Voting with their seats: computer laboratory design and the casual user

Abstract

Following a brief review of the literature, details are given of an in-depth evaluation of a computer training centre called Microjob. This facility set out to integrate computer training, vocational guidance, functional assessment, placement in employment and post-placement support into a single service delivery package. In this paper the facility's outcome record is examined in relation to targets set for it, consideration is given to the special needs of home-based trainees, and specific difficulties faced by the project (including an inefficient management structure, inadequate staff training and a poor level of awareness of clients' special needs) are discussed.     

A group AHP-TOPSIS framework for human spaceflight mission planning at NASA

Human spaceflight mission planning is a complex task with many interacting systems and mission phases. Analog missions are Earth-based science missions whose purpose is to help understand the complexities inherent in future human spaceflight missions. The goal of performing an analog mission is to prepare crewmembers and support teams for future space missions in a low risk-low cost environment by repeatedly testing vehicles, habitats, and surface terrain simulators. This study presents a group multi-attribute decision making (MADM) framework developed at the Johnson Space Center (JSC) for the Integrated human exploration mission simulation facility (INTEGRITY) project to assess the priority of human spaceflight mission simulators. The proposed framework integrates subjective judgments derived from the analytic hierarchy process (AHP) with the entropy information and the technique for order preference by similarity to the ideal solution (TOPSIS) into a series of preference models for the human exploration of Mars. Three different variations of TOPSIS including conventional, adjusted and modified TOPSIS methods are considered in the proposed framework.     

Heuristics for a continuous multi-facility location problem with demand regions

We consider a continuous multi-facility location allocation problem where the demanding entities are regions in the plane instead of points. The problem can be stated as follows: given m (closed, convex) polygonal demand regions in the plane, find the locations of q facilities and allocate each region to exactly one facility so as to minimize a weighted sum of squares of the maximum Euclidean distances between the demand regions and the facilities they are assigned to.We propose mathematical programming formulations of the single and multiple facility versions of the problem considered. The single facility location problem is formulated as a second order cone programming (SOCP) problem, and hence is solvable in polynomial time. The multiple facility location problem is NP-hard in general and can be formulated as a mixed integer SOCP problem. This formulation is weak and does not even solve medium-size instances. To solve larger instances of the problem we propose three heuristics. When all the demand regions are rectangular regions with their sides parallel to the standard coordinate axes, a faster special heuristic is developed. We compare our heuristics in terms of both solution quality and computational time.     

Constrained location of competitive facilities in the plane

This paper examines a competitive facility location problem occurring in the plane. A new gravity-based utility model is developed, in which the capacity of a facility serves as its measure of attractiveness. A new problem formulation is given, having elastic gravity-based demand, along with capacity, forbidden region, and budget constraints. Two solution algorithms are presented, one based on the big square small square method, and the second based on a penalty function formulation using fixed-point iteration. Computational testing is presented, comparing these two algorithms along with a general-purpose nonlinear solver.Scope and purposeIn a competitive business environment where products are not distinguishable, facility location plays an important role in an organization's success. This paper examines a firm's problem of selecting the locations in the plane for a set of new facilities such that market capture is maximized across all of the firm's facilities (both new and pre-existing). Customers are assumed to divide their demand among all competing facilities according to a utility function that considers facility attractiveness (measured by facility capacity for satisfying demand) and customer-facility distance. The level of customer demand is assumed to be a function of the facility configuration. Three types of constraints are introduced, involving facility capacity, forbidden regions for new facility location, and a budget function. Two solution algorithms are devised, one based on branch-and-bound methods and the other based on penalty functions. Computational testing is presented, comparing these two algorithms along with a general-purpose nonlinear solver.     

Model‐Driven and Risk‐Based Performance Analysis of Industrial Emergency Plans

This paper presents a methodology for the assessment of the performance of industrial hazardous materials emergency plans. This approach is based on a structuro‐functional model of the emergency plan, which highlights the plan's functions, resources, support services and interactions. A resource taxonomy is used to manage the complexity of the emergency response system. The model can be used both as a planning guide and for the analysis of the performance of the emergency response system, based on the risk assessment of the system. The failure probability is estimated through the plan's functions and resources fault trees. The failure severity of each function is determined by using the facility's hazard study. The failure criticality of each function is hence obtained.     

A bilevel partial interdiction problem with capacitated facilities and demand outsourcing

In this paper, partial facility interdiction decisions are integrated for the first time into a median type network interdiction problem with capacitated facilities and outsourcing option. The problem is modeled as a static Stackelberg game between an intelligent attacker and a defender. The attacker's (leader's) objective is to cause the maximum (worst-case) disruption in an existing service network subject to an interdiction budget. On the other hand, the defender (follower) is responsible for satisfying the demand of all customers while minimizing the total demand-weighted transportation and outsourcing cost in the wake of the worst-case attack. She should consider the capacity reduction at the interdicted facilities where the number of interdictions cannot be known a priori, but depends on the attacker's budget allocation. We propose two different methods to solve this bilevel programming problem. The first one is a progressive grid search which is not viable on large sized instances. The second one is a multi-start simplex search heuristic developed to overcome the exponential time complexity of the first method. We also use an exhaustive search method to solve all combinations of full interdiction to assess the advantage of partial interdiction for the attacker. The test results suggest that under the partial interdiction approach the attacker can achieve a better utilization of his limited resources.     

Lagrangean relaxation and decomposition in an uncapacitated 2-hierarchal location-allocation problem

We consider an uncapacitated 2-hierarchal location-allocation problem where p₁ level 1 facilities and p₂ level 2 facilities are to be located among n(?p₁ + p₂) potential locations so as to minimize the total weighted travel distance to the facilities when θ, (0 ? θ ? 1) fraction of the demand from a level 1 facility is referred to a level 2 facility. At most one facility may be located at any location. In this model, a level 2 facility provides services in addition to services provided by a level 1 facility.The problem is formulated as a mathematical programming problem, relaxed and solved by a subgradient optimization procedure. The proposed procedure is illustrated with an example.     

Stocks and flows underlying organizations’ knowledge management capability: Synergistic versus contingent complementarities over time

What are the components of a knowledge management (KM) capability and how do they impact firm performance? Based on prior research, we modeled a firm's KM capability in terms of its accumulations of stock – in the areas of human resources, technology infrastructures, and strategic templates – and regulation of flow, via institutionalization and internal and external learning processes. We then considered the extent to which these components complement one another in their impact on two types of firm performance – efficiency, based return on assets, and value creation, assessed as Tobin's q (the ratio of the capital market value of the firm to the replacement value of its assets). We posited differential types of stock-flow complementarities across these two performance outcomes over time – stable, positive effects on firm efficiency, synergistic complementarity, and initially positive, but subsequently negative effects on value creation, contingent complementarity. Data gathered from 218 Korean firms supported this premise. Implications for practice in the evolving fields of organizational capability and complementarities were explored.     

Capacity constrained maximizing bichromatic reverse nearest neighbor search

When planning a new development (facility/service site), location decisions are always the major issue. In this paper we introduce a novel query capacity constraint MaxBRNN, which can solve the facility location selection problem efficiently.The MaxBRNN (maximizing BRNN) query is based on bichromatic reverse nearest neighbor (BRNN) query which uses the number of reverse nearest customers to model the influence of a facility location. The MaxBRNN query has been appreciated extensively in spatial database studies because of its great potential in real life applications, such as, markets decision, sensor network clustering and the design of GSM (global system for mobile communication). The existing researches mostly suppose that the service facility's capacity is unlimited. However, in real cases, facilities are inevitably constrained by designed capacities. For example, if the government wants to select a new place to set up an emergency center to share the existing centers’ patients, they need to know the current emergency centers’ capacity so that they can estimate the new center's scale. Thus, the capacity constrained MaxBRNN query is significantly important in planning a new development. As far as we know, the capacity constrained MaxBRNN query has not been studied yet, so, we formulate this problem, propose a basic solution and develop some efficient algorithms for the query.Our major contributions are as follows: (1) we propose a novel query capacity constraint MaxBRNN which can solve the facility location selection problem effectively and efficiently; (2) we develop a basic algorithm CCMB and two improved algorithms which can find out the optimal region in terms of building a new facility, maximize its impact and deal with the complicated reassignment when adding new facilities into the dataset; (3) we prove the algorithms’ effectiveness and efficiency by extensive experiments using both real and synthetic data sets.     

Fast metaheuristics for the discrete (r|p)-centroid problem

Two players, the leader and his competitor, open facilities, striving to capture the largest market share. The leader opens p facilities, then the follower opens r facilities. Each client chooses the nearest facility as his supplier. We need to choose p facilities of the leader in such a way as to maximize his market share. This problem can be represented as a bilevel programming problem. Based on this representation, in this work we propose two numerical approaches: local search with variable neighborhoods and stochastic tabu search. We pay the most attention to improving the methods’ efficiency at no loss to the quality of the resulting solutions. Results of numerical experiments support the possibility to quickly find an exact solution for the problem and solutions with small error.     

Telepresence in concurrent lifecycle design and construction

Construction projects usually involve transient ‘virtual organisations’ made up of members of a project team (involving several disparate disciplines) working together on the design and construction of a facility. Team members are often non-co-located, particularly at the early stages of the design process, and tend to work independently while taking decisions that affect others. The adoption of concurrent engineering principles by the construction industry is increasingly being seen as vital for reducing the problems posed by the industry's fragmentation, and enhancing its competitiveness. An important aspect of concurrent engineering in construction is the need for an effective communications infrastructure able to transmit project information between members of the project team and across all stages in the constructed facility's lifecycle. This paper describes the development of such a communications infrastructure that is based on the concept of Telepresence. The intention is to create a persistent space to support interaction between project personnel throughout the design and construction phases of projects. The paper first highlights the key communications issues that need to be addressed, introduces ‘Telepresence’ and describes an initial prototype system. The approach being adopted in the development of an advanced Telepresence environment for construction project teams is also presented. The Telepresence environment is intended to help people who cannot be together to work together.     

A knowledge broker for collaboration and sharing for SIDS: the case of comprehensive disaster management in the Caribbean*

ABSTRACT

Knowledge sharing can be hindered by barriers that prevent the free flow of information, especially across organizational and other boundaries. Therefore information produced at one location might not be available to entities elsewhere even if there are benefits to sharing this information. This can often lead to 'reinventing the wheel' and wasted investments in duplicating resources and ultimately will lead to the development of knowledge silos. Information technologies can be used to address this problem as they provide opportunities to lower the barriers to knowledge sharing and increase collaboration. This need for knowledge sharing and collaborative technologies can be important for Small Island Developing States (SIDS) within particular regions that are exposed to similar environmental and economic issues that can hinder their development. Although each SIDS may have Knowledge Resources that it uses to address its own issues, there would be benefits to collaborating and sharing these resources to collectively tackle these regional issues. Even when there is a willingness to share and collaborate and entities have been established to foster this collaboration, there is a void in the availability of tools and technologies needed to support collaboration and sharing of resources. This paper describes the research that has been done to help fill this void by designing and developing a technological solution, a Knowledge Broker, for the identification and sharing of Knowledge Resources that may be spread across various locations (e.g. countries). The Design Science Research methodology was used to develop the Knowledge Broker architecture, which provides a single point of access to the knowledge resources within a particular domain. A critical component of this Knowledge Broker is a common, online interactive vocabulary of the domain of interest which provides the terms which are used to describe and search for the knowledge resources available. The Knowledge Broker was evaluated using informed arguments and an illustrative scenario in the Comprehensive Disaster Management domain in the Caribbean region. The initial evaluations that have been reported in this paper indicates that the Knowledge Broker has the potential to increase the efficiency of solving regional issues through the sharing of knowledge resources.     

Innovation characteristics and intention to adopt sustainable facilities management practices

Sustainable facilities management (SFM) is important because typical buildings consume more resources and energy than necessary, negatively impact the environment and generate lots of waste (US Department of Energy, 2003, Green Buildings). This study examined innovation characteristics that relate to facility managers' intention to adopt SFM practices. Based on the diffusion of innovations theory (Rogers 1962, 1995, Diffusion of Innovations. 4th ed. New York: The Free Press), an SFM innovation and adoption model was proposed. A survey was conducted with a convenience sample of 240 public facilities managers in 25 facilities management divisions in Seoul, Korea, and its metropolitan areas. Structural equation modelling was employed to analyse the data. The results showed that economic advantage and human comfort aspects are predictors for the intention of SFM adoption. Observability is positively relevant to the intention of SFM adoption. Complexity, however, is not a significant predictor for the intention of SFM adoption. Practical implications for sustainable products and systems and the built environment are suggested.

Practitioner summary: To incorporate an innovation like sustainable practices, it is required to meet the needs of potential adopters. Innovation characteristics that influence facility managers' intention to adopt sustainable facilities management were examined. A survey was conducted. Economic advantage, human comfort and observability are predictors for the intention of adoption of sustainable practice.     

A multi-objective approach for determining optimal air compressor location in a manufacturing facility

Determining the optimal location of an air compressor in a manufacturing facility is a challenging problem that can offer significant energy savings. A novel simulation-optimization model is proposed to increase energy efficiency in a facility by determining optimal air compressor location. The optimization strategy is based on an objective function that minimizes the total energy consumption of the air compressor – hence, the energy cost for the facility – while considering the user's preference for the air compressor location. The proposed mathematical model first integrates the facility's characteristics based on user inputs, divides the facility into zones, and generates a rectilinear zone-to-zone distance matrix within the facility. The user location preference is incorporated into the proposed model via a five level user-preference index, assigned using preferential locations as suggested by twenty-two experienced facility managers. A sensitivity analysis is conducted to determine the relationship between the selected user preference level and the resulting energy consumption at each location in the facility. A simulation-driven analysis is performed using a real-life facility layout and typical compressed air equipment with corresponding nameplate data. In order to investigate and demonstrate the effectiveness of the proposed approach, the derived optimal zones are compared with five zones, including the most energy efficient zone, least energy efficient zone, and three other zones selected at random. The results of our study reveal that the proposed method achieves significant energy reductions while maintaining the user's desired air compressor location.     

个性化学习路径推荐综述

近年来，伴随着现代信息技术的迅猛发展，以人工智能为代表的新兴技术在教育领域得到了广泛应用，引发了学习理念和方式的深刻变革.在这种大背景下，在线学习超越了时空的限制，为学习者“随时随地”学习提供了更多的可能性，从而得到了蓬勃发展.然而，在线学习中师生时间、空间分离的特征，导致教师无法及时掌握学生的学习状态，一定程度上制约了在线学习中教学质量的提升.面对多元化的学习需求及海量学习资源，如何迅速完成学习目标、降低学习成本、合理分配学习资源等问题成为限制个人和时代发展的重大问题.然而，传统的“一刀切”的教育模式已经不能满足人们获取知识的需求了，需要一个更高效、更科学的个性化教育模式，以帮助学习者以最小的学习成本最大限度地完成学习目标.基于以上背景，如何自动高效识别学习者特征，高效地组织和分配学习资源，为每一位学习者规划个性化路径，成为面向个体的精准化教育资源匹配机制研究中亟待解决的问题.系统地综述并分析了当前个性化学习路径推荐的研究现状，并从多学科领域的角度分析了对于同一问题的不同研究思路，同时也归纳总结了当前研究中最为主流的核心推荐算法.最后，强调当前研究存在的主要不足之处.     

A bilevel fixed charge location model for facilities under imminent attack

We investigate a bilevel fixed charge facility location problem for a system planner (the defender) who has to provide public service to customers. The defender cannot dictate customer-facility assignments since the customers pick their facility of choice according to its proximity. Thus, each facility must have sufficient capacity installed to accommodate all customers for whom it is the closest one. Facilities can be opened either in the protected or unprotected mode. Protection immunizes against an attacker who is capable of destroying at most r unprotected facilities in the worst-case scenario. Partial protection or interdiction is not possible. The defender selects facility sites from m candidate locations which have different costs. The attacker is assumed to know the unprotected facilities with certainty. He makes his interdiction plan so as to maximize the total post-attack cost incurred by the defender. If a facility has been interdicted, its customers are reallocated to the closest available facilities making capacity expansion necessary. The problem is formulated as a static Stackelberg game between the defender (leader) and the attacker (follower). Two solution methods are proposed. The first is a tabu search heuristic where a hash function calculates and records the hash values of all visited solutions for the purpose of avoiding cycling. The second is a sequential method in which the location and protection decisions are separated. Both methods are tested on 60 randomly generated instances in which m ranges from 10 to 30, and r varies between 1 and 3. The solutions are further validated by means of an exhaustive search algorithm. Test results show that the defender's facility opening plan is sensitive to the protection and distance costs.     

Cultivating Social Resources on Social Network Sites: Facebook Relationship Maintenance Behaviors and Their Role in Social Capital Processes

This study explores the relationship between perceived bridging social capital and specific Facebook‐enabled communication behaviors using survey data from a sample of U.S. adults (N=614). We explore the role of a specific set of Facebook behaviors that support relationship maintenance and assess the extent to which demographic variables, time on site, total and “actual” Facebook Friends, and this new measure (Facebook Relationship Maintenance Behaviors) predict bridging social capital. Drawing upon scholarship on social capital and relationship maintenance, we discuss the role of social grooming and attention‐signaling activities in shaping perceived access to resources in one's network as measured by bridging social capital.     

Fast approximate clearance evaluation for rovers with articulated suspension systems

We present a light‐weight body‐terrain clearance evaluation algorithm for the automated path planning of NASA's Mars 2020 rover. Extraterrestrial path planning is challenging due to the combination of terrain roughness and severe limitation in computational resources. Path planning on cluttered and/or uneven terrains requires repeated safety checks on all the candidate paths at a small interval. Predicting the future rover state requires simulating the vehicle settling on the terrain, which involves an inverse‐kinematics problem with iterative nonlinear optimization under geometric constraints. However, such expensive computation is intractable for slow spacecraft computers, such as RAD750, which is used by the Curiosity Mars rover and upcoming Mars 2020 rover. We propose the approximate clearance evaluation (ACE) algorithm, which obtains conservative bounds on vehicle clearance, attitude, and suspension angles without iterative computation. It obtains those bounds by estimating the lowest and highest heights that each wheel may reach given the underlying terrain, and calculating the worst‐case vehicle configuration associated with those extreme wheel heights. The bounds are guaranteed to be conservative, hence ensuring vehicle safety during autonomous navigation. ACE is planned to be used as part of the new onboard path planner of the Mars 2020 rover. This paper describes the algorithm in detail and validates our claim of conservatism and fast computation through experiments.     

The reverse greedy algorithm for the metric k-median problem

The Reverse Greedy algorithm (RGreedy) for the k-median problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the total distance to the remaining facilities. It stops when k facilities remain. We prove that, if the distance function is metric, then the approximation ratio of RGreedy is between Ω(logn/loglogn) and O(logn).     

Intellectual capital: from intangible assets to fitness landscapes

Intellectual Capital (IC) has been proposed by Edvinsson and Malone (Intellectual capital, Harper, 1997) as a technique for quantifying a company's intangible assets. A careful analysis can result in hundreds of variables, and extracting knowledge from these measurements can be difficult. We introduce a knowledge management technique called IC mapping that attempts to synthesize this data into a fitness landscape. Using the map, managers can query the surrounding landscape, view the company's trajectory across the landscape, and calculate what parameters need to be changed to reach new locations. IC mapping provides a novel knowledge management tool for understanding, managing, and representing a company's intangible knowledge assets.