A Hybrid Swarm Based Approach in Addressing University Timetabling Problems

This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

Surgical strategies for coexisting glaucoma and cataract: an evidence-based update.

OBJECTIVE:

To assess short- and long-term control of intraocular pressure (IOP) with different surgical treatment strategies for coexisting cataract and glaucoma.

DESIGN:

Systematic literature review and analysis.

METHOD:

We performed a search of the published literature to identify all eligible articles pertaining to the surgical management of coexisting cataract and glaucoma in adults. One investigator abstracted the content of each article onto a custom-designed form. A second investigator corroborated the findings. The evidence supporting different approaches was graded by consensus as good, fair, weak, or insufficient.

MAIN OUTCOME MEASURES:

Short-term (24 hours or fewer) and long-term (more than 24 hours) IOP control.

RESULTS:

The evidence was good that long-term IOP is lowered more by combined glaucoma and cataract operations than by cataract operations alone. On average, the IOP was 3 to 4 mmHg lower in the combined groups with fewer medications required. The evidence was weak that extracapsular cataract extraction (ECCE) alone results in short-term increase in IOP and was insufficient to determine the short-term impact of phacoemulsification cataract extraction (PECE) on IOP in glaucoma patients. The evidence was weak that short-term IOP control was better with ECCE or PECE combined with an incisional glaucoma procedure compared with ECCE or PECE alone. The evidence was also weak (but consistent) that long-term IOP is lowered by 2 to 4 mmHg after ECCE or PECE. Finally, there was weak evidence that combined PECE and trabeculectomy produces slightly worse long-term IOP control than trabeculectomy alone, and there was fair evidence that the same is true for ECCE combined with trabeculectomy.

CONCLUSIONS:

There is strong evidence for better long-term control of IOP with combined glaucoma and cataract operations compared with cataract surgery alone. For other issues regarding surgical treatment strategies for cataract and glaucoma, the available evidence is limited or conflicting.

Effect of technique on intraocular pressure after combined cataract and glaucoma surgery: An evidence-based review.

TOPIC:

To analyze the literature pertaining to the techniques used in combined cataract and glaucoma surgery, including the technique of cataract extraction, the timing of the surgery (staged procedure versus combined procedure), the anatomic location of the operation, and the use of antifibrosis agents.

CLINICAL RELEVANCE:

Cataract and glaucoma are both common conditions and are often present in the same patient. There is no agreement concerning the optimal surgical management of these disorders when they coexist.

METHODS/LITERATURE REVIEWED:

Electronic searches of English language articles published since 1964 were conducted in Pub MED and CENTRAL, the Cochrane Collaboration's database. These were augmented by a hand search of six ophthalmology journals and the reference lists of a sample of studies included in the literature review. Evidence grades (A, strong; B, moderate; C, weak; I, insufficient) were assigned to the evidence that involved a direct comparison of alternative techniques.

RESULTS:

The preponderance of evidence from the literature suggests a small (2-4 mmHg) benefit from the use of mitomycin-C (MMC), but not 5-fluorouracil (5-FU), in combined cataract and glaucoma surgery (evidence grade B). Two-site surgery provides slightly lower (1-3 mmHg) intraocular pressure (IOP) than one-site surgery (evidence grade C), and IOP is lowered more (1-3 mmHg) by phacoemulsification than by nuclear expression in combined procedures (evidence grade C). There is insufficient evidence to conclude either that staged or combined procedures give better results or that alternative glaucoma procedures are superior to trabeculectomy in combined procedures.

CONCLUSIONS:

In the literature on surgical techniques and adjuvants used in the management of coexisting cataract and glaucoma, the strongest evidence of efficacy exists for using MMC, separating the incisions for cataract and glaucoma surgery, and removing the nucleus by phacoemulsification.

Characteristics, complications, and gaps in evidence-based interventions in rheumatic heart disease: the Global Rheumatic Heart Disease Registry (the REMEDY study)

AIMS: Rheumatic heart disease (RHD) accounts for over a million premature deaths annually; however, there is little contemporary information on presentation, complications, and treatment.

METHODS AND RESULTS: This prospective registry enrolled 3343 patients (median age 28 years, 66.2% female) presenting with RHD at 25 hospitals in 12 African countries, India, and Yemen between January 2010 and November 2012. The majority (63.9%) had moderate-to-severe multivalvular disease complicated by congestive heart failure (33.4%), pulmonary hypertension (28.8%), atrial fibrillation (AF) (21.8%), stroke (7.1%), infective endocarditis (4%), and major bleeding (2.7%). One-quarter of adults and 5.3% of children had decreased left ventricular (LV) systolic function; 23% of adults and 14.1% of children had dilated LVs. Fifty-five percent (n = 1761) of patients were on secondary antibiotic prophylaxis. Oral anti-coagulants were prescribed in 69.5% (n = 946) of patients with mechanical valves (n = 501), AF (n = 397), and high-risk mitral stenosis in sinus rhythm (n = 48). However, only 28.3% (n = 269) had a therapeutic international normalized ratio. Among 1825 women of childbearing age (12-51 years), only 3.6% (n = 65) were on contraception. The utilization of valvuloplasty and valve surgery was higher in upper-middle compared with lower-income countries.

CONCLUSION: Rheumatic heart disease patients were young, predominantly female, and had high prevalence of major cardiovascular complications. There is suboptimal utilization of secondary antibiotic prophylaxis, oral anti-coagulation, and contraception, and variations in the use of percutaneous and surgical interventions by country income level.

Towards the 2021 UK Census imputation strategy: Response mode as a matching variable in a donor-based approach?

Since July 2014, the Office for National Statistics has committed to a predominantly online 2021 UK Census. Item-level imputation will play an important role in adjusting the 2021 Census database. Research indicates that the internet may yield cleaner data than paper based capture and attract people with particular characteristics. Here, we provide preliminary results from research directed at understanding how we might manage these features in a 2021 UK Census imputation strategy. Our findings suggest that if using a donor-based imputation method, it may need to consider including response mode as a matching variable in the underlying imputation model.

A systematic review of evidence-based assessment practices by allied health practitioners for children with cerebral palsy

AIM: The routine use of psychometrically robust assessment tools is integral to best practice. This systematic review aims to determine the extent to which evidence-based assessment tools were used by allied health practitioners for children with cerebral palsy (CP).

METHOD: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocols 2015 was employed. A search strategy applied the free text terms: 'allied health practitioner', 'assessment', and 'cerebral palsy', and related subject headings to seven databases. Included articles reported assessment practices of occupational therapists, physiotherapists, or speech pathologists working with children with CP aged 0 to 18 years, published from the year 2000.

RESULTS: Fourteen articles met the inclusion criteria. Eighty-eight assessment tools were reported, of which 23 were in high use. Of these, three tools focused on gross motor function and had acceptable validity for use with children with CP: Gross Motor Function Measure, Gross Motor Function Classification System, and goniometry. Validated tools to assess other activity components, participation, quality of life, and pain were used infrequently or not at all.

INTERPRETATION: Allied health practitioners used only a few of the available evidence-based assessment tools. Assessment findings in many areas considered important by children and families were rarely documented using validated assessment tools.

Midwifery-led antenatal care models: mapping a systematic review to an evidence-based quality framework to identify key components and characteristics of care

Background: Implementing effective antenatal care models is a key global policy goal. However, the mechanisms of action of these multi-faceted models that would allow widespread implementation are seldom examined and poorly understood. In existing care model analyses there is little distinction between what is done, how it is done, and who does it. A new evidence-informed quality maternal and newborn care (QMNC) framework identifies key characteristics of quality care. This offers the opportunity to identify systematically the characteristics of care delivery that may be generalizable across contexts, thereby enhancing implementation. Our objective was to map the characteristics of antenatal care models tested in Randomised Controlled Trials (RCTs) to a new evidence-based framework for quality maternal and newborn care; thus facilitating the identification of characteristics of effective care.

Methods: A systematic review of RCTs of midwifery-led antenatal care models. Mapping and evaluation of these models’ characteristics to the QMNC framework using data extraction and scoring forms derived from the five framework components. Paired team members independently extracted data and conducted quality assessment using the QMNC framework and standard RCT criteria.

Results: From 13,050 citations initially retrieved we identified 17 RCTs of midwifery-led antenatal care models from Australia (7), the UK (4), China (2), and Sweden, Ireland, Mexico and Canada (1 each). QMNC framework scores ranged from 9 to 25 (possible range 0–32), with most models reporting fewer than half the characteristics associated with quality maternity care. Description of care model characteristics was lacking in many studies, but was better reported for the intervention arms. Organisation of care was the best-described component. Underlying values and philosophy of care were poorly reported.

Conclusions: The QMNC framework facilitates assessment of the characteristics of antenatal care models. It is vital to understand all the characteristics of multi-faceted interventions such as care models; not only what is done but why it is done, by whom, and how this differed from the standard care package. By applying the QMNC framework we have established a foundation for future reports of intervention studies so that the characteristics of individual models can be evaluated, and the impact of any differences appraised.

Towards a knowledge-based approach for effective decision-making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport.

Random Forest Based Approach for Concept-Drift Handling

Algorithms for concept drift handling are important for various applications including video analysis and smart grids. In this paper we present decision tree ensemble classication method based on the Random Forest algorithm for concept drift. The weighted majority voting ensemble aggregation rule is employed based on the ideas of Accuracy Weighted Ensemble (AWE) method. Base learner weight in our case is computed for each sample evaluation using base learners accuracy and intrinsic proximity measure of Random Forest. Our algorithm exploits both temporal weighting of samples and ensemble pruning as a forgetting strategy. We present results of empirical comparison of our method with îriginal random forest with incorporated replace-the-looser forgetting andother state-of-the-art concept-drift classiers like AWE2.