In past decades, manufacturing companies have paid considerable attention to using their available resources in the most efficient way to satisfy customer demands. This endeavor is supported by many ...Industry 4.0 methods. One of these is called MES (Manufacturing Execution System), which is applied for monitoring and controlling manufacturing by recording and processing production-related data. This article presents a possible method of implementation of a risk-adjusted production schedule in a data-rich environment. The framework is based on production datasets of multiple workshops, which is followed by statistical analysis, and its results are used in stochastic network models. The outcome of the simulation is implemented in a production scheduling model to determine how to assign the production among workshops. After collecting the necessary data, the reliability indicator-based stochastic critical path method was applied in the case study. Two cases were presented based on the importance of inventory cost and two different scheduling results were created and presented. With the objective of the least inventory cost, the production was postponed to the latest time possible, which means that workshops had more time to finish their previous work on the first day due to the small production quantity. When the cost was not relevant, the production started on the first day of each workshop, and the production was completed before the deadline. These are optimal solutions, but alternative solutions can also be performed by the decision maker based on the results. The use of the modified stochastic critical path method and its analysis shed light on the deficiency of the production, which is a merit in the continuous improvement process and the estimation of the total project time.
This paper presents semantic-based methods for the understanding of human movements in robotic applications. To understand human movements, robots need to first, recognize the observed or ...demonstrated human activities, and secondly, learn different parameters to execute an action or robot behavior. In order to achieve that, several challenges need to be addressed such as the automatic segmentation of human activities, identification of important features of actions, determine the correct sequencing between activities, and obtain the correct mapping between the continuous data and the symbolic and semantic interpretations of the human movements. This paper aims to present state-of-the-art semantic-based approaches, especially the new emerging approaches that tackle the challenges of finding generic and compact semantic models for the robotics domain. Finally, we will highlight potential breakthroughs and challenges for the next years such as achieving scalability, better generalization, compact and flexible models, and higher system accuracy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•software vulnerability•exploitability assessment•automated exploit generation
Assessing the exploitability of vulnerabilities is critical for defenders. But the vulnerability-triggering samples ...available for analysts often do not trigger exploitable states, making it hard to accurately assess whether the underlying vulnerabilities are exploitable. Several customized fuzzing solutions have been proposed to address this problem, by searching for new vulnerability-triggering test cases that can enter exploitable program states. However, such solutions are inefficient and in general take an overwhelmingly long time to find exploitable states, due to the large number of program paths to explore and complicated path constraints to satisfy. In this paper, we present a new automated solution Tunter to assess the exploitability of vulnerabilities. It could explore exploitable program states and generate working exploits, even if only non-exploitable vulnerability-triggering samples are given. It adopts two novel techniques: (1) a taint-guided exploration procedure to explore candidate exploitable states; and (2) a pruning mechanism to prune unwanted states for exploitation to alleviate the state explosion issue faced by symbolic execution. We have implemented a prototype of Tunter and evaluated it on 14 capture-the-flag (CTF) programs and two real-world applications. The experimental results demonstrate that it has significant performance than state-of-the-art solution Revery (Wang et al., 2018). Specifically, it finds exploitable states for these 16 programs with a 75% recall and an 88.9% precision, and eventually generates working exploits for 11 out of these 16 programs. Moreover, Tunter is 41.02 times faster than Revery.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this work, we study an optimization problem arising when managing a renewable resource in finite time. The resource is assumed to evolve according to a logistic stochastic differential equation. ...The manager harvests partially the resource at any time and sell it at a stochastic market price. She equally decides to renew part of the resource but uniquely at deterministic times. However, we realistically assume that there is a delay in the renewing order. By using the dynamic programming theory, we characterize our value function as the unique solution to a PDE. To complete our study, we give an algorithm to compute the value function and optimal strategy. Some numerical illustrations are also provided.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Musik als Spiel - Spiel als Musik Marion Saxer (verst.), Karin Dietrich, Julian Kämper / Sebastian Rose / Marion Saxer (verst.), Karin Dietrich, Julian Kämper
2021, 20210720, Volume:
40
eBook
Außermusikalische Prinzipien des Spiels - freie wie streng regelbasierte - können Kompositionsprozesse, Aufführungssituationen oder Rezeptionsvorgänge prägen und bestehende Denkmuster aufbrechen. ...Daher hat der Spielbegriff als ästhetische Kategorie in den Künsten des 20. Jahrhunderts deutlich an Relevanz gewonnen und bis heute entstehen vielfältige kompositorische Konzepte, die Formen, Interaktionen und Oberflächen von analogen wie digitalen Spielen adaptieren. Die Beiträger*innen aus den Bereichen Komposition, Musik- und Kulturwissenschaft und Spieleentwicklung untersuchen markante Beispiele, in denen auf je eigene Weise Musik und Spiel als zwei eigenständig gewachsene Kulturformen zusammengeführt werden.
This research uses normative juridical approach to study on the analysis of the death penalty executions and the legal policy of death executions in Indonesia. There are delays on death executions ...for the convicted person since they entitled to using rights namely filing a judicial review (PK/Peninjauan Kembali). Furthermore, the legal loophole in the execution of the death penalty by the publication of the Constitutional Court Number 107 / PUU-XIII / 2015 which assert that the Attorney as the executor can ask the convicted person or his family whether to use their rights or not if the convict clearly does not want to use his rights, the executions will be carried out. Legal policy on threats and the implementation of the death penalty in the draft of criminal code was agreed by draftsman of the bill with the solutions. The draftsman of the bill agrees that the death penalty will be an alternative punishment sentenced as a last resort to protect the society. The bill also regulates that the execution among others include that the execution can be delayed by ten years probations. If the public reaction on the convict is not too large or convict has regret and could fix it or the role in the crime is not very important and there is a reason to reduce punishment, the death penalty may be changed. For pregnant women and the mentally ill convicts the execution can only be carried after the birth and the person has recovered from mental illness. The existence of this solutions is still kept putting the death penalty in criminal law, whereas the effectiveness of the death penalty is scientifically still in doubt to solve crimes and to prevent crimes by the death penalty punishment.
This paper presents SAILFISH, a scalable system for automatically finding state-inconsistency bugs in smart contracts. To make the analysis tractable, we introduce a hybrid approach that includes (i) ...a light-weight exploration phase that dramatically reduces the number of instructions to analyze, and (ii) a precise refinement phase based on symbolic evaluation guided by our novel value-summary analysis, which generates extra constraints to over-approximate the side effects of whole-program execution, thereby ensuring the precision of the symbolic evaluation. We developed a prototype of SAILFISH and evaluated its ability to detect two state-inconsistency flaws, viz., reentrancy and transaction order dependence (TOD) in Ethereum smart contracts. Our experiments demonstrate the efficiency of our hybrid approach as well as the benefit of the value summary analysis. In particular, we show that SAILFISH outperforms five state-of the-art smart contract analyzers (SECURIFY, MYTHRIL, OYENTE, SEREUM and VANDAL) in terms of performance, and precision. In total, SAILFISH discovered 47 previously unknown vulnerable smart contracts out of 89,853 smart contracts from ETHERSCAN.
IntroductionThe aim of this study was to evaluate the German falls prevention program 'Staying safe and active in old age - falls prevention', which is already established in practice.MethodsThe ...single-arm intervention study consisted of two time points, 6 months apart, to evaluate the multifactorial falls prevention program (n = 125 at Time 2). We observed the groups and their trainers and assessed which behavior change techniques (BCTs) were used. According to our evaluation framework, changes in the following three domains were assessed: (a) fall-related variables (i.e. number of falls, fear of falling), (b) physical functioning (i.e. performance-based gait speed, coordination, self-reported leg strength, balance, as well as habitual execution of the exercises), and (c) psychosocial functioning (i.e. quality of life, activities of daily living, mobility, and loneliness). Linear mixed models were used to determine changes in each variable.ResultsDemonstration of behavior was the most frequently used BCT. The program showed significant benefits for fear of falling, balance, coordination, habitual execution, and loneliness over time (Cohen's d between -0.59 and 1.73). Number of falls, gait speed, coordination (dual task), activities of daily living, and quality of life were maintained (Cohen's d between -0.26 and 0.30), whereas leg strength and mobility decreased significantly at Time 2 (Cohen's d = -0.55 and -0.36).DiscussionGroup-based falls prevention programs may facilitate social integration among older adults and may also enhance and maintain physical functioning in old age.Trial registration: German Clinical Trials Register identifier: DRKS00012321.
On knowledge in action Ferretti, Gabriele; Zipoli Caiani, Silvano
Theory & psychology,
10/2023, Volume:
33, Issue:
5
Journal Article
Peer reviewed
What mental states guide the execution of our actions? It is generally agreed that the execution of an action is guided by the relevant knowledge state concerning how to perform that action. However, ...not all agree on which mental states underlie such a knowledge. Some suggest that knowing how to perform an action has mainly to do with the propositional representation about the way to execute that action. Those opposing this view stress the role of the motor, non-propositional representation as the mental state responsible for action performance. The aim of this article is to overcome this dichotomy by showing that an explanation of the cognitive processes underlying knowing how to perform an action needs both propositional and motor states. We defend this view by providing an account of the way in which our propositional knowledge about an action is constituted by the motor representation that guides the execution of that action.
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The widespread adoption of Industrial Internet of Things (IIoT)-based applications has driven the emergence and development of cloud-related computing paradigms with the ability to seamlessly ...leverage cloud resources. Heterogeneous resources, mobility factors in IoT, and dynamic behavior make it challenging for the corresponding virtual machine (VM) scheduling problem to address the processing effectiveness of application requests in these kinds of cloud environments. Based on reinforcement learning theory, this article proposes an online VM scheduling scheme (OSEC) for joint energy consumption and cost optimization that divides the scheduling process into two parts: VM allocation and VM migration. First, all the VMs and the physical machines (PMs) are regarded as a set of states and actions in the cloud environment, and the Q-learning feedback is used to achieve the iterative computation of Q-values to obtain the optimal parallel allocation sequence for multiple VMs. Then, VMs are migrated among the active PMs according to a grouping policy and the best-fit principle to achieve dynamic consolidation of the resources in the data center. Finally, experimental results show that compared with state-of-the-art algorithms under different conditions, the proposed method reduces energy consumption by approximately 18.25%, VM execution costs by approximately 21.34%, and service level agreement (SLA) violations by approximately 90.51%.
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