Compliance management ontology – a shared conceptualization for research and practice in compliance management

The diversity of stakeholders in compliance management initiatives contributes to the challenges organisations face when managing compliance, and consequently adds to the cost of compliance. In particular, there is evidence that the lack of a common or shared understanding of compliance management concepts is a barrier to effective compliance management practice. Taking an information-centric view to addressing this challenge, this paper reports on the development of an ontology intended to provide a shared conceptualisation of the compliance management domain for various stakeholders. The ontology is based on input from domain experts and practitioners, validated and refined through eight case studies, and subsequently evaluated for its usability in practice.     

From product-centric to customer-centric services in a financial institution – exploring the organizational challenges of the transition process

This research aims to contribute to an increased understanding of the strategic, cultural and other organizational challenges in a transition process from product-centric to customer-centric services. The paper describes an exploratory case study, conducted in a complex financial services organization in the context of their customer-facing services. The transition process was examined through the theoretical lens of Work System Theory (WST), following the argument made by previous researchers that service systems could be seen as work systems. This holistic theory enabled us to capture the three key phases of the transition process as work systems snapshots and through their evolving relationships show the manner in which the transitions occurred from one phase to another. This innovative approach provided the researchers with an in-depth insight into key issues related to organizational environment, strategy, customers, products and services, processes and activities, participants, and information and technologies – all relevant for each phase of the transition process. This research contributes to both information systems (IS) and service science research, bringing the key service research priority of “service infusion” to the attention of IS researchers.     

Never blame the umpire – a review of Situation Awareness models and methods for examining the performance of officials in sport

As sport becomes more complex, there is potential for ergonomics concepts to help enhance the performance of sports officials. The concept of Situation Awareness (SA) appears pertinent given the requirement for officials to understand what is going on in order to make decisions. Although numerous models exist, none have been applied to examine officials, and only several recent examples have been applied to sport. This paper examines SA models and methods to identify if any have applicability to officials in sport (OiS). Evaluation of the models and methods identified potential applications of individual, team and systems models of SA. The paper further demonstrates that the Distributed Situation Awareness model is suitable for studying officials in fastball sports. It is concluded that the study of SA represents a key area of multidisciplinary research for both ergonomics and sports science in the context of OiS.

Practitioner Summary: Despite obvious synergies, applications of cognitive ergonomics concepts in sport are sparse. This is especially so for Officials in Sport (OiS). This article presents an evaluation of Situation Awareness models and methods, providing practitioners with guidance on which are the most suitable for OiS system design and evaluation.     

Creating a specific domain ontology for supporting R&D in the science-based sector – The case of biosensors

In science-based and technology-intensive projects, knowledge management challenges require a tentative and cautious review of the technological domains, as well as, venues to monitor and assess the way those domains evolve, emerge, mature, and decline. Ontologies play a crucial role in conceptualizing/formalizing domain knowledge, yet any ontological platform that is constructed for supporting R&D throughout the knowledge creation process, must explicitly address the interplay between exploitation and exploration of knowledge at deep and surface levels. Focusing on the product per se and its downstream and upstream knowledge evolution complex system, ontology engineering adopts herein a process-driven view for capturing a continuously changing environment. The authors present a methodological framework for creating specific domain ontologies by means of a cybernetic infrastructure built on a modification of the Nonaka’s SECI process. This rationale is exemplified on biosensors, a class of devices strongly attached to multidisciplinary basic and applied science, bearing along many levels of input and output knowledge. The proposed ontological representation, expresses and defines a target product as a metamodel. Combined with knowledge about the scientific background of the product, an aspect model at physical concept level is generated from the metamodel and is further converted into a design model. This scheme enables knowledge to be used not only for representation but also for reasoning at functional level. The research logic followed herein does not bring yet another ontology building methodology through a project-management context, but rather contributes to an ontological approach for exploring the diverse knowledge inputs that a product requires through a specific domain-derived and domain-oriented context, which relies on a collaborative model building methodology and a systemic modeling formalism by using 2nd order cybernetics in order to include human intervention.     

Airborne thermal data for evaluating the spatial distribution of actual evapotranspiration over a watershed in oceanic climatic conditions—application of semi-empirical models

Considerable work has been done on estimating daily fluxes at the regional scale from thermal data acquired in the early afternoon using semi-empirical models. But these studies have dealt only with clear days and homogeneous surfaces. We evaluate the use of some of these models under variable climatic conditions. A campaign of micrometeorological measurements performed from May to October 1993 on a small agricultural catchment in Brittany (NW France) allowed us to monitor the water budget and fluxes of three characteristical surfaces (meadow, wheat and stubble field). Thermal images covering the whole catchment were acquired on 7 August 1993 using an infrared camera aboard a small aircraft. They were corrected for atmospheric effects with the LOWTRAN 7 model. After geometrical corrections to superimpose these images on a digitilized land use map, a mapping of surface fluxes at the catchment scale is proposed and discussed.     

An integrated soft and hard classification approach for evaluating urban expansion from multisource remote sensing data: a case study of the Beijing–Tianjin–Tangshan metropolitan region,China

Integrating soft and hard classification to monitor urban expansion can effectively provide comprehensive urban growth information to urban planners. In this study, both the impervious surface coverage (as a soft classification result) and land cover (as a hard classification result) in the Beijing–Tianjin–Tangshan metropolitan region (BTTMR), China, were extracted from multisource remote sensing data from 1990 to 2015. Then, we evaluated urban expansion based on centre migration, standard deviation ellipse, and spatial autocorrelation metrics. Furthermore, the differences between the soft and hard classification results were analysed at the landscape scale. The results showed that (1) the impervious surface area increased considerably over the past 25 years. Notably, the areas of urban built-up land and industrial production land increased rapidly, while those of ecological land and agricultural production land seriously decreased. (2) The distribution of impervious surfaces was closely related to the regional economic development plan of ‘One Axis, Two Wing, and Multi-Node’ in the BTTMR. (3) The contributions of different land use types to impervious surface growth ranked from high to low as follows: urban built-up land, rural residential land, industrial production land, agricultural production land, and ecological land. (4) The landscape metrics varied considerably based on the hard and soft classification results and were sensitive to different factors.     

A mixed 0–1 nonlinear optimization model and algorithmic approach for the collision avoidance in ATM: Velocity changes through a time horizon

In this paper a mixed 0–1 nonlinear model for the Collision Avoidance problem in Air Traffic Management is presented. The aim of the problem consists of deciding the best strategy for an arbitrary aircraft configuration such that all conflicts in the airspace are avoided where a conflict is the loss of the minimum safety distance that two aircraft have to keep in their flight plans. The optimization model is based on geometric constructions. It requires knowing the initial flight plan (coordinates, angles and velocities in each period). The objective is the minimization of the acceleration variations when the aircraft are forced to return to the original flight plan once there is no aircraft in conflict. A linear approximation by using iteratively Taylor polynomials is presented to solve the problem in mixed 0–1 linear terms. An extensive computational experience for a testbed of large-scale instances is reported.     

A monitoring indicator system for remote sensing of grassland vegetation growth and suitability evaluation – a case study of the Xilingol Grassland in Inner Mongolia,China

Grassland vegetation growth directly reflects plant growth conditions, and growth processes are an important component of ecological status assessments of grasslands and can provide timely guidance for agricultural production. In this study, the Xilingol Grassland in Inner Mongolia was used as the study area, and a monitoring indicator system for the remote sensing of grassland vegetation growth was established based on 16 days of Moderate Resolution Imaging Spectroradiometer (MODIS) data and ground sampling data, which were used to assess the suitability of the indicator system. A monitoring indicator system for the remote sensing of grassland vegetation that included the modified growth index (MGI)-normalized difference vegetation index (NDVI), MGI-enhanced vegetation index (EVI), growth index (GI)-NDVI, and GI-EVI was established by using the year 2000 as the base year, two vegetation indices and difference and normalized difference methods. A model for estimating the ground growth (g) was then constructed by using expert opinion scoring and the Analytic Hierarchy Process (AHP) to determine the weights of vegetation coverage (c), height (h), and yield (y) in the ground plots, with the model calculated as follows: g = 0.2543c + 0.1848 h + 0.5609y. Additionally, the ground growth value was calculated according to the ground growth model, and the values obtained from the remote-sensing indicators in the corresponding region were subjected to a correlation analysis based on this partition. The remote-sensing growth indices suitable for temperate steppe, meadow steppe, and desert steppe regions were GI-EVI, MGI-NDVI, and GI-NDVI, respectively. Finally, vegetation growth in the Xilingol Grassland was evaluated using the optimal remote-sensing GI for each area, and the results indicated that the areas with the greatest growth improvement occurred in the temperate steppe region followed by the meadow steppe region, whereas vegetation growth improvement was insignificant in the desert steppe region. The results of this study have important significance for the economic development and ecological environmental improvement of pastoral and semi-pastoral regions and can be used to determine the optimal use and scientific management of grasslands.     

Classification of radar echoes with a textural–fuzzy approach: an application for the removal of ground clutter observed in Sétif (Algeria) and Bordeaux (France) sites

This work deals with the classification of radar echoes and the removal of clutter caused by the Earth’s surface. Two incoherent radar sites are considered, which are the regions of Sétif (Algeria) and Bordeaux (France) where different climates and landforms prevail. To perform this task, we used a combination of textural and fuzzy approaches. For the textural technique, we applied grey-level co-occurrence matrices that are widely used in the analysis of texture images. We have shown that among nine parameters, only energy and local homogeneity are considered to be effective in discriminating between precipitation echoes and clutter. Then, these parameters are used as inputs for the fuzzy system, while the two radar echo types are its output classes. Image processing done by using this approach has reduced ground echoes by more than 93.5% for Sétif and 92.3% for Bordeaux sites, while more than 97.6% of precipitation echoes are stored at both sites. In addition, over 96% of the anomalous propagations observed only in Bordeaux site are removed. The proposed approach gives a filtering average rate that is 94.5% higher than that obtained for the textural technique alone, which is 91.5%.     

Exact asymptotics of small deviations for a stationary Ornstein-Uhlenbeck process and some Gaussian diffusion processes in the L p -norm, 2 ≤ p ≤ ∞

We prove results on exact asymptotics of the probabilities

Study of the Radio Frequency (RF) performance of a Wafer-Level Package (WLP) with Through Silicon Vias (TSVs) for the integration of RF-MEMS and micromachined waveguides in the context of 5G and Internet of Things (IoT) applications: Part 1—validation of the 3D modelling approach

Microsystem Technologies - Packaging of Radio Frequency MicroElectroMechanical-Systems (RF-MEMS) and other passive components is a delicate issue, especially in the riverbed of upcoming application...