Exhaustive Enumeration Research Articles

The third AI summer: AAAI Robert S. Engelmore Memorial Lecture

The third AI summer: AAAI Robert S. Engelmore Memorial Lecture

Response time analysis of memory-bandwidth-regulated multiframe mixed-criticality systems

The multiframe mixed-criticality task model eliminates the pessimism in many systems where the worst-case execution times (WCETs) of successive jobs vary greatly by design, in a known pattern. Existing feasibility analysis techniques for multiframe mixed-criticality tasks are shared-resource-oblivious, hence unsafe for commercial-off-the-shelf (COTS) multicore platforms with a memory controller shared among all cores. Conversely, the feasibility analyses that account for the interference on shared resource(s) in COTS platforms do not leverage the WCET variation in multiframe tasks. This paper extends the state-of-the-art by presenting an analysis that incorporates the memory access stall in memory-bandwidth-regulated multiframe mixed-criticality multicore systems. An exhaustive enumeration approach is proposed for this analysis to further enhance the schedulability success ratio. The running time of the exhaustive analysis is improved by proposing a pruning mechanism that eliminates the combinations of interfering job sequences that subsume others. Experimental evaluation, using synthetic task sets, demonstrates up to 72% improvement in terms of schedulability success ratio, compared to frame-agnostic analysis.

A Combined Research Platform of Structural Morphology, Dealing with the Ordered 3D Space

The architecture of the human habitat and the whole domain of conceptual and physical space structures are mostly concerned with few basic 3D spatial features: 3D Space Networks- Lattices, Polyhedral (finite or infinite) close packing solids and space dividing surfaces. The inter- relation of these prime 3D features provides for the Quintuplet Phenomenology of 3D Space: 3D Networks are associated with close-packing arrays of polyhedra and every dual network pair is as- sociated with continuous surface partition, subdividing the space between the two. When combined with specific ‘symmetry regimes’, controlled by 3D Symmetry Space Groups, the focus is turned on Uniform 3D Space Networks-Lattices, with symmetrically identical vertex figures; on self-close- packing 3D polyhedra, and on highly symmetrical continuous surfaces, subdividing space between the dual, symmetrically identical 3D networks. Not even one of the a.m. features was exhaustively researched and enumerated in the past and that, mostly because no combined research platform was ever suggested. It is the author’s belief and conviction that such a platform might be generated and operated, when based on manipulative scanning of the fundamental domains that are associat- ed with the overall 3D Symmetry Space groups, provided that their exhaustive enumeration is com- plete.

Toward Health System Recovery in the Aftermath of Ebola Outbreak in Guinea: New Approaches for Improved Knowledge of Target Populations at the Community Level.

Background:Before the COVID-19 pandemic, Guinea has been the epicenter of the huge West Africa Ebola outbreak (2014-2016), that impact heavily the health system. Demographic information is one of the most basic data sources for health systems and services delivery, and yet can be very difficult to obtain with any accuracy. The objectives were to contribute among other to: (i) a determination of the catchment area (health coverage area and responsibility) of the Kirikilan health facility (PCM); (ii) geocoded mapping to find out exactly where these populations per sector of Kirikilan neighborhood lives; (iii) an approach for regular and systematic annual demographic follow up of target populations.Methods:The study was a 3-year community-based survey with annual follow up of the population within the quartier of Kirikilan in Dubreka Prefecture in Guinea. It was an exhaustive enumeration of the population, sector by sector of the quartier, then there was no sampling size neither estimation.Results:In October 2017 as a baseline of the study, the enumeration showed the total population was 8824 persons, 936 compounds, 1435 households, and the breakdown by sub quartier (sector) has been performed. It’s showed the interest of the mapping of the target populations with geo-referenced localization. The annual follow up by demographic enumerus showed a dramatic increase of the size of the population, including strong migration of the evicted population due to urbanization purpose in some districts of Conakry, the capital.Conclusion:The study showed the importance of the enumeration and follow up of the target populations, but also of the setting up community data based to improve the district health information system (DHIS 2) in Guinea. The approach has a best practice could be an importunity to improve data sharing, mapping, health quality access, and affordability for a sustainable health toward universal health coverage.

Non-Blockingness Verification of Bounded Petri Nets Using Basis Reachability Graphs

In this paper, we study the problem of non-blockingness verification by tapping into the basis reachability graph (BRG). Non-blockingness is a property that ensures that all pre-specified tasks can be completed, which is a mandatory requirement during the system design stage. In this paper we develop a condition of transition partition of a given net such that the corresponding conflict-increase BRG contains sufficient information on verifying non-blockingness of its corresponding Petri net. Thanks to the compactness of the BRG, our approach possesses practical efficiency since the exhaustive enumeration of the state space can be avoided. In particular, our method does not require that the net is deadlock-free.

Route Planning using Wireless Sensor Network for Garbage Collection in COVID-19 Pandemic

Garbage collection is a responsibility faced by all cities and, if not properly carried out, can generate greater costs or sanitary problems. Considering the sanitary situation due to the COVID-19 pandemic, it is necessary to take sanitary safety measures to prevent its spread. The challenge of the present work is to provide an efficient and effective solution that guarantees a garbage collection that optimizes the use of resources and prioritizes the attention to garbage containers located in or near contagion risk zones. To this end, this research proposes the integration of a basic garbage monitoring system, consisting of a wireless sensor network, and a route planning system that implements the decomposition of the Vehicle Routing problem into the subproblems of clustering and sequencing of containers using the K-Means and Ant Colony algorithms. For the monitoring of garbage, a significant reduction in the measurement error of waste level in the containers was achieved compared to other authors. About route planning, adequate error ranges were obtained in the calculation of the optimal values of distance traveled and travel time indicators with respect to an exhaustive enumeration of routes.

Computing the forcing and anti-forcing numbers of perfect matchings for graphs by integer linear programmings

The forcing polynomial and anti-forcing polynomial are two important enumerative polynomials associated with all perfect matchings of a graph. In a graph with large order, the exhaustive enumeration which is used to compute forcing number of a given perfect matching is too time-consuming to compute anti-forcing number. In this paper, we come up with an efficient method — integer linear programming, to compute forcing number and anti-forcing number of a given perfect matching. As applications, we obtain the di-forcing polynomials C60 , C70 and C72 , and as a consequence, the forcing and anti-forcing polynomials of them are obtained.

Identification of Iron-Sulfur (Fe-S) Cluster and Zinc (Zn) Binding Sites Within Proteomes Predicted by DeepMind’s AlphaFold2 Program Dramatically Expands the Metalloproteome

DeepMind’s AlphaFold2 software has ushered in a revolution in high quality, 3D protein structure prediction. In very recent work by the DeepMind team, structure predictions have been made for entire proteomes of twenty-one organisms, with >360,000 structures made available for download. Here we show that thousands of novel binding sites for iron-sulfur (Fe-S) clusters and zinc (Zn) ions can be identified within these predicted structures by exhaustive enumeration of all potential ligand-binding orientations. We demonstrate that AlphaFold2 routinely makes highly specific predictions of ligand binding sites: for example, binding sites that are comprised exclusively of four cysteine sidechains fall into three clusters, representing binding sites for 4Fe-4S clusters, 2Fe-2S clusters, or individual Zn ions. We show further: (a) that the majority of known Fe-S cluster and Zn binding sites documented in UniProt are recovered by the AlphaFold2 structures, (b) that there are occasional disputes between AlphaFold2 and UniProt with AlphaFold2 predicting highly plausible alternative binding sites, (c) that the Fe-S cluster binding sites that we identify in E. coli agree well with previous bioinformatics predictions, (d) that cysteines predicted here to be part of ligand binding sites show little overlap with those shown via chemoproteomics techniques to be highly reactive, and (e) that AlphaFold2 occasionally appears to build erroneous disulfide bonds between cysteines that should instead coordinate a ligand. These results suggest that AlphaFold2 could be an important tool for the functional annotation of proteomes, and the methodology presented here is likely to be useful for predicting other ligand-binding sites.

Analyzing Network Reliability Based on Individual Link Reliabilities Using Exhaustive Enumeration

Analyzing Network Reliability Based on Individual Link Reliabilities Using Exhaustive Enumeration

Elucidating an Atmospheric Brown Carbon Species-Toward Supplanting Chemical Intuition with Exhaustive Enumeration and Machine Learning.

Brown carbon (BrC) is involved in atmospheric light absorption and climate forcing and can cause adverse health effects. Understanding the formation mechanisms and molecular structure of BrC is of key importance in developing strategies to control its environment and health impact. Structure determination of BrC is challenging, due to the lack of experiments providing molecular fingerprints and the sheer number of molecular candidates with identical mass. Suggestions based on chemical intuition are prone to errors due to the inherent bias. We present an unbiased algorithm, using graph-based molecule generation and machine learning, which can identify all molecular structures of compounds involved in biomass burning and the composition of BrC. We apply this algorithm to C12H12O7, a light-absorbing "test case" molecule identified in chamber experiments on the aqueous photo-oxidation of syringol, a prevalent marker in wood smoke. Of the 260 million molecular graphs, the algorithm leaves only 36,518 (0.01%) as viable candidates matching the spectrum. Although no unique molecular structure is obtained from only a chemical formula and a UV/vis absorption spectrum, we discuss further reduction strategies and their efficacy. With additional data, the method can potentially more rapidly identify isomers extracted from lab and field aerosol particles without introducing human bias.

Exact Solution of Resource Leveling Problem by Exhaustive Enumeration with Parallel Programming

Kaynak dengeleme problemi (KDP) sezgisel, modern sezgisel ve matematiksel yöntemlerle çözülmektedir. Fakat belirtilen yöntemler özellikle büyük boyutlu problemler için kesin çözümü garanti edememektedir. Bu çalışmada KDP'nin aktiviteler arasındaki bağımlılık ilişkilerini ihlal etmeden ve proje süresinde uzamaya neden olmayacak şekilde bolluğu olan aktivitelerin ertelenmesi ile elde edilebilecek birbirinden farklı kaç iş programı oluşturulabileceği hesaplanmıştır. Arama uzayı olarak tanımlanan tüm uygulanabilir iş programlarının tamamının denenmesi ile garantili biçimde KDP'nin en iyi çözümü elde edilerek mevcut yöntemlerden farklı biçimde KDP'nin çözülmesi sağlanmıştır. Aktivite sayısı ile arama uzayı arasında seri bağlı aktiviteler için üstel bağıntı formülü türetilerek büyük projelerin tek işlemci ile çözümünün makul sürede gerçekleşemeyeceği belirlenmiştir. Problemin paralel programlama ile tüm işlemcilere eşit sayıda şebeke çözümü düşecek şekilde paylaştırılması sağlanmıştır. Bu çalışmada en büyüğü 36 aktiviteli olan 4 KDP arama uzayının tamamı taranıp makul sürede çözülerek geliştirilen yöntemin uygulanabilir olduğu kanıtlanmıştır. Bu yöntem ile daha küçük parçalara ayırmak sureti ile daha büyük kaynak dengeleme problemlerinin kesin çözümü elde edilebilecektir.

Weight minimization of fiber laminated composite beam for aircraft wing construction using exhaustive enumeration algorithm and numerical modeling

PurposeThis paper aims to focus on calculating the number of layers of composite laminates required to take the applied load made up of graphite/epoxy (AS4/3501-6) which can be used in many industrial applications. Optimization for minimization of weight by variation in the mechanical properties is possible by using different combinations of fiber angle, number of plies and their stacking sequence.Design/methodology/approachLots of research studies have been put forth by aerospace industry experts to improve the performance of aircraft wings with weight constraints. The orthotropic nature of the laminated composites and their ability to characterize as per various performance requirements of aerospace industry make them the most suitable material. This leads to necessity of implementing most appropriate optimization technique for selecting appropriate parameter sets and material configurations.FindingsIn this work, exhaustive enumeration algorithm has been applied for weight minimization of fiber laminated composite beam subjected to two different loading conditions by computing overall possible stacking sequences and material properties using classical laminate theory. This combinatorial type optimization technique enumerates all possible solutions with an assurance of getting global optimum solution. Stacking sequences are filtered through Tsai-Wu failure criteria.Originality/valueFinally, through the outcome of this optimization framework, eight different combinations of stacking sequences and 24-ply symmetric layup have been obtained. Furthermore, this 24-ply layup weighing 0.468 kg has been validated using finite element solver for given boundary conditions. Interlaminar stresses at top and bottom of the optimized ply layup were validated with Autodesk’s Helius composites solver.

Estimating Algorithmic Information Using Quantum Computing for Genomics Applications

Inferring algorithmic structure in data is essential for discovering causal generative models. In this research, we present a quantum computing framework using the circuit model, for estimating algorithmic information metrics. The canonical computation model of the Turing machine is restricted in time and space resources, to make the target metrics computable under realistic assumptions. The universal prior distribution for the automata is obtained as a quantum superposition, which is further conditioned to estimate the metrics. Specific cases are explored where the quantum implementation offers polynomial advantage, in contrast to the exhaustive enumeration needed in the corresponding classical case. The unstructured output data and the computational irreducibility of Turing machines make this algorithm impossible to approximate using heuristics. Thus, exploring the space of program-output relations is one of the most promising problems for demonstrating quantum supremacy using Grover search that cannot be dequantized. Experimental use cases for quantum acceleration are developed for self-replicating programs and algorithmic complexity of short strings. With quantum computing hardware rapidly attaining technological maturity, we discuss how this framework will have significant advantage for various genomics applications in meta-biology, phylogenetic tree analysis, protein-protein interaction mapping and synthetic biology. This is the first time experimental algorithmic information theory is implemented using quantum computation. Our implementation on the Qiskit quantum programming platform is copy-left and is publicly available on GitHub.

The P‐graph approach for systematic synthesis of wastewater treatment networks

AbstractWastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P‐graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.

Simultaneous process parameters and heat integration optimization for industrial organosilicon production

Traditionally, the heat integrated schemes begin from the well-designed process, design parameters of a chemical process are first optimized based on various objectives (economic, environmental, sustainable, etc.), followed by the stiff heat integration. This may result in the omission of competitive solutions and unfair process comparisons. However, the reverse procedure, potential heat integrated structures prior to parameter optimization, require an exhaustive enumeration and is time-consuming. As a solution, this work proposes a simultaneous process parameter and heat integration optimization approach, by incorporating the consideration of heat integrated networks into a stochastic optimization procedure. Four complex industrial organosilicon production configurations with 4 or 5 columns, as illustrative examples, verify the feasibility of the proposed approach.

Computational Techniques for Investigating Information Theoretic Limits of Information Systems

Computer-aided methods, based on the entropic linear program framework, have been shown to be effective in assisting the study of information theoretic fundamental limits of information systems. One key element that significantly impacts their computation efficiency and applicability is the reduction of variables, based on problem-specific symmetry and dependence relations. In this work, we propose using the disjoint-set data structure to algorithmically identify the reduction mapping, instead of relying on exhaustive enumeration in the equivalence classification. Based on this reduced linear program, we consider four techniques to investigate the fundamental limits of information systems: (1) computing an outer bound for a given linear combination of information measures and providing the values of information measures at the optimal solution; (2) efficiently computing a polytope tradeoff outer bound between two information quantities; (3) producing a proof (as a weighted sum of known information inequalities) for a computed outer bound; and (4) providing the range for information quantities between which the optimal value does not change, i.e., sensitivity analysis. A toolbox, with an efficient JSON format input frontend, and either Gurobi or Cplex as the linear program solving engine, is implemented and open-sourced.

Bishop's hat silicene: a planar square silicon bilayer decorated with adatoms.

We investigate a family of free-standing quasi-two-dimensional silicon structures based on a planar square bilayer with adatom decorations. When attached to the bilayer, these adatoms form local reconstructions which resemble either a bishop's hat or elongated square bipyramids. We systematically constructed members of this family via exhaustive enumeration and then studied them using tight-binding and density-functional theory. We find that this geometry contributes significantly to the stability of the resulting structures, with some squared bilayers energetically more stable than the honeycomb bilayers. The most interesting phases were then characterized in more detail, and they all turned out metallic. Finally, we propose the [100] surface of ZrO2 as the most suitable substrate for the synthesis of these two-dimensional phases.

Conceptual State Analysis

Conceptual State Analysis (CSA) is the process of defining, exploring, and reasoning about state attributes and state spaces in complex system architectures. Model-Based State Analysis enhances CSA with formal modeling and analysis methods. We propose a process for generating the state vector of a given system architecture, based on a graph representation of the architecture’s model in Object-Process Methodology. A robust graph data structure that represents the model is queried to produce the architecture’s state space. The process facilitates analysis, reasoning, and model revision based on improved understanding of state vectors and state spaces. State attribute refinements within the model allow for model validity, viability, and reusability as the architecture evolves, with multiple agents, attributes, and attribute state values. The CSA approach advocates and facilitates careful, dynamic, and interactive state space exploration in lieu of exhaustive upfront enumeration of state space permutations. The results can be fed into other analysis, simulation, or visualization tools. We demonstrate CSA on driver assistance technology.

Z-matrix template-based substitution approach for enumeration of 3D molecular structures

The exhaustive enumeration of 3D chemical structures based on Z-matrix templates has recently been used in the quantum chemical investigation of constitutional isomers, diastereomers and rotamers. This simple yet powerful initial structure generation approach can apply beyond the investigation of compounds of identical formula by quantum chemical methods. This paper provides a comprehensive description of the overall concept followed by a practical tutorial to the approach.•The four steps required for Z-matrix template-based substitution are template construction, generation of tuples for substitution sites, removal of duplicate tuples and substitution on the template.•The generated tuples can be used to create chemical identifiers to query compound properties from chemical databases.•All of these steps are demonstrated in this paper by common model compounds and are very straightforward for an undergraduate audience to reproduce. A comparison of the approach in this paper and other options is also discussed.

Production, Recruitment, and Retention of Health Workers in Rural Areas in the Philippines

Objective. This study aimed to examine capacities and initiatives of the local government units (LGUs) in the Philippines in producing, recruiting and retaining human resources for health (HRH). Methods. This 2-phase, descriptive, cross-sectional study employed multiple methods such as key informant interviews (KIIs), focus group discussions (FGDs) (for Phase 1) and surveys (for Phase 2) in rural municipalities across the country. Phase 1: We employed qualitative methods to develop a quantitative questionnaire in 22 purposefully selected municipalities. An exhaustive enumeration of responses from the guide questions of the FGDs and KIIs were then translated into a questionnaire. Phase 2: We administered the survey questionnaire from phase 1 to another 67 municipalities to obtain a greater representation of the intended study population as well as quantify results from the qualitative methods. We analyzed data with descriptive statistics. Results. Initiatives in HRH production were mainly on provision of scholarships. Active recruitment was not done due to lack of available pool of applicants, lack of vacant positions, financial constraints leading to utilization of deployment programs and temporary nature of employment. Recruitment was influenced by budgetary constraints, political biases, dependency on deployment programs and other hired temporary HRH, and set health worker-to-population ratios. Initiatives to retain HRH were largely financial in nature based on pertinent policies. The capacities of LGUs to produce, recruit, and retain needed HRH were strongly dependent on the internal revenue allotment (IRA), along with their local income. Conclusion. Rural municipalities in the Philippines have initiatives to produce, recruit, and retain HRH. However, these are not enough to meet the needed number of competent and highly motivated HRH that are expected to respond to the unique needs of the rural municipalities. Strategies to increase the capacity of LGUs, address the shortage of HRH, and increase motivation of HRH are recommended.