Deriving industrial logistics hub reference models for manufacturing based economies

Global enterprises require extended logistics operations that integrate channel intermediaries into the network. The method for deriving integrated models for logistics hubs that improve the efficiency of manufacturers’ global operations is the focus of this paper. Under government sponsorship, six industrial logistics hubs were implemented by leading manufacturing sectors across Taiwan over a five year period from 2004 until 2008. Each industry sector had unique industry characteristics, business strategies, and logistics models. Therefore, this paper describes how generalized and quick to implement integrated logistics hubs are developed by studying the successful reference models and systems used by six independent industrial sectors. The research results provide a field tested method for deriving integrated logistics hub models in different manufacturing economies with notes that provide sufficient methodological detail for repeating the construction of logistics hubs in other manufacturing economies.     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

Google Wave: Have CTSA-Minded Institutions Caught It?

BACKGROUND: Google Wave was touted as the next big communication tool-combining e-mail, social networking, and chat within a single "wave"-with the potential to create a new world for collaboration. Information professionals who are knowledgeable of this tool and its capabilities could become uniquely situated to use it, evaluate it, and teach it. This seemed especially true for those working within Clinical and Translational Science Award (CTSA)-minded institutions, given the promise of interdisciplinary collaboration between investigators and the potential for creating new authorship models. This case study on Google Wave users who are affiliated with CTSA-minded institutions, was designed for and presented at the Evidence-Based Scholarly Communication Conference held by the University of New Mexico Health Sciences Library and Information Center. It provides an early evidence based evaluation of Google Wave's potential. METHODS: Two "waves" were created. The first consisted of five survey questions designed to collect demographic data on the respondents' roles, a general impression of Wave, the specific tools within Wave that might be useful, and potential collaborators with whom the respondents might use Wave. The second wave was a private, guided discussion on Wave's collaboration potential. Individuals from CTSA-minded institutions were invited to participate with messages on Twitter, forums, blogs, and electronic mail lists, although there were difficulties reaching out to these institutions as a group. RESULTS: By the conclusion of the study, only a small number of people (n=11, with a viable n=9) had responded to the survey. Given this small result set, it made sense to group the responses by the respondents' roles (CTSA staff and researchers, support staff, medical librarian, or general public) and to treat them as individual cases. Most of the respondents were librarians and support staff who felt that Wave might have potential for collaboration; there were no CTSA researcher respondents. For the second part of the study, the discussion wave, only one participant explicitly expressed interest in joining. All were invited to join, but there was no participation in the discussion wave at the conclusion of the study. CONCLUSIONS: The results of this study implied that Google Wave was not on the forefront of CTSA-minded institutions' communication strategies. However, it was being used, and it did demonstrate new collaboration and authorship capabilities. Being generally aware of these capabilities may be useful to information professionals who seek to be current and informed regarding developing technology and to those interested in scholarly communication practices. In addition, the difficulties encountered during this case study in attempting to reach out to CTSA-minded institutions raised the question of how members currently communicate with each other as institutions and as individuals. There was a lesson learned in the usefulness of doing case-study research to evaluate new technologies; the cost in terms of time was relatively low, and knowledge about the technology itself was gained while establishing a base level of evidence to potentially build on in the future.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Fuzzy multiple goal programming applied to TFT-LCD supplier selection by downstream manufacturers

In today’s highly competitive environment, a good supply chain relationship is essential for a company to survive and to acquire reasonable profit. While a few large companies may be able to vertically integrate from the design stage to the final distribution of the entire supply chain, most companies can only focus on their specialized functions and to cooperate with upstream or downstream companies. Supplier selection, as a result, is very important for maintaining strategic alliances. The objective of this paper is to develop a fuzzy multiple goal programming (FMGP) model to help downstream companies to select thin film transistor liquid crystal display (TFT-LCD) suppliers for cooperation. Fuzzy analytic hierarchy process (FAHP) is applied first to analyze the importance of multiple factors by incorporating experts’ opinion, and these factors include cost, yield and number of suppliers. Multi-choice goal programming is used next to consider the limits of various resources and to formulate the constraints. From the experimental design and examination, we can testify that the proposed model not only can consider multi-choice goals, decision-making behavior and limit of resources, it can also allocate the purchase among the selected supplier(s).     

Evaluation of terrain and canopy height products in central African tropical forests

Since the introduction of space-based altimetry data into the science community, global products associated with elevation and vegetation metrics have been heavily utilized for a variety of ecological applications. Satellite remote sensing enables the collection of global (or near-global), standardized data sets, which can be used in their original form or used as inputs along with other data sets in generating new products. Recent effort has focused on using available data to generate maps of tree heights at a global scale in the service of a better understanding of above ground biomass distribution and its effects on global carbon storage. However, global data sets, while validated at a global scale, often display local and regional variations in accuracy which must be quantified before applying those data sets to smaller scale studies. This work addresses the need for a better understanding of the quality of the Shuttle Radar Topography Mission (SRTM) 90 m digital elevation model and a global 1 km canopy height model in the dense tropical forests of Gabon by using a small-footprint airborne lidar survey and large-footprint, space-based waveform lidar data from teh National Air and Space Administration’s Ice, Cloud, and land Elevation Satellite (ICESat) for validation. As expected, the study found SRTM elevations to be heavily biased by vegetation in this biome, with elevations consistently located within the canopy volume. In addition, the global canopy height model consistently underestimates maximum canopy height at both local and regional scales.     

Supporting command and control training functions in the emergency management domain using cognitive systems engineering

The design and implementation of MERMAIDS, a computer-based training system in the domain of emergency command and control, is described. The research investigates the use of cognitive systems engineering and information management tools for modelling and representing training knowledge of emergency system operators. We propose a decision-centric human-computer interface as a new method of supporting computer-based modelling in the domain of emergency systems. Several interacting themes in information management relevant to emergency response planning are discussed.     

Reduction mammaplasty improves symptoms of macromastia

The condition macromastia has not been defined and characterized precisely by the medical community. Whether the patient with hypertrophic breasts is a candidate for or can be helped by reduction mammaplasty is unclear to both the medical and the lay community. A prospective study of 39 women undergoing reduction mammaplasty surgery was initiated to answer these questions. Patients rated the severity of their somatic pain symptoms and discomfort before reduction mammaplasty and again after complete recovery. The severity of their symptoms and complaints was numerically graded and analyzed. These data were compared with similar data obtained from 40 "small-breasted" women of similar age. Headache, neck pain, back pain, shoulder pain, and bra strap groove pain were present in 60 to 92 percent of patients, and 97 percent of patients had at least three of these pain symptoms preoperatively. All the patients had reduction of their pain symptomatology postoperative, and 25 percent of the study patients had total elimination of pain symptoms by reduction mammaplasty. The postoperative incidence and severity of pain symptoms and discomfort complaints were statistically equivalent to or less than the levels in the control group.     

Implementing tactics and tacticals in a higher-order logic programming language

We argue that a logic programming language with a higher-order intuitionistic logic as its foundation can be used both to naturally specify and implement tactic-style theorem provers. The language extends traditional logic programming languages by replacing first-order terms with simply-typed -terms, replacing first-order unification with higher-order unification, and allowing implication and universal quantification in queries and the bodies of clauses. Inference rules for a variety of inference systems can be naturally specified in this language. The higher-order features of the language contribute to a concise specification of provisos concerning variable occurrences in formulas and the discharge of assumptions present in many inference systems. Tactics and tacticals, which provide a framework for high-level control over search for proofs, can be directly and naturally implemented in the extended language. This framework serves as a starting point for implementing theorem provers and proof systems that can integrate many diversified operations on formulas and proofs for a variety of logics. We present an extensive set of examples that have been implemented in the higher-order logic programming language Prolog.     

Cytomorphometric markers for uterine cancer in intermediate cells

Precise microphotometric assessment of intermediate cells from patients with normal cervical cytology and from patients with dysplasia or carcinoma in situ shows the existence of small but consistent differences. Marker features for the presence of premalignant and malignant disease can be extracted from the cell images of "normal"-appearing intermediate cells. The marker features and their diagnostic classification potential are described.