Does Affirmative Action Work? Evidence from the Operation of Fair Employment Legislation in Northern Ireland

An affirmative action programme, established by the Fair Employment (Northern Ireland) Act 1989, has been an important attempt to ensure ‘fair participation’ in employment for both Catholics and Protestants in Northern Ireland since 1990. The programme includes detailed monitoring of the community background of employees and requires employers to undertake remedial action where fair participation is not evident. Agreements were concluded between the regulatory agency and many employers specifying what affirmative action measures were required. Based on the annual monitoring returns submitted between 1990 and 2005, this article evaluates the effectiveness of the affirmative action programme in promoting fair employment participation using fixed effects models. The analysis shows that there has been a general shift towards workforce integration in Northern Ireland but the increase of under-represented groups in agreement concerns is greater than in concerns with no agreement. The success of agreements, however, is limited to certain industrial sectors and medium-sized enterprises.

The institutionalisation of the European Internal Cross-Border Co-operation Policy: A first appraisal

In the space of just 20 years, internal cross-border co-operation (CBC) has transformed from a marginal issue for European integration into an important strand of the third objective of European Union's (EU's) regional policy. How might this process of transformation be explained? This study intends to reconstruct the chronology of its development through interviews and use of archival material. The emergence of the current CBC policy was not, we argue, an inevitable solution to the problem of border management but, rather, the result of a struggle between the actors of that policy sub-system. The dramatic rise of CBC is the result of a series of factors that originated with the signing of the Single European Act in 1986. The construction of CBC as a set of problems and solutions by a network of policy actors at the margins of the EU through a series of technical reports, together with the policy window opened by the appointment of the Delors Commission, allowed the launching of an innovative CBC policy which has consolidated over time.

A Bayesian framework for age modeling of radiocarbon-dated peat deposits: Case studies from the Netherlands

Recently, Bayesian statistical software has been developed for age-depth modeling (wiggle-match dating) of sequences of densely spaced radiocarbon dates from peat cores. The method is described in non-statistical terms, and is compared with an alternative method of chronological ordering of 14C dates. Case studies include the dating of the start of agriculture in the northeastern part of the Netherlands, and of a possible Hekla-3 tephra layer in the same country. We discuss future enhancements in Bayesian age modeling.

PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Analysis of Bayesian classification-based approaches for Android malware detection

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.

Application of PMUs to Coordinate Hydroelectric and Wind Power Plant Operation

It is acknowledged that wind power is a stochastic energy source compared to hydroelectric generation which is easily scheduled. In this paper a scheme for coordinating wind power plant and hydroelectric power plant is presented by using PMUs to measure and control the state of wind and hydro power plants. Hydroelectric generation is proposed as a method of energy reserve and compensation in the context of wind power fluctuation in order to avoid full or partial curtailment of wind generation to benefit wind providers. The feasibility of this proposed scheme is investigated by power flow calculation and stability analysis using the IEEE 30-bus power system model.

Data Reduction of Power System Disturbances using Wavelet Transforms for Network Operation and Control

Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the reduction properties of the wavelet transform using real power system data and discusses the application of the reduction method for information transfer in network communications.

Simulation of three-dimension cutting force and tool deflection in the end milling operation based on finite element method

This paper presents a 3D simulation system which is employed in order to predict cutting forces and tool deflection during end-milling operation. In order to verify the accuracy of 3D simulation, results (cutting forces and tool deflection) were compared with those based on the theoretical relationships, in terms of agreement with experiments. The results obtained indicate that the simulation is capable of predicting the cutting forces and tool deflection.

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Idealized Operation of Third-Harmonic-Peaking Class-Ef Power Amplifier with Extended Maximum Operating Frequency

A new variant of Class-EF power amplifier (PA), the so-called third-harmonic-peaking Class-EF, is presented. It inherits a soft-switching operation from the Class-E PA and a low peak switch voltage from the Class-F PA. More importantly, the new topology allows operations at higher frequencies and permits deployment of large transistors which is normally prohibited since they are always accompanied with high output capacitances. Using a simple transmission-line load network, the PA is synthesized to satisfy Class-EF impedances at fundamental frequency, third harmonic, and all even harmonics as well as to simultaneously provide an impedance matching to 50-Ω load.

Mineralogical Characteristics and Transformations during Long-Term Operation of a Zerovalent Iron Reactive Barrier

Design and operation of Fe⁰ permeable reactive barriers (PRBs) can be improved by understanding the long-term mineralogical transformations that occur within PRBs. Changes in mineral precipitates, cementation, and corrosion of Fe⁰ filings within an in situ pilot-scale PRB were examined after the first 30 months of operation and compared with results of a previous study of the PRB conducted 15 months earlier using X-ray diffraction and scanning electron microscopy employing energy dispersive X-ray and backscatter electron analyses. Iron (oxy)hydroxides, aragonite, and maghemite and/or magnetite occurred throughout the cores collected 30 mo after installation. Goethite, lepidocrocite, mackinawite, aragonite, calcite, and siderite were associated with oxidized and cemented areas, while green rusts were detected in more reduced zones. Basic differences from our last detailed investigation include (i) mackinawite crystallized from amorphous FeS, (ii) aragonite transformed into calcite, (iii) akaganeite transformed to goethite and lepidocrocite, (iv) iron (oxy)hydroxides and calcium and iron carbonate minerals increased, (v) cementation was greater in the more recent study, and (vi) oxidation, corrosion, and disintegration of Fe⁰ filings were greater, especially in cemented areas, in the more recent study. If the degree of corrosion and cementation that was observed from 15 to 30 mo after installation continues, certain portions of the PRB (i.e., up-gradient entrance of the ground water to the Fe⁰ section of the PRB) may last less than five more years, thus reducing the effectiveness of the PRB to mitigate contaminants.