Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

Eddy covariance and meteorological tower in a long-hydroperiod Everglades marsh during the height of the wet season, 2008 (at SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Long-hydroperiod Everglades marsh, wet season, 2008 (near SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Eddy covariance tower in long-hydroperiod Everglades marsh in mid-dry season, 2009 (at SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Long-hydroperiod Everglades marsh under extremely dry conditions, late dry season, 2009 (near SRS-2), Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Comparative study of periphyton community structure in long and short-hydroperiod Everglades marshes

The Florida Everglades is a mosaic of short and long-hydroperiod marshes that differ in the depth, duration, and timing of inundation. Algae are important primary producers in widespread Everglades’ periphyton mats, but relationships of algal production and community structure to hydrologic variability are poorly understood. We quantified differences in algal biomass and community structure between periphyton mats in 5 short and 6 long-hydroperiod marshes in Everglades National Park (ENP) in October 2000. We related differences to water depth and total phosphorus (TP) concentration in the water, periphyton and soils. Long and short-hydroperiod marshes differed in water depth (73 cm vs. 13 cm), periphyton TP concentrations (172μg g−1 vs. 107 μg g−1, respectively) and soil TP (284 μg g−1 vs. 145 μg g−1). Periphyton was abundant in both marshes, with short-hydroperiod sites having greater biomass than long-hydroperiod sites (2936 vs. 575 grams ash-free dry mass m−2). A total of 156 algal taxa were identified and separated into diatom (68 species from 21 genera) and “soft algae” (88 non-diatom species from 47 genera) categories for further analyses. Although diatom total abundance was greater in long-hydroperiod mats, diatom species richness was significantly greater in short- hydroperiod periphyton mats (62 vs. 47 diatom taxa). Soft algal species richness was greater in long-hydroperiod sites (81 vs. 67 soft algae taxa). Relative abundances of individual taxa were significantly different among the two site types, with soft algal distributions being driven by water depth, and diatom distributions by water depth and TP concentration in the water and periphyton. Periphyton communities differ between short and long-hydroperiod marshes, but because they share many taxa, alterations in hydroperiod could rapidly

Law Enforcement Actions in Urban Spaces Governed by Violent Non-State Entities: Lessons from Latin America

In response to a crime epidemic afflicting Latin America since the early 1990s, several countries in the region have resorted to using heavy-force police or military units to physically retake territories de facto controlled by non-State criminal or insurgent groups. After a period of territory control, the heavy forces hand law enforcement functions in the retaken territories to regular police officers, with the hope that the territories and their populations will remain under the control of the state. To a varying degree, intensity, and consistency, Brazil, Colombia, Mexico, and Jamaica have adopted such policies since the mid-1990s. During such operations, governments need to pursue two interrelated objectives: to better establish the state’s physical presence and to realign the allegiance of the population in those areas toward the state and away from the non-State criminal entities. From the perspective of law enforcement, such operations entail several critical decisions and junctions, such as: Whether or not to announce the force insertion in advance. The decision trades off the element of surprise and the ability to capture key leaders of the criminal organizations against the ability to minimize civilian casualties and force levels. The latter, however, may allow criminals to go to ground and escape capture. Governments thus must decide whether they merely seek to displace criminal groups to other areas or maximize their decapitation capacity. Intelligence flows rarely come from the population. Often, rival criminal groups are the best source of intelligence. However, cooperation between the State and such groups that goes beyond using vetted intelligence provided by the groups, such as a State tolerance for militias, compromises the rule-of-law integrity of the State and ultimately can eviscerate even public safety gains. Sustaining security after initial clearing operations is at times even more challenging than conducting the initial operations. Although unlike the heavy forces, traditional police forces, especially if designed as community police, have the capacity to develop trust of the community and ultimately focus on crime prevention, developing such trust often takes a long time. To develop the community’s trust, regular police forces need to conduct frequent on-foot patrols with intensive nonthreatening interactions with the population and minimize the use of force. Moreover, sufficiently robust patrol units need to be placed in designated beats for substantial amount of time, often at least over a year. Establishing oversight mechanisms, including joint police-citizens’ boards, further facilities building trust in the police among the community. After disruption of the established criminal order, street crime often significantly rises and both the heavy-force and community-police units often struggle to contain it. The increase in street crime alienates the population of the retaken territory from the State. Thus developing a capacity to address street crime is critical. Moreover, the community police units tend to be vulnerable (especially initially) to efforts by displaced criminals to reoccupy the cleared territories. Losing a cleared territory back to criminal groups is extremely costly in terms of losing any established trust and being able to recover it. Rather than operating on a priori determined handover schedule, a careful assessment of the relative strength of regular police and criminal groups post-clearing operations is likely to be a better guide for timing the handover from heavy forces to regular police units. Cleared territories often experience not only a peace dividend, but also a peace deficit – in the rise new serious crime (in addition to street crime). Newly – valuable land and other previously-inaccessible resources can lead to land speculation and forced displacement; various other forms of new crime can also significantly rise. Community police forces often struggle to cope with such crime, especially as it is frequently linked to legal business. Such new crime often receives little to no attention in the design of the operations to retake territories from criminal groups. But without developing an effective response to such new crime, the public safety gains of the clearing operations can be altogether lost.

Fabrication of Dense Non-Circular Nanomagnetic Device Arrays Using Self-Limiting Low-Energy Glow-Discharge Processing

We describe a low-energy glow-discharge process using reactive ion etching system that enables non-circular device patterns, such as squares or hexagons, to be formed from a precursor array of uniform circular openings in polymethyl methacrylate, PMMA, defined by electron beam lithography. This technique is of a particular interest for bit-patterned magnetic recording medium fabrication, where close packed square magnetic bits may improve its recording performance. The process and results of generating close packed square patterns by self-limiting low-energy glow-discharge are investigated. Dense magnetic arrays formed by electrochemical deposition of nickel over self-limiting formed molds are demonstrated.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Factors associated with critical care nurses' communication with non-communicative patients in the ICU

Hospitalized individuals are isolated from their familiar environment at the onset of illness. Those individuals who are non-communicative are detached from the world and from life, as they previously knew it. Although nurses have long since recognized the importance of communication, patients still report the lack of iy. This study was done to identify factors influencing critical care nurses to communicate with their noncommunicative patients. The overall results of the study indicate that nurses are aware of the importance of verbal communication with patients who may be intubated, paralyzed, unconscious, comatose or neurologically impaired and are not deterred by them. Despite these results, some significant observations emerged identified. CCRN certified nurses and nurses with more years of experience were less likely to have verbal communication with noncommunicative patients. Nurses with children, spouses and those working full-time were more likely to communicate with non-communicative patients.

Two devices, each of which measure water velocity; on the right is an acoustic device that is permanently maintained at Gumbo Limbo by PI Rene Price; on the left is a 3D camera with a long fiberoptic lens, deployed for testing purposes by collaborator Evan Variano.

http://digitalcommons.fiu.edu/fce_lter_photos/1303/thumbnail.jpg

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^

Long-term Trends in Magnitude and Frequency of Extreme Rainfall Events in Florida

This study computed trends in extreme precipitation events of Florida for 1950-2010. Hourly aggregated rainfall data from 24 stations of the National Climatic Data Centre were analyzed to derive time-series of extreme rainfalls for 12 durations, ranging from 1 hour to 7 day. Non-parametric Mann-Kendall test and Theil-Sen Approach were applied to detect the significance of trends in annual maximum rainfalls, number of above threshold events and average magnitude of above threshold events for four common analysis periods. Trend Free Pre-Whitening (TFPW) approach was applied to remove the serial correlations and bootstrap resampling approach was used to detect the field significance of trends. The results for annual maximum rainfall revealed dominant increasing trends at the statistical significance level of 0.10, especially for hourly events in longer period and daily events in recent period. The number of above threshold events exhibited strong decreasing trends for hourly durations in all time periods.