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Raman spectroscopy can characterize the rich molecular vibration information of soybean milk powder samples, but difficulties arise in its direct use for sample classification and identification. Therefore, it is urgent to develop an intelligent identification technology based on Raman spectroscopy. For brand identification of soybean milk powder, this work investigates and discusses a variety of spectral processing technologies including wavelet denoising, normalization, principal component analysis, and the results show that appropriate spectral processing can improve the recognition accuracy of the random forest algorithm. Under the optimal conditions (db2 wavelet, normalization, principal component analysis, 30 decision trees), the best recognition effect of soybean milk brand identification can be achieved. The Raman spectral signal acquisition time of each sample is 40 s, and the spectra pretreatment and identification operation time only takes a few minutes. The analytical approach established in this paper has the advantages of convenient and fast Raman spectra acquisition, fast and accurate model identification., Author(s): Zheng-Yong Zhang [sup.1] , Xiao-Jing Shi [sup.1] , Ya-Ju Zhao [sup.2] , Yin-Sheng Zhang [sup.2] , Hai-Yan Wang [sup.2] Author Affiliations: (1) grid.440844.8, 0000 0000 8848 7239, School of [...]

Author(s): Shagun Bhatia Shah (corresponding author) [1]; Rajiv Chawla [1]; Uma Hariharan [2]; Seema Shukla [1] INTRODUCTION Double lumen tubes (DLTs) remain the gold-standard lung isolation devices to prevent soilage [...]

The spectral gap--the energy difference between the ground state and first excited state of a system--is central to quantum many-body physics. Many challenging open problems, such as the Haldane conjecture, the question of the existence of gapped topological spin liquid phases, and the Yang-Mills gap conjecture, concern spectral gaps. These and other problems are particular cases of the general spectral gap problem: given the Hamiltonian of a quantum many--body system, is it gapped or gapless? Here we prove that this is an undecidable problem. Specifically, we construct families of quantum spin systems on a two-dimensional lattice with translationally invariant, nearest-neighbour interactions, for which the spectral gap problem is undecidable. This result extends to undecidability of other low-energy properties, such as the existence of algebraically decaying ground-state correlations. The proof combines Hamiltonian complexity techniques with aperiodic tilings, to construct a Hamiltonian whose ground state encodes the evolution of a quantum phase-estimation algorithm followed by a universal Turing machine. The spectral gap depends on the outcome of the corresponding 'halting problem'. Our result implies that there exists no algorithm to determine whether an arbitrary model is gapped or gapless, and that there exist models for which the presence or absence of a spectral gap is independent of the axioms of mathematics., The spectral gap is one of the most important physical properties of a quantum many-body system, determining much of its low-energy physics. Gapped systems exhibit non-critical behaviour (for example, massive [...]

The vehicle routing problem with stochastic demands (VRPSD) consists of designing transportation routes of minimal expected cost to satisfy a set of customers with random demands of known probability distribution. [...]

In this paper, we study the split delivery vehicle routing problem with time windows (SDVRPTW) that is a variant of the well-known vehicle routing problem with time windows (VRPTW), where [...]

Recent studies suggest that speakers with dysarthria may be able to manipulate prosodic features sufficiently to convey information. Leveraging prosodic cues as an alternative or augmentative communication (AAC) signal may [...]

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games (1-3), but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology (4), while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems., Although it has been known for over 40 years that the three-dimensional structures of proteins are determined by their amino acid sequences (5), protein structure prediction remains a largely unsolved [...]

Train derailments are important safety issues, and they become even more critical when dangerous goods (DG) are involved. This paper is concerned with mitigating derailment risk through improved operational strategies, with a specific focus on DG marshalling practices in the train-assembly process. A new modelling framework is proposed to investigate how the position of DG railway cars affects their chances of being involved in a derailment as the train travels over a given track segment. The underlying research problem can be formulated as a linear integer programming technique. However, since solving this formulation is computationally intractable, a heuristic method has been developed based on a genetic algorithm that gives a near-optimum solution. The proposed model is applied to a hypothetical rail corridor to demonstrate how effective marshalling of DG along a train can reduce overall derailment risks. Key wards: rail transportation, derailment, dangerous goods, risk, rail yard, marshalling. Les derailments de train representenl une importanie question de seeurile, plus parliculieremenl lorsque des matieres dangereuses sont impliquees. Le present article traite de 1'attenuation du risque de deraillement par 1'amelioration des strategies operationnelles, plus specifiquement sur le positionnemem des wagons de matieres dangereuses durant le classement des wagons. Un nouveau cadre de modelisation est propose pour examiner la maniere dont la position des wagons de matieres dangereuses affecte leur chance d'etre impliques dans un deraillement lorsque le train roule sur un segment de voie ferree donne. Le probleme sous-jacent peut etre formule comme une technique de programmation lineaire par nombres entiers. Toutefois, etant donne que la resolution de cette formulation est difficilement calculable, une methode heuristique a ete developpee en se basant sur un algorithme genetique qui offre une solution pres de 1'optimal. Le modele propose est applique a un corridor hypothetique de voie ferree afin de demontrer comment un classement efficace des matieres dangereuses le long d'un train peut reduire les risques lors d'un deraillement. Mots-cles : transport ferroviaire, deraillement, matieres dangereuses, risque, cour de triage, classement des wagons., Dangerous goods derailment risks Rail accidents can be classified into three main types: derailments, collisions (including head on, rear end, and side), and highway railway grade crossing accidents. As illustrated [...]

In this paper, we prove the optimality of disturbance-affine control policies in the context of one-dimensional, constrained, multistage robust optimization. Our results cover the finite-horizon case, with minimax (worst-case) objective, [...]

We propose an approximate lifting procedure for general integer programs. This lifting procedure uses information from multiple constraints of the problem formulation and can be used to strengthen formulations and […]

In one-machine scheduling, mixed-integer program time-indexed formulations are often used to provide very good lower bounds through Lagrangian relaxations. To get an improved lower bound, we add valid cuts to […]

Mass customization requires us to select a few types of resources to produce heterogeneous classes of products. In the assortment problem addressed here, a resource unit of type j yields, […]

We consider the single-facility ordered median location problem with uncertainty in the parameters (weights) defining the objective function. We study two cases. In the first case, the uncertain weights belong […]

We view the beam orientation optimization (BOO) problem in intensity-modulated radiation therapy (IMRT) treatment planning as a global optimization problem with expensive objective function evaluations. We propose a response surface […]

This paper is concerned with the optimal constrained pruning of decision trees. We present a novel 0-1 programming model for pruning the tree to minimize some general penalty function based […]

We address a class of single-machine, hard scheduling problems with the objective of minimizing the maximum tardiness. The jobs can be preempted, but whenever a job is started or resumed, […]

The aim of this article is to find optimal or nearly optimal designs for experiments to detect spatial dependence that might be in the data. The questions to be answered [...]

We analyze the allocation of objects in a network of caches that coliaborate to service requests from customers. A thorough analysis of this problem in centralized and decentralized setups, both of which occur in practice, is essential for understanding the benefits of collaboration. A key insight offered by this paper is that an efficient implementation of cooperative cache management is possible because, in the centralized scenario, the object allocation resulting in the best social welfare can be found easily as a solution to a transportation problem. For the decentralized scenario involving selfish caches, it is shown that pure equilibria exist and that the cache network always reaches a pure equilibrium in a finite number of steps, starting from any point in the strategy space. An auction mechanism is developed to derive prices that motivate the caches to hold objects in a manner such that the optimal social welfare is attained. In the special case of symmetric caches, simple algorithms are devised to find the optimal social welfare allocation, the best pure equilibrium, and the prices for sharing objects. The results obtained in this paper should be valuable in developing and evaluating cache-management policies. Resource-sharing problems with a similar cost structure exist in a variety of other domains, and the insights gained here are expected to extend to those scenarios as well. Key words: collaborative cache management; resource sharing; peer-to-peer network; mathematical programming; game theory. History: Accepted by Barrie Nault, information systems; received May 3, 2006. This paper was with the authors 1 year and 1 month for 3 revisions. Published online in Articles in Advance October 17, 2008., 1. Introduction Caching is the process of replicating Web contents in locations where they can be readily accessed by end users. The objective is to expedite the delivery of the [...]

The problem of sharing manufacturing, inventory, or capacity to improve performance is applicable in many decentralized operational contexts. However, the solution of such problems commonly requires an intermediary or a [...]

Byline: Manuel F. Silva (Department of Electrical Engineering, Institute of Engineering of Porto, Rua Dr. Antonio Bernardino de Almeida, 4200 072 Porto, Portugal, mss@isep.ipp.pt); J.A. Tenreiro Macahdo (Department of Electrical [...]

Maritime logistics operations are full of uncertainty such as severe weather, mechanical problems, strikes, and fluctuating freight rates. Traditional ship-scheduling models ignore uncertainty, even in highly volatile markets. Although ship [...]

Byline: Nenad Sarapa, MD (Daiichi Sankyo Pharma Development, Edison, New Jersey, nsarapa@prdus.jnj.com); Justin L. Mortara, PhD (Mortara Instrument, Milwaukee, Wisconsin); Barry D. Brown (Mortara Instrument, Milwaukee, Wisconsin); Lamberto Isola, MS [...]

Byline: F. Bogard (Group of Mechanics, Materials & Structures (EA2617) Universite de Reims Champagne Ardenne, Moulin de la House BP1039 51687 Reims Cedex2, France, fabien.bogard@univ-reims.fr); P. Lestriez (Group of Mechanics, [...]

The berth allocation problem is one of the most relevant logistics problems arising in the management of container ports. Depending on assumptions made on the berthing location policy, two classes [...]

The creation of a spatial weights matrix by a procedure called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, is dependent on the use of a local spatial autocorrelation statistic. The result [...]

Purpose The purpose of this study was to determine whether an algorithm that recommended individualized changes in therapy would help providers to change therapy appropriately and improve glycemic control in [...]

We consider both branch-and-cut and column-generation approaches for the problem of finding a minimum-cost assignment of jobs with release dates and deadlines to unrelated parallel machines. Results are presented for […]

In higher education, different instructors who teach the same course may vary the instructional paths, pace, and depth of the content. These variations may result in different performances among learners. [...]