The role of artificial intelligence techniques in scheduling systems

Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture

Scheduling spacecraft operations

A prototype scheduling system named MAESTRO currently under development is being used to explore possible approaches to the spacecraft operations scheduling problem. Results indicate that the appropriate combination of heuristic and other techniques can provide an acceptable solution to the scheduling problem over a wide range of operational scenarios and management approaches. These can include centralized or distributed instrument or systems control, batch or incremental scheduling, scheduling loose resource envelopes or exact profiles, and scheduling with varying degrees of user intervention. Techniques used within MAESTRO to provide this flexibility and power include constraint propagation mechanisms, multiple asynchronous processes, prioritized transaction-based command management, resource opportunity calculation, user-alterable selection and placement mechanisms, and maintenance of multiple schedules and resource profiles. These techniques and scheduling complexities requiring them are discussed

Managing temporal relations

Various temporal constraints on the execution of activities are described, and their representation in the scheduling system MAESTRO is discussed. Initial examples are presented using a sample activity described. Those examples are expanded to include a second activity, and the types of temporal constraints that can obtain between two activities are explored. Soft constraints, or preferences, in activity placement are discussed. Multiple performances of activities are considered, with respect to both hard and soft constraints. The primary methods used in MAESTRO to handle temporal constraints are described as are certain aspects of contingency handling with respect to temporal constraints. A discussion of the overall approach, with indications of future directions for this research, concludes the study

Space station automation of common module power management and distribution

The purpose is to automate a breadboard level Power Management and Distribution (PMAD) system which possesses many functional characteristics of a specified Space Station power system. The automation system was built upon 20 kHz ac source with redundancy of the power buses. There are two power distribution control units which furnish power to six load centers which in turn enable load circuits based upon a system generated schedule. The progress in building this specified autonomous system is described. Automation of Space Station Module PMAD was accomplished by segmenting the complete task in the following four independent tasks: (1) develop a detailed approach for PMAD automation; (2) define the software and hardware elements of automation; (3) develop the automation system for the PMAD breadboard; and (4) select an appropriate host processing environment

Influence of chemical activation of a 35% hydrogen peroxide bleaching gel on its penetration and efficacy--in vitro study

OBJECTIVES: The aim of this study was to evaluate the effects of chemical activation of hydrogen peroxide (HP) gel on colour changes and penetration through the tooth structure. METHODS: One hundred and four bovine incisors were used. One dentine (CD) disc and one enamel-dentine (ED) disc were prepared from each tooth. They were positioned over artificial pulpal chambers and the bleaching was performed with an experimental 35% HP gel. Two control and six experimental groups were prepared. In the positive control group (PC) no chemical activator was used. In the negative control group (NC) the specimens did not receive any bleaching. Each experimental group received a different chemical activator (manganese gluconate-MG; manganese chlorite-MC; ferrous sulphate-FS; ferrous chlorite-FC; and mulberries root extract-MRE). After the bleaching procedure a sample of solution was collected from the artificial pulpal chamber and the HP concentration was measured. The data were analysed using ANOVA, Tukey's, and Dunnett's tests. RESULTS: The groups MG and FS showed a significantly lower penetration of HP than the PC group. For the parameter Delta E, all the groups, with the exception of the group MRE, showed a significantly higher means in relation to the PC group in ED colour. For dentine colour, just the groups MG and FS had significant differences in relation to PC. CONCLUSIONS: The addition of MG and FS decreases the penetration of HP. The chemical activation using metal salts tested was effective in increasing the bleaching effect

Integrated Photonic AI Accelerators under Hardware Security Attacks: Impacts and Countermeasures

Integrated photonics based on silicon photonics platform is driving several application domains, from enabling ultra-fast chip-scale communication in high-performance computing systems to energy-efficient optical computation in artificial intelligence (AI) hardware accelerators. Integrating silicon photonics into a system necessitates the adoption of interfaces between the photonic and the electronic subsystems, which are required for buffering data and optical-to-electrical and electrical-to-optical conversions. Consequently, this can lead to new and inevitable security breaches that cannot be fully addressed using hardware security solutions proposed for purely electronic systems. This paper explores different types of attacks profiting from such breaches in integrated photonic neural network accelerators. We show the impact of these attacks on the system performance (i.e., power and phase distributions, which impact accuracy) and possible solutions to counter such attacks

SerIOS: Enhancing Hardware Security in Integrated Optoelectronic Systems

Silicon photonics (SiPh) has different applications, from enabling fast and high-bandwidth communication for high-performance computing systems to realizing energy-efficient optical computation for AI hardware accelerators. However, integrating SiPh with electronic sub-systems can introduce new security vulnerabilities that cannot be adequately addressed using existing hardware security solutions for electronic systems. This paper introduces SerIOS, the first framework aimed at enhancing hardware security in optoelectronic systems by leveraging the unique properties of optical lithography. SerIOS employs cryptographic keys generated based on imperfections in the optical lithography process and an online detection mechanism to detect attacks. Simulation and synthesis results demonstrate SerIOS's effectiveness in detecting and preventing attacks, with a small area footprint of less than 15% and a 100% detection rate across various attack scenarios and optoelectronic architectures, including photonic AI accelerators

Efficient Defense Against Model Stealing Attacks on Convolutional Neural Networks

Model stealing attacks have become a serious concern for deep learning models, where an attacker can steal a trained model by querying its black-box API. This can lead to intellectual property theft and other security and privacy risks. The current state-of-the-art defenses against model stealing attacks suggest adding perturbations to the prediction probabilities. However, they suffer from heavy computations and make impracticable assumptions about the adversary. They often require the training of auxiliary models. This can be time-consuming and resource-intensive which hinders the deployment of these defenses in real-world applications. In this paper, we propose a simple yet effective and efficient defense alternative. We introduce a heuristic approach to perturb the output probabilities. The proposed defense can be easily integrated into models without additional training. We show that our defense is effective in defending against three state-of-the-art stealing attacks. We evaluate our approach on large and quantized (i.e., compressed) Convolutional Neural Networks (CNNs) trained on several vision datasets. Our technique outperforms the state-of-the-art defenses with a $\times37$ faster inference latency without requiring any additional model and with a low impact on the model's performance. We validate that our defense is also effective for quantized CNNs targeting edge devices.Comment: Accepted for publication at 2023 International Conference on Machine Learning and Applications (ICMLA

O cuidado na educação infantil: contribuições da área da saúde

This article focuses on the care for children in preschools and the relevant contributions from the health care field. It reflects on care, its relationship with the child, the family, and the institutional environment and professionals, and considers the binomial relationship of care and education. To care and educate are seen here as pedagogical practices, forms of mediation, interaction, and a life practice for healthcare prevention and protection and citizen action.O cuidado na Educação Infantil: contribuições da área da saúde. O presente artigo enfoca o cuidado com as crianças na Educação Infantil e as contribuições da área da saúde. Faz uma reflexão acerca do cuidado, sua relação com a criança, família, ambiente institucional, profissionais e retrata a correlação do binômio cuidar e educar. Cuidar e educar são vistos aqui como prática pedagógica, forma de mediação, interação, prática de vida, de prevenção e proteção da saúde e ação cidadã