleration for a transverse field Ising model (TFIM) and could possibly be extended to other QMC models as well. The clockless analog hardware can be viewed as the classical counterpart of the quantum annealer and provides performance within a factor of < 10 of the latter. The convergence time for the clockless analog hardware scales with the number of qubits as ∼ N, improving the ∼ N2 scaling for CPU implementations, but appears worse than that reported for quantum annealers by D-Wave. Quantum Monte Carlo (QMC) techniques have been very successful in quantum simulation. This paper shows a pathway to provide orders of magnitude speedup to QMC simulations through massively parallel architectures (both digital and mixed signal) while maintaining a scaling advantage over QMC implemented in software. [ABSTRACT FROM AUTHOR]

The need for computation speed is ever increasing. A promising solution for this requirement is parallel computing but the degree of parallelism in electronic computers is limited due to the physical and technological barriers. DNA computing proposes a fascinating level of parallelism that can be utilized to overcome this problem. This paper presents a new computational model and the corresponding design methodology using the massive parallelism of DNA computing. We proposed an automatic design algorithm to synthesis the logic functions on the DNA strands with the maximum degree of parallelism. In the proposed model, billions of DNA strands are utilized to compute the elements of the Boolean function concurrently to reach an extraordinary level of parallelism. Experimental and analytic results prove the feasibility and efficiency of the proposed method. Moreover, analyses and results show that a delay of a circuit in this method is independent of the complexity of the function and each Boolean function can be computed with O(1) time complexity. [ABSTRACT FROM AUTHOR]

The article focuses on the capabilities of quantum computers in solving problems without running a program. The process by which a quantum computer's solution to a computation may be learnt without actually running the computer is called the counter-factual computation (CFC). This could be used to deduce the result of a computation with a higher probability of arriving at the right answer than random guessing. Errors that are prevalent in the computer can be avoided by applying the CFC process.

The article discusses electronic voting machines, particularly the direct recording electronic (DRE) devices. The device translates a voter's choice into electronic data. Computer scientists Avi Rubin and Dan Wallach recommended that DRE systems should generate voter-verified audit trails on which a voter could check that his or her vote had been cast correctly. The DRE system was put in place in the May 2006 primary elections in Ohio. However, it was not a great success and a Ohio study showed that almost 10% of the paper records were useless or absent because the printers jammed, ran out of paper or overprinted.

Compares the Web-based and traditional instruments in take-home and in-class settings through computer surveys. Drawbacks in computer surveys; Response rates of the survey; Advantages of using the Web-based method in data collection.

Alongside many research studies that have been presented in the open innovation domain and smart manufacturing systems, there is a research gap on integrating the outbound individual capabilities with the new smart manufacturing machines to satisfy the customers' varied and uncertain requirements. In this paper, Open Supply Chain Management (OSCM) is conceptualized as a new paradigm in the evolution of SCM. Companies can benefit from integrated physical and conceptual resources to promote efficiency and flexibility throughout the supply chain's main processes, including supplying, manufacturing, distributing, and marketing. The OSCM concept is undergoing several drivers including crowdsourcing, open innovation, Industry 4.0, cloud manufacturing, Internet of Things (IoT), big data, and the digital twin that appeared in the last decades. To validate OSCM in practice, a subset of this concept is investigated to incorporate the designing process with supply chain production planning applying a digital twin network. Additionally, dealing with epistemic uncertainty, a fuzzy tactical planning model is developed, and to study the developed model in more detail, an industrial study in the clothes manufacturing industry is employed. The results illustrate that the products' designing cost consists of only 2% of the supply chain total cost. [ABSTRACT FROM AUTHOR]

Much of the knowledge and information needed for enabling high-quality clinical research is stored in free-text format. Natural language processing (NLP) has been used to extract information from these sources at scale for several decades. This paper aims to present a comprehensive review of clinical NLP for the past 15 years in the UK to identify the community, depict its evolution, analyse methodologies and applications, and identify the main barriers. We collect a dataset of clinical NLP projects (n = 94; £ = 41.97 m) funded by UK funders or the European Union's funding programmes. Additionally, we extract details on 9 funders, 137 organisations, 139 persons and 431 research papers. Networks are created from timestamped data interlinking all entities, and network analysis is subsequently applied to generate insights. 431 publications are identified as part of a literature review, of which 107 are eligible for final analysis. Results show, not surprisingly, clinical NLP in the UK has increased substantially in the last 15 years: the total budget in the period of 2019–2022 was 80 times that of 2007–2010. However, the effort is required to deepen areas such as disease (sub-)phenotyping and broaden application domains. There is also a need to improve links between academia and industry and enable deployments in real-world settings for the realisation of clinical NLP's great potential in care delivery. The major barriers include research and development access to hospital data, lack of capable computational resources in the right places, the scarcity of labelled data and barriers to sharing of pretrained models. [ABSTRACT FROM AUTHOR]

Imagine advanced computers that could, by virtue merely of being programmed in the right ways, act, react, communicate, and otherwise behave like humans. Might such computers be capable of understanding, thinking, believing, and the like? The framework developed in this paper for tackling challenging questions of concept application (in any realm of discourse) answers in the affirmative, contrary to Searle's famous 'Chinese Room' thought experiment, which purports to prove that ascribing such mental processes to computers like these would be necessarily incorrect. The paper begins by arguing that the core issue concerns language, specifically the discourse-community-guided mapping of phenomena onto linguistic categories. It then offers a model of how people adapt language to deal with novel states of affairs and thereby lend generality to their words, employing processes of assimilation, lexemic creation, and accommodation (in intersense and intrasense varieties). Attributions of understanding to some computers lie in the middle range on a spectrum of acceptability and are thus reasonable. Possible objections deriving from Searle's writings require supplementing the model with distinctions between present and future acceptability, and between contemplated and uncontemplated word uses, as well as a literal-figurative distinction that is more sensitive than Searle's to actual linguistic practice and the multiplicity of subsenses possible within a single literal sense. The paper then critiques two misleading rhetorical features of Searle's Chinese Room presentation, and addresses a contemporary defense of Searle that seems to confront the sociolinguistic issue, but fails to allow for intrasense accommodation. It concludes with a brief consideration of the proper course for productive future discussion. [ABSTRACT FROM AUTHOR]

Today, there is an ever-increasing number of workloads pushed and executed on the Cloud. Data center operators and Cloud providers have embraced application co-location and multi-tenancy as first-class system design concerns to effectively serve and manage these huge computational demands. In addition, the continuous advancements in the computers' hardware technology have made it possible to seamlessly leverage heterogeneous pools of physical machines in data center environments. Even though current modern Cloud schedulers and orchestrators adopt application-aware policies to achieve automation of time-consuming management tasks at scale, e.g., resource provisioning, they still rely on coarse-grained system metrics, such as CPU and/or memory utilization to place incoming applications, thus, not considering (1) interference effects that are provoked by co-located tasks, and (2) the impact on performance caused by the diversity of heterogeneous systems' characteristics. The lack of such knowledge in existing state-of-the-art orchestration solutions results in their inability to perform efficient allocations, which negatively impacts the overall latency distribution delivered by the infrastructure. In this paper, to alleviate this inefficiency, we present a machine learning (ML) based Cloud orchestration extension that takes into account both resource interference and heterogeneity. The framework adequately schedules data-analytics applications on a pool of heterogeneous resources. We evaluate our proposed solution on different application mixes and co-location scenarios. We show that the proposed framework improves the tail latency of the distribution of the deployed applications by up to 3.6x compared to the state-of-the-art Kubernetes scheduler. [ABSTRACT FROM AUTHOR]

Energy distribution networks represent crucial infrastructures for modern society, and various simulation tools have been widely used by energy suppliers to manage these intricate networks. However, simulation calculations include a large number of fluid control equations, and computational overhead limits the performance of simulation software. This paper proposes a universal parallel simulation framework for energy pipeline networks that takes advantages of data parallelism and computational independence between network elements. A non-pipe model of an energy supply network is optimized, and the input and output of the network model in the proposed framework are modified, which can reduce the development burden during the numerical computations of the pipeline network and weaken the computational correlation between different simulated components. In addition, independent computations can be performed concurrently through periodic data exchange procedures between component instances, improving the parallelism and efficiency of simulation computations. Further, a parallel water pipelines network simulation computing paradigm based on a heterogeneous computer hardware architecture is used to evaluate the proposed framework's performance. A series of tests are conducted to verify the accuracy of the proposed framework, and simulation errors of less than 5% are achieved. The results of multi-threaded simulation experiments have demonstrated the feasibility of the proposed framework in a parallel computing approach. Moreover, an Advanced Micro Devices (AMD) Deep Computing Unit (DCU)-parallel program is implemented into a water supply network simulation system; the computational efficiency of this system is compared with that of its serial counterpart. The experimental results show that the proposed framework is appropriate for high-performance computer architectures, and the 18x speed-up ratio demonstrates that the parallel program based on the proposed universal framework outperforms the serial program. That provides the basis for the application of pipe network simulation on high-performance computers. [ABSTRACT FROM AUTHOR]

In recent decades, there has been a proliferation among the scientific community of works that focus on Alan Turing's contributions to the design and development of the modern computer. However, there are significant discrepancies among these studies, to such a point that some of them cast serious doubts on Alan Turing's work with respect to today's computer, and there are others that staunchly defend his leading role, as well as other studies that set out more well-balanced opinions. Faced with this situation, the aim of this paper is to analyse the evidence existing today in order to be able to draw a conclusion about whether or not Turing anticipated the trivialisation of the modern computer memory and, likewise, if his universal a-machine is the precursor of the general-purpose computer so omnipresent today. As a result of our research, the authors conclude that Turing did indeed play a leading role in the appearance of the modern computer, although he was not the only one or the first in the field of Computing Science, albeit he was the most influential, both in scope and in depth. [ABSTRACT FROM AUTHOR]

Background: To implement distress screening in routine radiotherapy practice and to compare computerised and paper-and-pencil screening in terms of acceptability and utility.Methods: We used the Stress Index RadioOncology (SIRO) for screening. In phase 1, 177 patients answered both a computerised and a paper version, and in phase 2, 273 patients filled out either the computerised or the paper assessment. Physicians received immediate feedback of the psycho-oncological results. Patients, nurses/radiographers (n=27) and physicians (n=15) evaluated the screening procedure.Results: The agreement between the computerised and the paper assessment was high (intra-class correlation=0.92). Patients' satisfaction did not differ between the two administration modes. Nurses/radiographers rated the computerised assessment less time consuming (3.7 vs 18.5%), although the objective data did not reveal a difference in time demand. Physicians valued the psycho-oncological results as interesting and informative (46.7%). Patients and staff agreed that the distress screening did not lead to an increase in the discussion of psychosocial issues in clinician-patient encounters.Conclusion: The implementation of a distress screening was feasible and highly accepted, regardless of the administration mode. Communication trainings should be offered in order to increase the discussion of psychosocial topics in clinician-patient encounters. [ABSTRACT FROM AUTHOR]

DDoS attacks launched by IoT botnets can be classified into low-rate and high-rate DDoS attacks, which depict two distinct scenarios of data imbalance, namely, the minimal and maximal proportion of attack traffic. Developing a detection model that can effectively address two data imbalance scenarios concurrently is crucial in safeguarding computers against DDoS attacks. This necessitates the development of a model with enhanced generalizability. However, in the examination of cross-evaluation across datasets which is closely associated with the generalizability of models, there is a limited focus on addressing the issue of data imbalance. This oversight has led to a significant decrease in model performance when compared to training and testing on a single dataset. To identify guiding principles within this context, the literature suggests employing an undersampling technique on benign instances during the preprocessing phase to eliminate redundant data. Additionally, the literature conducts simulations of various cross-evaluation scenarios and evaluates the performance of classifiers. This evaluation is done after applying representative oversamplers, undersamplers, and the method proposed in this paper. After analyzing the experiment results, it is advisable to employ oversamplers for low-rate DDoS datasets and undersamplers for high-rate DDoS datasets. Moreover, optimizing SMOTE-based algorithms for specific models will yield optimal performance. [ABSTRACT FROM AUTHOR]

When implementing fully connected layer computation on electronic computer (EC), slow computing speed and high power consumption result in the inefficiency of the overall process. The ternary optical computer (TOC) platform with enormous data bits and reconfigurable processor can solve the inefficiency of full-connection computation on EC. In this paper, we design the parallel scheme of fully connected layer operations based on TOC and the rectified linear unit (ReLU) output device to achieve the computation of nonlinear fully connected layer. Furthermore, we also use the ReLU output device and the positive and negative discriminator of modified signed digit (MSD) data to design the ReLU judgment output device, which can realize the operation of the ReLU activation function in one step. The operations of the nonlinear fully connected layer with ReLU function on TOC can reduce the amount of computation by one magnitude and have lower power consumption by experimentally verifying the accuracy of operations and analyzing hardware resources and clock cycles. Through comparison find that TOC consumes fewer data bits, while improving the calculation speed by approximately 10%. [ABSTRACT FROM AUTHOR]

We study here the diagnosability of networks under two models of self-diagnosis: PMC model introduced by Preparata, Metze and Chien (IEEE Trans Electronic Computers 16(12):848–854 (1967)) and MM ∗ model introduced by Sengupta and Dahbura (IEEE Trans Computers 41(11):1386–1396 (1992)) which is the variant of the comparison model (1980). The diagnosability of a network of processors is the maximum number of faulty processors that can be identified by the network itself. Lee and Hsieh (IEEE Trans Dependable Secure Comput 8(2):246–255 (2011)) considered the diagnosability of networks obtained by connecting two networks of the same order by two perfect matchings and got the lower bounds. Usually, there is a gap between the lower bound and the exact value of the diagnosability. In this paper, we completely determine the diagnosability of this family of matching composition networks. [ABSTRACT FROM AUTHOR]

The classification of data stream susceptible to the concept drift phenomenon has been a field of intensive research for many years. One of the dominant strategies of the proposed solutions is the application of classifier ensembles with the member classifiers validated on their actual prediction quality. This paper is a proposal of a new ensemble method – Covariance-signature Concept Selector – which, like state-of-the-art solutions, uses both the model accumulation paradigm and the detection of changes in the data posterior probability, but in the integrated procedure. However, instead of ensemble fusion, it performs a static classifier selection, where model similarity assessment to the currently processed data chunk serves as a concept selector. The proposed method was subjected to a series of computer experiments assessing its temporal complexity and efficiency in classifying streams with synthetic and real concepts. The conducted experimental analysis allows concluding the advantage of this proposal over state-of-the-art methods in the identified pool of problems and high potential in practical applications. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fine-grained fast parallel genetic algorithm based on a ternary optical computer. Owing to the natural parallelizability of genetic algorithms, we take advantage of the characteristics of ternary optical computers, such as a large number of processor bits that can be reconfigured or allocated bit-by-bit, parallel computation, and low power consumption. The design and implementation of a parallel genetic algorithm on a ternary optical computer by solving the traveling salesman problem (TSP) is used as an example. Theoretical analysis and experimental results show that our proposed algorithm provides more efficient performance when the size of the members of the cities continuously increases according to the acceleration ratio measurement results. It also lays the theoretical foundation for the application of ternary optical computers in data-intensive computing. [ABSTRACT FROM AUTHOR]

For 3-D graphic applications requiring powerful, piece-by-piece, second-order polynomial assessments, this paper proposes a novel dual-channel multiplier (NDCM). Generally multiplier plays a key role in any signal processing application. But multipliers will occupy more area and power consumption. Multipliers will consist of adders and shifters. So to increase the speed of multiplier a novel adder is to be designed. The type of adder used to evaluate the multiplier has a significant impact on its performance. Different hardware architectures can be created using the kogge—stone adder and its applications. Traditional dual channel multiplier's (DCM) drawbacks are eliminated by using the kogge-stone Parallel Prefix adder. Hardware complexity is decreased. The proposed scheme's complicated functions can be meet with a powerful and economical solution. In the piece-wise polynomial approximation, the prefix adder reduces the hardware computer initiative with uniform or uniform segmentation. There is a negligible influence on delay as compared to the large input word size CPA of these devices. The proposed design is synthesized on Xilinx 14.2. The proposed architecture achieves high speed at a reduced area and delay when compared with recent designs. The proposed architecture is implemented and tested on Virtex 5vsx95-1ff1136 FPGA and the results show that the proposed design involves less number of slices and offers high speed than existing designs. The FPGA device utilization summary and latency are analyzed and compared. [ABSTRACT FROM AUTHOR]

All kinds of electronic products, such as motherboards, digital cameras, mobile phones and even chip products in manufacturing production processes, require some form of defect detection in an IoT environment. Shortcomings and improvements need to be found before a product is shipped, and various computer applications have been proposed to facilitate this, such as facial recognition, object tracking, digital picture processing and other forms of defect detection automation in an IoT environment, to reduce costs in the industrial production field. Various manufacturers have also invested in computer research aimed at replacing some labour-intensive aspects of key processes. This paper focuses on detection of printed circuit board defects, which plays a key role in the production process of general electronic products. In this study, computer theory was used as the basic architecture. This method can convert spatial domain signals into frequency domain signals, providing users with a specific frequency range. An algorithm is described here, capable of detecting defects in printed circuit boards, such as short circuits, protruding solder, solder dents and open circuits. In this study, the algorithm was used with wavelet transform technology to achieve the purpose of detecting PCB defects in an IoT environment. The results indicated that the technology in question is simple to operate and performs efficiently. It only requires an accurate picture to be inputted (after processing), containing the defect, in order to determine the location of the defect. [ABSTRACT FROM AUTHOR]

This paper introduces the Volume 30 of "The Journal of Supercomputing." The special issues presents four different applications on configurable computing platform. The research and experiments in configurable computing showed that many application-specific systems, which require the use of high-performance computing facilities, may be often be implemented more efficiently using reconfigurable hardware. The two first papers present the applications where traditionally high-performance computers or supercomputers are used. The first paper by Soheil Ghiasi and colleagues deals with collaborative object tracking with a number of networked cameras to perceive information. The second paper by William D. Smith and colleagues deals with Computational Fluid Dynamics applications, which demand intensive floating-point calculations and run traditionally on supercomputers. The third paper by Gerard K. Rauwerda and colleagues deals with implementing wireless communication algorithms on a reconfigurable computing platform.

This article presents a new algorithmic approach for computational convergence verification of the Collatz problem. The main contribution of the paper is the replacement of huge precomputed tables containing O (2 N) entries with small lookup tables comprising just O(N) elements. Our single-threaded CPU implementation can verify 4.2 × 10 9 128-bit numbers per second on Intel Xeon Gold 5218 CPU computer, and our parallel OpenCL implementation reaches the speed of 2.2 × 10 11 128-bit numbers per second on NVIDIA GeForce RTX 2080. Besides the convergence verification, our program also checks for path records during the convergence test. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To synthesise current evidence for the influence on clinical behaviour of patient-specific electronically generated reminders available at the time of the clinical encounter. DATA SOURCES: PubMed, Cochrane library of systematic reviews; Science Citation Index Expanded; Social Sciences Citation Index; ASSIA; EMBASE; CINAHL; DARE; HMIC were searched for relevant articles. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND INTERVENTIONS: We included controlled trials of reminder interventions if the intervention was: directed at clinician behaviour; available during the clinical encounter; computer generated (including computer generated paper-based reminders); and generated by patient-specific (rather than condition specific or drug specific) data. STUDY APPRAISAL AND SYNTHESIS METHODS: Systematic review and meta-analysis of controlled trials published since 1970. A random effects model was used to derive a pooled odds ratio for adherence to recommended care or achievement of target outcome. Subgroups were examined based on area of care and study design. Odds ratios were derived for each sub-group. We examined the designs, settings and other features of reminders looking for factors associated with a consistent effect. RESULTS: Altogether, 42 papers met the inclusion criteria. The studies were of variable quality and some were affected by unit of analysis errors due to a failure to account for clustering. An overall odds ratio of 1.79 [95% confidence interval 1.56, 2.05] in favour of reminders was derived. Heterogeneity was high and factors predicting effect size were difficult to identify. LIMITATIONS: Methodological diversity added to statistical heterogeneity as an obstacle to meta-analysis. The quality of included studies was variable and in some reports procedural details were lacking. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: The analysis suggests a moderate effect of electronically generated, individually tailored reminders on clinician behaviour during the clinical encounter. Future research should concentrate on identifying the features of reminder interventions most likely to result in the target behaviour. [ABSTRACT FROM AUTHOR]

The Jacobi iterative algorithm has the characteristic of low computational load, and multiple components of the solution can be solved independently. This paper applies these characteristics to the ternary optical computer, which can be used for parallel optimization because it has a large number of data bits and reconfigurable processor bits. Therefore, a new parallel design scheme is constructed to solve the problem of slow efficiency in solving large linear equations. And the elaborate experiment is used to verify. The experimental method is to simulate the calculation on the ternary optical computer experimental platform. Then, the resource consumption is numerically calculated and summarized to measure the feasibility of the parallel design. Eventually, the results show that the parallel design has obvious advantages in computing speed. The Jacobi iterative algorithm is optimized in parallel on ternary optical processor for the first time. There are two parallel highlights of the scheme. First, the n components are calculated in full parallel. Second, the modified signed-digit (MSD) multiplier based on the minimum module and one-step MSD adder are used to calculate each component to eliminate the impact of large amount of data on calculation time. The research provides a new method for fast solution of large linear equations. [ABSTRACT FROM AUTHOR]

The abundance of parallel and distributed computing platforms, such as MPP, SMP, and the Beowulf clusters, to name just a few, has added many more possibilities and challenges to high performance computing (HPC), parallel I/O, mass data storage, scalable architectures, and large-scale simulations, which traditionally belong to the realm of custom-tailored parallel systems. The intent of this special issue is to discuss problems and solutions, to identify new issues, and to help shape future research directions in these areas. From these perspectives, this special issue addresses the problems encountered at the hardware, architectural, and application levels, while providing conceptual as well as empirical treatments to the current issues in high performance computing, and the I/O architectures and systems utilized therein. [ABSTRACT FROM AUTHOR]

The knowledgeable, human–machine interaction sight system has the benefits of low interference, lower permeability, and no interface attachment. The smart vision system has been critical in human–computer interaction to grow and advance technologies and research. The Human–Computer Interaction based Visual Feedback System (HCIVFS) is very quickly relative to the conventional collaborative mode. Such challenges may also affect the smart machine's view and the general use of sensation communication. The fundamental premise of the computer's sight communication architecture requires practical stability. This article explores the quality of the intellectual computer's enabling communication. The Rule of Fitts has also been included in this paper for three points-to-clicks applications. The proposed algorithm's reliability is analyzed in operations, visualization, and computer vision algorithms. There is a fair recommendation for an immersive configuration of the input method for intellectual sight by computer. [ABSTRACT FROM AUTHOR]

Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a legal sentence often based on logical patterns that illustrate the relations between concepts in the sentence, often consist of multiple words. Those representations cause the lack of semantic information at the word level. In our work, we aim to tackle such shortcomings by representing legal texts in the form of abstract meaning representation (AMR), a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing (producing AMR from natural language) and AMR-to-text Generation (producing natural language from AMR) specifically for legal domain. We also introduce JCivilCode, a human-annotated legal AMR dataset which was created and verified by a group of linguistic and legal experts. We conduct an empirical evaluation of various approaches in parsing and generating AMR on our own dataset and show the current challenges. Based on our observation, we propose our domain adaptation method applying in the training phase and decoding phase of a neural AMR-to-text generation model. Our method improves the quality of text generated from AMR graph compared to the baseline model. (This work is extended from our two previous papers: "An Empirical Evaluation of AMR Parsing for Legal Documents", published in the Twelfth International Workshop on Juris-informatics (JURISIN) 2018; and "Legal Text Generation from Abstract Meaning Representation", published in the 32nd International Conference on Legal Knowledge and Information Systems (JURIX) 2019.). [ABSTRACT FROM AUTHOR]

Modern information systems are built fron a complex composition of networks, infrastructure, devices, services, and applications, interconnected by data flows that are often private and financially sensitive. The 5G networks, which can create hyperlocalized services, have highlighted many of the deficiencies of current practices in use today to create and operate information systems. Emerging cloud computing techniques, such as Infrastructure-as-Code (IaC) and elastic computing, offer a path for a future re-imagining of how we create, deploy, secure, operate, and retire information systems. In this paper, we articulate the position that a comprehensive new approach is needed for all OSI layers from layer 2 up to applications that are built on underlying principles that include reproducibility, continuous integration/continuous delivery, auditability, and versioning. There are obvious needs to redesign and optimize the protocols from the network layer to the application layer. Our vision seeks to augment existing Cloud Computing and Networking solutions with support for multiple cloud infrastructures and seamless integration of cloud-based microservices. To address these issues, we propose an approach named Open Infrastructure as Code (OpenIaC), which is an attempt to provide a common open forum to integrate and build on advances in cloud computing and blockchain to address the needs of modern information architectures. The main mission of our OpenIaC approach is to provide services based on the principles of Zero Trust Architecture (ZTA) among the federation of connected resources based on Decentralized Identity (DID). Our objectives include the creation of an open-source hub with fine-grained access control for an open and connected infrastructure of shared resources (sensing, storage, computing, 3D printing, etc.) managed by blockchains and federations. Our proposed approach has the potential to provide a path for developing new platforms, business models, and a modernized information ecosystem necessary for 5G networks. [ABSTRACT FROM AUTHOR]

It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence (Turing in Computing machinery and intelligence. Oxford University Press, Oxford, 1950). In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of 'thinking' ('I propose to consider the question, Can computers think?' ...Alan Turing, Computing Machinery and Intelligence, Mind, 1950). Turing also set up a number of criteria-including his imitation game-under which a human could judge whether a computer could be said to be 'intelligent'. Turing's paper, as well as his important mathematical and computational insights of the 1930s and 1940s led to his popular acclaim as the 'Father of Artificial Intelligence'. In the years since his paper was published, however, no computational system has fully satisfied Turing's challenge. In this paper we focus on a different question, ignored in, but inspired by Turing's work: How might the Artificial Intelligence practitioner implement 'intelligence' on a computational device? Over the past 60 years, although the AI community has not produced a general-purpose computational intelligence, it has constructed a large number of important artifacts, as well as taken several philosophical stances able to shed light on the nature and implementation of intelligence. This paper contends that the construction of any human artifact includes an implicit epistemic stance. In AI this stance is found in commitments to particular knowledge representations and search strategies that lead to a product's successes as well as its limitations. Finally, we suggest that computational and human intelligence are two different natural kinds, in the philosophical sense, and elaborate on this point in the conclusion. [ABSTRACT FROM AUTHOR]

The International Journal of Computer Vision has published a special issue on the British Machine Vision Conference (BMVC) 2021. The issue includes three extended papers that have undergone rigorous review. The papers can be accessed through the "Collections" link on the journal's homepage. The journal acknowledges the editorial work of guest editors from various institutions in the UK, France, Germany, Italy, and the University of Edinburgh. The publisher, Springer Nature, maintains a neutral stance on jurisdictional claims and institutional affiliations. [Extracted from the article]

In their important paper “Autonomous Agents”, Floridi and Sanders use “levels of abstraction” to argue that computers are or may soon be moral agents. In this paper we use the same levels of abstraction to illuminate differences between human moral agents and computers. In their paper, Floridi and Sanders contributed definitions of autonomy, moral accountability and responsibility, but they have not explored deeply some essential questions that need to be answered by computer scientists who design artificial agents. One such question is, “Can an artificial agent that changes its own programming become so autonomous that the original designer is no longer responsible for the behavior of the artificial agent?” To explore this question, we distinguish between LoA1 (the user view) and LoA2 (the designer view) by exploring the concepts of unmodifiable, modifiable and fully modifiable tables that control artificial agents. We demonstrate that an agent with an unmodifiable table, when viewed at LoA2, distinguishes an artificial agent from a human one. This distinction supports our first counter-claim to Floridi and Sanders, namely, that such an agent is not a moral agent, and the designer bears full responsibility for its behavior. We also demonstrate that even if there is an artificial agent with a fully modifiable table capable of learning* and intentionality* that meets the conditions set by Floridi and Sanders for ascribing moral agency to an artificial agent, the designer retains strong moral responsibility. [ABSTRACT FROM AUTHOR]

I/O- and data-intensive workloads, as represented by the Grand Challenge problems, multimedia applications, cosmology simulations, climate modeling, and large collaborative visualizations, to name a few, entail innovative approaches to alleviate the I/O (both bandwidth and data access) performance bottlenecks. The advent of low-cost hardware platforms, such as the Beowulf clusters, has opened up numerous possibilities in mass data storage, scalable architectures, and large-scale simulations. The objective of this Special Issue is to discuss problems and solutions, to identify new issues, and to help shape future research and development directions in these areas. From these perspectives, the Special Issue addresses the problems encountered at the hardware, middleware, and application levels, providing conceptual as well as empirical treatments. [ABSTRACT FROM AUTHOR]

Survivable systems are increasingly needed in a wide range of applications. As a step toward realizing survivable systems, this paper presents architecture of intrusion-tolerant servers. It is to deliver intended services transparently to the clients even when a computing node fails due to failures, intrusions, and other threats. In order to deliver only secure results to the client, we need an algorithm to decide agreement on results from replicated servers. For this purpose, a secure and practical decentralized voting algorithm for the architecture is proposed in the paper. Through the experiments on a test-bed, especially, for web services, the approach turned out very effective in terms of extra cost and considered to be able to cope with both confidentiality and integrity attacks. [ABSTRACT FROM AUTHOR]

The current paper introduces a systematic method for representing and analysing coupled integrated engineering systems by means of general discrete mathematical models, called Combinatorial Representations, that can be conveniently implemented in computers. The combinatorial representation of this paper, which is based on graph theory, was previously shown to be useful in representing engineering systems from different engineering domains. Once all of the subsystems of an integrated multidisciplinary system are brought up to the common level of the combinatorial representation, they cease to be separated from one another and the analysis process is applied to all of the engineering elements disregarding the domain to which they belong. During the development of the representation and study of its inherent properties, special attention was dedicated to developing an efficient analysis method. A vectorial extension of the mixed variable method known from electrical network theory was found to be the most suitable choice for this purpose. In the paper, the approach is implemented by representing and analysing two systems: one that is a macro system comprised of truss, dynamic and electric elements, and another that is a comb-driven micro-resonator. The techniques presented in the paper are not limited to analysis only, but can be applied to many other aspects of engineering research. Among them is a systematic derivation of new ways of presenting engineering elements, one of which ? the process of derivation of a new type of force representation entitled ?face force? ? is described in the paper. [ABSTRACT FROM AUTHOR]

The article presents an introduction to articles related to supercomputing. In the first paper, the authors evaluate two new performance prediction methods using a distributed enterprise application benchmark on server architectures to improve service level agreement-based resource management. Continuous resource monitoring and profiling are critical for ensuring accurate performance tuning and scheduling optimization. In the third paper the authors present a bandwidth-centric job communication model that can capture the interaction and impact of simultaneously co-allocating jobs across multiple clusters.

Cyber-physical systems are hybrid networked cyber and engineered physical elements that record data (e.g. using sensors), analyse them using connected services, influence physical processes and interact with human actors using multi-channel interfaces. Examples of CPS interacting with humans in industrial production environments are the so-called cyber-physical production systems (CPPS), where operators supervise the industrial machines, according to the human-in-the-loop paradigm. In this scenario, research challenges for implementing CPPS resilience, promptly reacting to faults, concern: (i) the complex structure of CPPS, which cannot be addressed as a monolithic system, but as a dynamic ecosystem of single CPS interacting and influencing each other; (ii) the volume, velocity and variety of data (Big Data) on which resilience is based, which call for novel methods and techniques to ensure recovery procedures; (iii) the involvement of human factors in these systems. In this paper, we address the design of resilient cyber-physical production systems (R-CPPS) in digital factories by facing these challenges. Specifically, each component of the R-CPPS is modelled as a smart machine, that is, a cyber-physical system equipped with a set of recovery services, a Sensor Data API used to collect sensor data acquired from the physical side for monitoring the component behaviour, and an operator interface for displaying detected anomalous conditions and notifying necessary recovery actions to on-field operators. A context-based mediator, at shop floor level, is in charge of ensuring resilience by gathering data from the CPPS, selecting the proper recovery actions and invoking corresponding recovery services on the target CPS. Finally, data summarisation and relevance evaluation techniques are used for supporting the identification of anomalous conditions in the presence of high volume and velocity of data collected through the Sensor Data API. The approach is validated in a food industry real case study. [ABSTRACT FROM AUTHOR]

Advanced visualization of medical imaging has been a motive for research due to its value for disease analysis, surgical planning, and academical training. More recently, attention has been turning toward mixed reality as a means to deliver more interactive and realistic medical experiences. However, there are still many limitations to the use of virtual reality for specific scenarios. Our intent is to study the current usage of this technology and assess the potential of related development tools for clinical contexts. This paper focuses on virtual reality as an alternative to today's majority of slice-based medical analysis workstations, bringing more immersive three-dimensional experiences that could help in cross-slice analysis. We determine the key features a virtual reality software should support and present today's software tools and frameworks for researchers that intend to work on immersive medical imaging visualization. Such solutions are assessed to understand their ability to address existing challenges of the field. It was understood that most development frameworks rely on well-established toolkits specialized for healthcare and standard data formats such as DICOM. Also, game engines prove to be adequate means of combining software modules for improved results. Virtual reality seems to remain a promising technology for medical analysis but has not yet achieved its true potential. Our results suggest that prerequisites such as real-time performance and minimum latency pose the greatest limitations for clinical adoption and need to be addressed. There is also a need for further research comparing mixed realities and currently used technologies. [ABSTRACT FROM AUTHOR]

This paper describes a new apple classification system based on machine vision and artificial neural network (ANN), which classifies apple in real time on the basis of physical parameters of apple such as size, color and external defects. A specific hardware subsystem has been developed and described for every stage of input and output. The hardware subsystem is interfaced with the software to make the whole system automatic. The purpose of this paper is to automate apple classification. Presently, ANN is used in a wide range of classification applications. We have trained a back-propagation neural network to classify apple. Two sets of variables are used for the training purpose. First set is the independent variable, which is the surface level apple quality parameter. Second set is the dependent variable, which is the quality of the apple. The results of ANN model are discussed; however, the modeling results showed that there is an excellent agreement between the experimental data and predicted values, with a high determination coefficient, very good performance, fewer parameters, shorter calculation time and lower prediction error. The classification accuracy achieved is high, showing that a neural network is capable of making such classification. A low level of errors in classification confirmed that the neural network models are an effective instrument for apple classification. This model might be an alternative method for assessing the quality of apple and provide consumers with a safer food supply. [ABSTRACT FROM AUTHOR]

This paper presents a new computational approach for solving optimal control problems governed by impulsive switched systems. Such systems consist of multiple subsystems operating in succession, with possible instantaneous state jumps occurring when the system switches from one subsystem to another. The control variables are the subsystem durations and a set of system parameters influencing the state jumps. In contrast with most other papers on the control of impulsive switched systems, we do not require every potential subsystem to be active during the time horizon (it may be optimal to delete certain subsystems, especially when the optimal number of switches is unknown). However, any active subsystem must be active for a minimum non-negligible duration of time. This restriction leads to a disjoint feasible region for the subsystem durations. The problem of choosing the subsystem durations and the system parameters to minimize a given cost function is a non-standard optimal control problem that cannot be solved using conventional techniques. By combining a time-scaling transformation and an exact penalty method, we develop a computational algorithm for solving this problem. We then demonstrate the effectiveness of this algorithm by considering a numerical example on the optimization of shrimp harvesting operations. [ABSTRACT FROM AUTHOR]

The computer vision (CV) paradigm is introduced to improve the computational and processing system efficiencies through visual inputs. These visual inputs are processed using sophisticated techniques for improving the reliability of human–machine interactions (HMIs). The processing of visual inputs requires multi-level data computations for achieving application-specific reliability. Therefore, in this paper, a two-level visual information processing (2LVIP) method is introduced to meet the reliability requirements of HMI applications. The 2LVIP method is used for handling both structured and unstructured data through classification learning to extract the maximum gain from the inputs. The introduced method identifies the gain-related features on its first level and optimizes the features to improve information gain. In the second level, the error is reduced through a regression process to stabilize the precision to meet the HMI application demands. The two levels are interoperable and fully connected to achieve better gain and precision through the reduction in information processing errors. The analysis results show that the proposed method achieves 9.42% higher information gain and a 6.51% smaller error under different classification instances compared with conventional methods. [ABSTRACT FROM AUTHOR]