Time Dimension for Business News in the Knowledge Warehouse

This paper proposes a data structure to support the integration of business news and data in the knowledge warehouse using the Temporal Document Retrieval Model (TDRM). Temporal document retrieval takes into account the time context expressed as temporal phrases in the document content. The maintenance and scalability of the proposed data cluster is discussed. The results of temporal document retrieval experiments based on typical and ad-hoc time constraints, performed on a large corpus of business news are reported. The experiments showed that the instantaneous TDRM-based retrieval using the proposed cluster is possible with the currently available database technology and confirmed the highly constraining character of the temporal context

The obnoxious facilities planar p-median problem

In this paper we propose the planar obnoxious p-median problem. In the p-median problem the objective is to find p locations for facilities that minimize the weighted sum of distances between demand points and their closest facility. In the obnoxious version we add constraints that each facility must be located at least a certain distance from a partial set of demand points because they generate nuisance affecting these demand points. The resulting problem is extremely non-convex and traditional non-linear solvers such as SNOPT are not efficient. An efficient solution method based on Voronoi diagrams is proposed and tested. We also constructed the efficient frontiers of the test problems to assist the planers in making location decisions

Directional approach to gradual cover: the continuous case

The objective of the cover location models is covering demand by facilities within a given distance. The gradual (or partial) cover replaces abrupt drop from full cover to no cover by defining gradual decline in cover. In this paper we use a recently proposed rule for calculating the joint cover of a demand point by several facilities termed "directional gradual cover". Contrary to all gradual cover models, the joint cover depends on the facilities' directions. In order to calculate the joint cover, existing models apply the partial cover by each facility disregarding their direction. We develop a genetic algorithm to solve the facilities location problem and also solve the problem for facilities that can be located anywhere in the plane. The proposed modifications were extensively tested on a case study of covering Orange County, California

Community Paramedicine to Proactively Combat Opioid Overdoses

The growing problem of opioid overdoses has traditionally been combated with a reactive approach. In New Castle County, DE, a Community Paramedicine program has been implemented to make an attempt at stopping overdoses before they happen. Community Paramedicine is a mobile integrated health program that trains paramedics to visit and treat high risk patients at their homes on a non emergent basis. The aim is to prevent acute exacerbation of chronic disease. In other jurisdictions, this model has been used in an effort to reduce abuse of the 911 system and Emergency Department by high utilizers of the 911 system. Opioid addiction fits this model well: it is a chronic disease that has acute flare ups (overdoses) that are acutely life threatening. In addition to the standard treatment that addicted patients receive, visits are made to their home. A team of both a paramedic and a social worker visit the patient, both assessing/treating the patient medically as well as training family members on naloxone administration. This program differs from other addiction treatment models because it allows easier access to care for patients. This study is a feasibility assessment utilizing census data to pinpoint the locations that would be ideal to focus efforts for a pilot program of a Community Paramedicine program. Zip codes that contained the highest proportion of high utilizers were identified and recommendations were made to assist the county government with targeting efforts to make the greatest impact

Dynamic Prediction of retail Website Visitors\u27 Intentions

This paper presents a model for identifying general intentions of consumers visiting a retail website. When visiting a transactional website, consumers have various intentions such as browsing (i.e., no purchase intention), purchasing a product in the near future, or purchasing a particular product during their current visit. By predicting these intentions early in the visit, online merchants could personalize their offer to better fulfill the needs of consumers. We propose a simple model which enables classifying visitors according to their intentions after only four traversals (clicks). The model is based solely on navigation patterns which can be automatically extracted from clickstream. The results are presented and extensions of the model are proposed

Measuring the Effect of a Resuscitation Academy on Out of Hospital Cardiac Arrest Resuscitation Rates

According to the American Heart Association (AHA), rates of successful resuscitation after out of hospital cardiac arrest (OHCA) vary across the country. Amongst 132 counties in the United States, the rates of CPR survival to hospital discharge ranges between 3.4%-22.0%, and the rates of CPR survival with functional recovery ranges from 0.8%-20.1%. This large degree of variability between regions has been improved through programs that educate Emergency Medical Service (EMS) departments on ways to improve outcomes through an evidence-based lens. The Medic One EMS department in Seattle and King County, Washington developed a resuscitation academy (RA) that improved cardiac arrest survival from 26% in 2002 to 62% in 2013. In 2015, The New Castle County, Delaware EMS (NCCEMS) department modeled a RA after the Medic One EMS department. This study measured the effect on the number of patients experiencing return of spontaneous circulation (ROSC) and the cerebral performance category (CPC) scores for discharged patients. Data from 599 atraumatic out-of-hospital cardiac arrests (OHCA) was collected from 2009-2019, and 99 cases met Utstein inclusion criteria. Next, the study categorized if at least one RA was implemented prior to these cases to determine the RA’s effect. Implementation of one RA on ROSC outcomes yielded a significant improvement (p = .028), with a small to medium strength of effect (Cramer’s V=0.221); this indicates that the administration of at least one RA had a moderate and significant effect on increasing ROSC in patients suffering from OHCA. Administration of at least one RA did not demonstrate a significant effect on eventual patient outcomes as indicated by discharge CPC score (p = .488). This indicates that there was no statistically significant effect on the cerebral performance of patients who suffered OHCA upon discharge

An effective iterated greedy algorithm for the mixed no-idle flowshop scheduling problem

In the no-idle flowshop, machines cannot be idle after finishing one job and before starting the next one. Therefore, start times of jobs must be delayed to guarantee this constraint. In practice machines show this behavior as it might be technically unfeasible or uneconomical to stop a machine in between jobs. This has important ramifications in the modern industry including fiber glass processing, foundries, production of integrated circuits and the steel making industry, among others. However, to assume that all machines in the shop have this no-idle constraint is not realistic. To the best of our knowledge, this is the first paper to study the mixed no-idle extension where only some machines have the no-idle constraint. We present a mixed integer programming model for this new problem and the equations to calculate the makespan. We also propose a set of formulas to accelerate the calculation of insertions that is used both in heuristics as well as in the local search procedures. An effective iterated greedy (IG) algorithm is proposed. We use an NEH-based heuristic to construct a high quality initial solution. A local search using the proposed accelerations is employed to emphasize intensification and exploration in the IG. A new destruction and construction procedure is also shown. To evaluate the proposed algorithm, we present several adaptations of other well-known and recent metaheuristics for the problem and conduct a comprehensive set of computational and statistical experiments with a total of 1750 instances. The results show that the proposed IG algorithm outperforms existing methods in the no-idle and in the mixed no-idle scenarios by a significant margin.Quan-Ke Pan is partially supported by the National Science Foundation of China 61174187, Program for New Century Excellent Talents in University (NCET-13-0106), Science Foundation of Liaoning Province in China (2013020016), Basic scientific research foundation of Northeast University under Grant N110208001, Starting foundation of Northeast University under Grant 29321006, and Shandong Province Key Laboratory of Intelligent Information Processing and Network Security (Liaocheng University). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "RESULT - Realistic Extended Scheduling Using Light Techniques" with reference DPI2012-36243-C02-01 co-financed by the European Union and FEDER funds and by the Universitat Politecnica de Valencia, for the project MRPIV with reference PAID/2012/202.Pan, Q.; Ruiz García, R. (2014). An effective iterated greedy algorithm for the mixed no-idle flowshop scheduling problem. Omega. 44:41-50. https://doi.org/10.1016/j.omega.2013.10.002S41504

The planar multiple obnoxious facilities location problem: A Voronoi based heuristic

Consider the situation where a given number of facilities are to be located in a convex polygon with the objective of maximizing the minimum distance between facilities and a given set of communities with the important additional condition that the facilities have to be farther than a certain distance from one another. This continuous multiple obnoxious facility location problem, which has two variants, is very complex to solve using commercial nonlinear optimizers. We propose a mathematical formulation and a heuristic approach based on Voronoi diagrams and an optimally solved binary linear program. As there are no nonlinear optimization solvers that guarantee optimality, we compare our results with a popular multi-start approach using interior point, genetic algorithm (GA), and sparse non-linear optimizer (SNOPT) solvers in Matlab. These are state of the art solvers for dealing with constrained non linear problems. Each instance is solved using 100 randomly generated starting solutions and the overall best is then selected. It was found that the proposed heuristic results are much better and were obtained in a fraction of the computer time required by the other methods.The multiple obnoxious location problem is a perfect example where all-purpose non-linear non-convex solvers perform poorly and hence the best way forward is to design and analyze heuristics that have the power and the exibility to deal with such a high level of complexity