Search

The conventional clustering methods assume a binary classification and establish a complete inclusive or exclusive type relation of an object with a cluster. In contrast, a three-way paradigm handles situations where an object may or may not belong to a cluster, i.e., uncertain. The objects belonging to the uncertainty region may lead to inclusion or exclusion after further processing and information. One of the use cases of the three-way paradigm is the overlapping region between different clusters. Effective computation of overlapping objects is crucial to the application’s overall success. In this paper, we employ a three-way clustering approach inspired by image blurring and sharpening operations that consider the objects in the inside or outside regions of a cluster to be non-overlapping. The objects belonging to the partial region of more than one cluster are considered overlapping. The experiment conducted on Birds, Scenes, and 20 newsgroups datasets indicates that the proposed approach improves the F1 measure and hamming loss up to 18.6% and 4.9%, respectively. Furthermore, the system’s robustness for overlapping regions is observed using typical clustering measures. The experimental results suggested that the proposed approach may improve the computation of overlapping regions effectively.

Abstract Background The study aimed to investigate the effect of urea molasses mineral blocks (UMMB) on nutrient digestibility, productive performance and blood biochemical profile of indigenous yaks under various feeding systems. A total of sixteen yaks were randomly divided into four groups (n = 4 animal per group) and offered the, following feeding systems: (A) stall feeding, (B), urea molasses mineral block (UMMB) + stall feeding, (C) yard feeding and (D) UMMB + yard feeding. Trial lasted for 40 days. Results Results showed that nutrients intake (g) and nutrient digestibility (%) of dry matter (DM), organic matter (OM), crude protein (CP), ether extract (EE) and crude fiber (CF) were significantly higher (p

The explainable human–computer interaction (HCI) is about designing approaches capable of using cognitive characteristics like humans. One such characteristic is human vision and its accuracy. The accuracy measures the trust in that system. Therefore, improving accuracy in the authorization with identification process is a primary concern for a visual-based explainable human–computer interaction system. In this article, we propose a three-way decision based ensembled face recognition mechanism called E3FRM. The E3FRM uses a three-way approach to determine the match cases and the respective worth of the captured image with the match cases. Features are extracted using PCA/FLD, and the ensembled face recognition algorithms utilize the extracted features to process the image. Ensemble Face recognition approaches find the match cases based on a given threshold. Finally, the three-way decision model evaluates the suitability of the captured image for acceptance, rejection, or deferred cases with a dual verification mechanism. Experimental results on well-known eighteen datasets suggest improvements in commonly used metrics of F1, Accuracy and Recall by up to 0.8% to 12.8%, 1% to 9.6% and 1.2% to 13.9%, respectively, in comparison to the state-of-the-art methods available, including SPCA +, ML-EM, FLDA-SVD, DMMA, Fast-DMMA, LU, LPP, TDL, KCFT, RBF + DT, and NMF. Furthermore, the proposed approach is comparatively analyzed with ensembled face recognition methods that result in an outperformed F1, Accuracy and Recall by up to 1.1% to 10.3%, 0.1% to 7.3% and 0.9% to 10.5%, respectively. These results suggest that the proposed model may improve face recognition accuracy and the resulting trust in the machines.

In this article, we consider a fractal-fractional tobacco mathematical model with generalized kernels of Mittag-Leffler functions for qualitative and numerical studies. From qualitative point of view, our study includes; existence criteria, uniqueness of solution and Hyers-Ulam stability. For the numerical aspect, we utilize Lagrange's interpolation polynomial and obtain a numerical scheme which is further illustrated simulations. Lastly, a comparative analysis is presented for different fractal and fractional orders. The numerical results are divided into four figures based on different fractal and fractional orders. We have found that the fractional and fractal orders have a significant impact on the dynamical behaviour of the model.

Image denoising is a vital pre-processing phase, used to refine the image quality and make it more informative. Many image-denoising algorithms have been proposed with their own pros and cons. This paper presents a comprehensive study of the median filter and its different variants to reduce or remove the impulse noise from gray scale images. These filters are compared with respect to their functionality, time complexity and relative performance. For performance evaluation of the existing algorithms, extensive MATLAB based simulations have been carried out on a set of images. For benchmarking the relative performance, we have used Peak Signal to Noise Ratio (PSNR), Root Mean Square Error (RMSE), Universal Image Quality Index (UQI), Structural Similarity Index (SSIM) and Edge-strength Similarity (ESSIM) as quality assessment metrics. The Extended median filter (EMF) and Modified BDND are best in terms of relative statistical ratios and pleasant visual results where IAMF is having the best time complexity among existing algorithms.

Aims and objectives This study sets out to describe benefits from the implementation of electronic observation charting in intensive care units (ICU). This was an extension to the existing hospital wide digital health system. We evaluated error reduction, time-savings and the costs associated with conversion from paper to digital records. The world health emergency of COVID-19 placed extraordinary strain on ICU and staff opinion was evaluated to test how well the electronic system performed.Methods A clinically led project group working directly with programmers developed an electronic patient record for intensive care. Data error rates, time to add data and to make calculations were studied before and after the introduction of electronic charts. User feedback was sought pre and post go-live (during the COVID-19 pandemic) and financial implications were calculated by the hospital finance teams.Results Error rates equating to 219 000/year were avoided by conversion to electronic charts. Time saved was the equivalent of a nursing shift each day. Recurrent cost savings per year were estimated to be £257k. Staff were overwhelmingly positive about electronic charts in ICU, even during a health pandemic and despite redeployment into intensive care where they were using the electronic charts for the first time.Discussion Electronic ICU charts have been successfully introduced into our institution with benefits in terms of patient safety through error reduction and improved care through release of nursing time. Costs have been reduced. Staff feel supported by the digital system and report it to be helpful even during redeployment and in the unfamiliar environment of intensive care.

Computer vision (CV) and human–computer interaction (HCI) are essential in many technological fields. Researchers in CV are particularly interested in real-time object detection techniques, which have a wide range of applications, including inspection systems. In this study, we design and implement real-time object detection and recognition systems using the single-shoot detector (SSD) algorithm and deep learning techniques with pre-trained models. The system can detect static and moving objects in real-time and recognize the object’s class. The primary goals of this research were to investigate and develop a real-time object detection system that employs deep learning and neural systems for real-time object detection and recognition. In addition, we evaluated the free available, pre-trained models with the SSD algorithm on various types of datasets to determine which models have high accuracy and speed when detecting an object. Moreover, the system is required to be operational on reasonable equipment. We tried and evaluated several deep learning structures and techniques during the coding procedure and developed and proposed a highly accurate and efficient object detection system. This system utilizes freely available datasets such as MS Common Objects in Context (COCO), PASCAL VOC, and Kitti. We evaluated our system’s accuracy using various metrics such as precision and recall. The proposed system achieved a high accuracy of 97% while detecting and recognizing real-time objects.

The eradication of the concentration of wealth is one of the prime objectives of Islamic finance. Many scholars have written on this issue, who claim that by eradicating interest from the society, we will be able to minimise the concentration of wealth in an economy. This study conjectures that interest-free finance is a necessary but not sufficient condition for the eradication of concentration of wealth. The sufficient condition is to bring change in the objective of the Islamic banks that is, switching the moto from the maximisation of the profit to the maximisation of welfare of society. This paper states that the main focus of Islamic banks is to transform the current models of interest based transactions to interest free transactions. However, merely changing the transactions from interest based to interest free might not be enough to achieve the main objective of Islamic finance. The study compares the assets side of Islamic and conventional banks to provide support in favour of the hypothesis that with current objective of profit maximisation, the Islamic banks are less likely to play any role in the eradication of the concentration of wealth.

Objectives To safely expand and adapt the normal workings of a large critical care unit in response to the COVID-19 pandemic.Methods In April 2020, UK health systems were challenged to expand critical care capacity rapidly during the first wave of the COVID-19 pandemic so that they could accommodate patients with respiratory and multiple organ failure. Here, we describe the preparation and adaptive responses of a large critical care unit to the oncoming burden of disease. Our changes were similar to the revolution in manufacturing brought about by ‘Long Shops’ of 1853 when Richard Garrett and Sons of Leiston started mass manufacture of traction engines. This innovation broke the whole process into smaller parts and increased productivity. When applied to COVID-19 preparations, an assembly line approach had the advantage that our ICU became easily scalable to manage an influx of additional staff as well as the increase in admissions. Healthcare professionals could be replaced in case of absence and training focused on a smaller number of tasks.Results Compared with the equivalent period in 2019, the ICU provided 30.9% more patient days (2599 to 3402), 1845 of which were ventilated days (compared with 694 in 2019, 165.8% increase) while time from first referral to ICU admission reduced from 193.8±123.8 min (±SD) to 110.7±76.75 min (±SD). Throughout, ICU maintained adequate capacity and also accepted patients from neighbouring hospitals. This was done by managing an additional 205 doctors (70% increase), 168 nurses who had previously worked in ICU and another 261 nurses deployed from other parts of the hospital (82% increase).Our large tertiary hospital ensured a dedicated non-COVID ICU was staffed and equipped to take regional emergency referrals so that those patients requiring specialist surgery and treatment were treated throughout the COVID-19 pandemic.Conclusions We report how the challenge of managing a huge influx of patients and redeployed staff was met by deconstructing ICU care into its constituent parts. Although reported from the largest colocated ICU in the UK, we believe that this offers solutions to ICUs of all sizes and may provide a generalisable model for critical care pandemic surge planning.

This study aimed to evaluate the impact of dietary addition of jojoba seed oil on productive performance, physicochemical attributes and carcass quality of broiler meat under tropical weather conditions. A total of 384 one-day-old Ross-308 were subdivided into four dietary treatments of jojoba seed oil: 0, 50, 100 and 150 mg/kg of control diet. Each treatment group included twelve replicates with eight birds each. The results showed that dietary supplementation of jojoba seed oil linearly increased (p < 0.01) feed intake, body weight gain and improved (p < 0.01) feed conversion ratio. Interestingly, diets supplemented with jojoba seed oil linearly (p < 0.05) improved the percentage of dressing and reduced abdominal fat percentage compared to the control group. Dietary supplementation of jojoba seed oil showed no effects (p ≥ 0.05) on the weight of internal organs, including liver, heart, gizzard, spleen and pancreas of broiler chickens. Increasing jojoba seed oil levels in the diet decreased (p < 0.001) percentages of cook and drip losses of breast and leg (drumstick and thigh) muscles of broilers. It was concluded that jojoba seed oil used as a feed additive up to 150 mg/kg improves growth performance and meat quality of broiler chickens in tropical weather conditions.

This paper focuses on the role of local governments in bringing about fair, accountable, incoorruptible and responsive (FAIR) governance. Local governments around the world have done important innovations to earn the trust of their residents and their comparative performance is of great interest yet a comprehensive framework to provide such benchmarking is not available. This paper attempts to fill this void, by developing a general framework for performance accountability of local governments and by relating real world practices to aspects of this framework. The proposed rating framework requires several types of assessments: (a) their compliance with due process and law; (b) monitoring of fiscal health for sustainability; (c) monitoring of service delivery ; and (d) citizens’ satisfaction with local services. The approach yields key indicators useful for benchmarking performance that can be used in selfevaluation and improvement of performance. t From an analysis of practices in local government performance monitoring and evaluation, the paper concludes that ad hoc ad-on self standing monitoring and evaluation systems are more costly and less useful than built-in tools and mechanisms for government transparency, self–evaluation and citizen based accountability such as local government output budgeting and output based fiscal transfers to finance local services.

Background and Objectives: The purpose of this study is to evaluate the frictional resistance generated by conventional stainless steel, radiance ceramic bracket, self-ligating and composite brackets using a 0.019 × 0.025 stainless steel straight length wires in a 022 slot and to select brackets based on their frictional characteristic. Methodology: In order to conduct this study, four different types of bracket system were selected of the mclaughlin-bennet-trevesi (MBT) discipline. They are Group 1 - stainless steel, Group 2 - composite bracket Group 3 - (American Orthodontics) radiance ceramic bracket Group 4 - self-ligating bracket (SLB) (Empower). In this study, five maxillary brackets of an arch of each type were used. All brackets are 0.022 × 0.028" in preadjusted edgewise appliance which simulates the dental arch. Five brackets were bonded to a stainless steel bar of dimension 150 mm × 25 mm × 3 mm. The bracket-arch wire units were submitted to mechanical test with an Instron universal testing machine 3365. A testing apparatus or holding jig was designed to hold the bracket during the mechanical test. Each sample was pulled at a speed of 6 mm for 1 min. Descriptive statistical information including mean and standard deviation of maximum friction force was calculated for each bracket wire combination. Interpretation and Conclusion: The SLB has the least friction among the four groups. The ceramic bracket showed the highest friction followed by stainless steel bracket, composite bracket, and SLB.

During treatment of acute type A aortic dissection there is potential for both pre- and intra-operative malperfusion. There are a number of monitoring strategies that may allow for earlier detection of potentially catastrophic malperfusion (particularly cerebral malperfusion) phenomena available for the anaesthetist and surgeon. This review article sets out to discuss the benefits of the current standard monitoring techniques available as well as desirable/experimental techniques which may serve as adjuncts in the monitoring of these complex patients.

Intergovernmental fiscal transfers are a dominant feature of sub-national finance in most countries. They are used to ensure that revenues roughly match the expenditure needs of various orders (levels) of sub-national governments. They are also used to advance national, regional and local area objectives such as fairness and equity and creating a common economic union. The structure of these transfers create incentives for national, regional and local governments that have a bearing on fiscal management, macroeconomic stability, distributional equity, allocative efficiency and public services delivery. This paper reviews conceptual, empirical and the practice literature to distill lessons of policy interest in designing the fiscal transfers to create the right incentives for prudent fiscal managment and competitive and innovative service delivery. The paper provides practical guidance on the design of performance-oriented transfers that emphasize bottom-up, client- focused and results-based government accountability. It cites examples of simple but innovative grant designs that can satisfy grantors’ objectives while preserving local autonomy and creating an enabling environment for responsive, responsible, equitable and accountable public governance. The paper further provides guidance on the design and the practice of equalization transfers for regional fiscal equity as well as the institutional arrangements for implementation of such transfer mechanisms. The paper concludes with negative (practices to avoid) and positive (practices to emulate) lessons from international practices.

Although the field of classroom learning environments has undergone remarkable expansion and internationalisation, no study in Afghanistan in any subject area or at any educational level has ever adopted a learning environment framework or involved the assessment and investigation of classroom environments. Our study in Afghanistan included seven learning environment scales from the widely-used What Is Happening In this Class? (WIHIC) questionnaire, together with two scales assessing the student attitudes of Enjoyment and Self-regulation. After minor modifications to suit the Afghani context, scales were translated into Dari (one of the two dominant languages in Afghanistan) and then independently back-translated to check the accuracy of the original translation. Analyses of data from 1619 grade 10-12 science students supported the validity and reliability of the Dari-language scales. Past research in other countries was replicated in Afghanistan in that positive and statistically-significant associations were found between the learning environment and student attitudes. Some consistent patterns of gender differences and school-location differences (urban/rural) were identified.