A Very Large Area Network (VLAN) knowledge-base applied to space communication problems

This paper first describes a hierarchical model for very large area networks (VLAN). Space communication problems whose solution could profit by the model are discussed and then an enhanced version of this model incorporating the knowledge needed for the missile detection-destruction problem is presented. A satellite network or VLAN is a network which includes at least one satellite. Due to the complexity, a compromise between fully centralized and fully distributed network management has been adopted. Network nodes are assigned to a physically localized group, called a partition. Partitions consist of groups of cell nodes with one cell node acting as the organizer or master, called the Group Master (GM). Coordinating the group masters is a Partition Master (PM). Knowledge is also distributed hierarchically existing in at least two nodes. Each satellite node has a back-up earth node. Knowledge must be distributed in such a way so as to minimize information loss when a node fails. Thus the model is hierarchical both physically and informationally

A failure management prototype: DR/Rx

This failure management prototype performs failure diagnosis and recovery management of hierarchical, distributed systems. The prototype, which evolved from a series of previous prototypes following a spiral model for development, focuses on two functions: (1) the diagnostic reasoner (DR) performs integrated failure diagnosis in distributed systems; and (2) the recovery expert (Rx) develops plans to recover from the failure. Issues related to expert system prototype design and the previous history of this prototype are discussed. The architecture of the current prototype is described in terms of the knowledge representation and functionality of its components

A Framework for the Strategic Management of Science & Technology Parks

Science and technology parks (STPs) have been playing an increasingly influential role in the stimulation and growth of the knowledge economy. However, the spread of STPs faces relevant challenges, such as the development of robust performance management systems, able to demonstrate results and indicate improvement opportunities. Thereby, this paper proposes a theoretical model of performance management, which combines premises of the Service-Dominant Logic (S-D Logic), the Balanced Scorecard (BSC) and the General Hierarchical Model (GHM). Based on a multiple-case exploratory and qualitative study, relevant information about the strategic planning and management of these projects were extracted and paved the way for the construction of a performance hierarchical model composed of five perspectives, according to the BSC. Considering the outcomes, it is expected that the proposed model provide useful insights for the consolidation of a framework for the strategic management of science and technology parks

The changing knowledge and expectations of public health nurses in a HIV/AIDS training programme for managers

This research project examined the changing expectations and knowledge of Managers in the Department of Health who attended the Sexual Health Counselling Project offered by Rhodes University, East London, South Africa. These managers came from contexts in which the hierarchical medical model is firmly entrenched. The Sexual Health Counselling Project, drawing on theoretical principles from Narrative and other theories,presented a challenge to the standard management practices used by the managers. It also challenged how they dealt with clients. This research explored changes in expectations and knowledge prior to and during a two- week training course that the managers attended. A personal awareness and shift in knowledge occurred for many managers who examined their current practices. Some managers, who were firmly entrenched in the hierarchical model,found it difficult to change their ways of working

Developing people capabilities for the promotion of sustainability in facility management practices

Sustainability is becoming an integral part of the life-cycle development of built facilities. It is increasingly highlighted during the post construction phase, as facility management personnel can have major influence to the sustainability agenda through operational and strategic management functions. Sustainable practices in facility management can bring substantial benefits such as reducing energy consumption and waste, while increasing productivity, financial return and corporate standing in the community. Despite the potential, facility managers have yet to embrace sustainability ideas holistically and implement them in their operation. The lack of capabilities and skills coupled with knowledge gaps are among the barriers. In the developmental context, capabilities are vital to foster the competency of an organisation. Facility managers need to be empowered with the necessary knowledge, capabilities and skills to support sustainability. This research investigates the potential people capabilities factors that can assist in the implementation of sustainability agenda in facility management practices. Through questionnaire survey, twenty three critical people capability factors were identified and encapsulated into a conceptual framework. The critical factors were separated into four categories of strategic capabilities, anticipatory capabilities, interpersonal capabilities and system thinking capabilities. Pair-wise comparison and Interpretive Structural Modelling techniques were then used to further explore the interrelationship and influence of each critical factor. An interpretive structural model for people capability was developed to identify the priority of critical factors and provide a hierarchical structure to guide facility managers for appropriate actions. The research concludes with three case-studies of professional facility management practices to finalise the developed people capabilities framework and interpretive structural model. Through the identification and integration of different perceptions and priority needs of the stakeholders, a set of guidelines for action and potential effects of each people capability factor were brought forward for the industry to promote sustainability endeavour in facility management practices

Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change Detection

Speaker change detection (SCD) is an important task in dialog modeling. Our paper addresses the problem of text-based SCD, which differs from existing audio-based studies and is useful in various scenarios, for example, processing dialog transcripts where speaker identities are missing (e.g., OpenSubtitle), and enhancing audio SCD with textual information. We formulate text-based SCD as a matching problem of utterances before and after a certain decision point; we propose a hierarchical recurrent neural network (RNN) with static sentence-level attention. Experimental results show that neural networks consistently achieve better performance than feature-based approaches, and that our attention-based model significantly outperforms non-attention neural networks.Comment: In Proceedings of the ACM on Conference on Information and Knowledge Management (CIKM), 201

MICROWAVE: A GENERIC FRAMEWORK FOR MICRO SIMULATIONBASED EX ANTE POLICY EVALUATION

This paper presents the MicroWave approach that has been developed to improve the process of modeling in the context of micro simulation. It leads to a more efficient model development, better quality of models and their output and improvement in knowledge management. A conceptual framework has been developed and translated into a hierarchical structure of GAMS program code. Besides, several software applications and other tools have been developed for support. These products are presented and some examples illustrate how MicroWave can be applied. MicroWave is especially useful in interdisciplinary research in which different persons are involved in the modeling process and when different models have to be combined.Research Methods/ Statistical Methods,

A Hierarchical Recurrent Encoder-Decoder For Generative Context-Aware Query Suggestion

Users may strive to formulate an adequate textual query for their information need. Search engines assist the users by presenting query suggestions. To preserve the original search intent, suggestions should be context-aware and account for the previous queries issued by the user. Achieving context awareness is challenging due to data sparsity. We present a probabilistic suggestion model that is able to account for sequences of previous queries of arbitrary lengths. Our novel hierarchical recurrent encoder-decoder architecture allows the model to be sensitive to the order of queries in the context while avoiding data sparsity. Additionally, our model can suggest for rare, or long-tail, queries. The produced suggestions are synthetic and are sampled one word at a time, using computationally cheap decoding techniques. This is in contrast to current synthetic suggestion models relying upon machine learning pipelines and hand-engineered feature sets. Results show that it outperforms existing context-aware approaches in a next query prediction setting. In addition to query suggestion, our model is general enough to be used in a variety of other applications.Comment: To appear in Conference of Information Knowledge and Management (CIKM) 201

Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case study that was conducted within the logistics unit of Shell Chemicals Europe. The proposed method is based on the classical view by Sprague and Carlson of sequence and interaction of the different phases of decision making in a decision support system and supports Kraljic’s portfolio approach for supplier management. This method aims to help the managers in making decisions on the allocation of volumes to suppliers while simultaneously trying to satisfy conflicting objectives of improvement in benefit and reduction in risk. A mathematical model to struc-ture the problem is presented, knowledge elicited from the managers is used to parameterize the mathemati-cal model and a multi-objective, hierarchical optimization procedure produces ‘trade-off’ outputs. The man-agers can also conduct interactive post optimization ‘what-if’ analysi

Understanding Cross National Difference in Knowledge Seeking Behavior Model: A Survival Perspective

Electronic Knowledge Repository (EKR) is one of the most commonly deployed knowledge management technologies, yet its success is hindered by employees’ underutilization and further complicated when implemented in the multinational context. To address these challenges, we propose a research model by conceptualizing employees’ knowledge seeking via EKR as a survival-centric behavior, identifying the technology acceptance model as the individual-level explanation for EKR use, and drawing on the thermal demands-resources theory for explaining cross national behavioral differences. Using hierarchical linear modeling, we tested the model with data from 1352 randomly sampled knowledge workers across 30 nations. The results reveal interesting cross national behavioral patterns. Specifically, thermal climates and national wealth at the macro-level interactively moderate individual-level relationships between perceived ease of use and perceived usefulness and between perceived usefulness and behavioral intention