MEDICAL IMAGES COMPRESSION BASED ON SPIHT AND BAT INSPIRED ALGORITHMS

There is a significant necessity to compress the medical images for the purposes of communication and storage.Most currently available compression techniques produce an extremely high compression ratio with a high-quality loss. Inmedical applications, the diagnostically significant regions (interest region) should have a high image quality. Therefore, it ispreferable to compress the interest regions by utilizing the Lossless compression techniques, whilst the diagnostically lessersignificant regions (non-interest region) can be compressed by utilizing the Lossy compression techniques. In this paper, a hybridtechnique of Set Partition in Hierarchical Tree (SPIHT) and Bat inspired algorithms have been utilized for Lossless compressionthe interest region, and the non-interest region is loosely compressed with the Discrete Cosine Transform (DCT) technique.The experimental results present that the proposed hybrid technique enhances the compression performance and ratio. Also,the utilization of DCT increases compression performance with low computational complexity

A realist evaluation of the role of external peer review programmes in improving the quality of mental health services

Background: Available evidence suggests that membership of external peer review programmes can help improve the quality of health care services. However, little is known about how this is achieved and what key mechanisms and contexts are essential for quality improvement. Methods: I undertook a mixed methods realist evaluation of peer review networks and accreditation schemes in inpatient and community-based mental health services provided by the Royal College of Psychiatrists’ Centre for Quality Improvement (CCQI). Informed by a systematic literature review, I collected qualitative data from coordinators (four focus groups) and participants (122 interviews) of external peer review programmes. I also collected quantitative data from 178 community-based memory clinics and 33 inpatient mental health services to examine whether organisational readiness for change influenced service quality. Results: Causal mechanisms including sharing and learning, consultation, and engagement of senior management and junior staff were essential for sustained quality improvement. The most salient contexts were type of external peer review and length of membership In accreditation schemes, most changes occurred before or during self-review, and following written feedback for peer review networks. A two-level linear model signalled services with higher baseline readiness for change achieved greater quality improvement through membership of a peer review network, however findings were not statistically significant. Qualitative findings echoed the importance of readiness for change constructs. Conclusions: Differences in when change occurs between peer review networks and accreditation schemes should be considered by organisations that provide external peer review programmes. Sharing and learning was the main essential causal mechanism of external peer review programmes. To maximise the benefit of participation, this mechanism should be further supported and enhanced. A future of increased competition in healthcare could reduce sharing and learning opportunities; indicating a need to further develop the evidence base for external peer review.Open Acces

Charting the path towards a long-term knowledge brokerage function: an ecosystems view

Hybrid networks of actors such as policymakers, funders, scholars, and business practitioners are simultaneous producers and consumers of evidence use. While this diversity of evidence use is a strength, it also necessitates greater collaboration among interested parties for knowledge exchange. To address this need, we investigate how ecotones, which are hybrid networks operating in the transitional area between two distinct ecosystems, such as academic research and policy ecosystems, must involve, disseminate, and integrate different types of knowledge. Specifically, our research aims to unpack how an ecotone’s knowledge brokerage function evolves over its lifecycle. This paper presents the findings of a phenomenological investigation involving experts from the policy and academic research ecosystems. The study introduces a three-stage maturity transitions framework that outlines the trajectory of the brokerage function throughout the ecotone’s lifecycle: i. as a service function, ii. a programme-partnership, and iii. a network of networks. The paper contributes to the theory of knowledge brokerage for policy-making. We reflect on our findings and discuss the theoretical contributions within an ecosystem approach and their associated research and policy implications

Modern drowsiness detection techniques: a review

According to recent statistics, drowsiness, rather than alcohol, is now responsible for one-quarter of all automobile accidents. As a result, many monitoring systems have been created to reduce and prevent such accidents. However, despite the huge amount of state-of-the-art drowsiness detection systems, it is not clear which one is the most appropriate. The following points will be discussed in this paper: Initial consideration should be given to the many sorts of existing supervised detecting techniques that are now in use and grouped into four types of categories (behavioral, physiological, automobile and hybrid), Second, the supervised machine learning classifiers that are used for drowsiness detection will be described, followed by a discussion of the advantages and disadvantages of each technique that has been evaluated, and lastly the recommendation of a new strategy for detecting drowsiness

Driving sleepiness detection using electrooculogram analysis and grey wolf optimizer

In modern society, providing safe and collision-free travel is essential. Therefore, detecting the drowsiness state of the driver before its ability to drive is compromised. For this purpose, an automated hybrid sleepiness classification system that combines the artificial neural network and gray wolf optimizer is proposed to distinguish human Sleepiness and fatigue. The proposed system is tested on data collected from 15 drivers (male and female) in alert and sleep-deprived conditions where physiological signals are used as sleep markers. To evaluate the performance of the proposed algorithm, k-nearest neighbors (k-NN), support vector machines (SVM), and artificial neural networks (ANN) classifiers have been used. The results show that the proposed hybrid method provides 99.6% accuracy, while the SVM classifier provides 93.0% accuracy when the kernel is (RBF) and outlier (0.1). Furthermore, the k-NN classifier provides 96.7% accuracy, whereas the standalone ANN algorithm provides 97.7% accuracy

Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Face and Eye Tracking

It is critical today to provide safe and collision-free transport. As a result, identifying the driver’s drowsiness before their capacity to drive is jeopardized. An automated hybrid drowsiness classification method that incorporates the artificial neural network (ANN) and the gray wolf optimizer (GWO) is presented to discriminate human drowsiness and fatigue for this aim. The proposed method is evaluated in alert and sleep-deprived settings on the driver drowsiness detection of video dataset from the National Tsing Hua University Computer Vision Lab. The video was subjected to various video and image processing techniques to detect the drivers’ eye condition. Four features of the eye were extracted to determine the condition of drowsiness, the percentage of eyelid closure (PERCLOS), blink frequency, maximum closure duration of the eyes, and eye aspect ratio (ARE). These parameters were then integrated into an ANN and combined with the proposed method (gray wolf optimizer with ANN [GWOANN]) for drowsiness classification. The accuracy of these models was calculated, and the results demonstrate that the proposed method is the best. An Adadelta optimizer with 3 and 4 hidden layer networks of (13, 9, 7, and 5) and (200, 150, 100, 50, and 25) neurons was utilized. The GWOANN technique had 91.18% and 97.06% accuracy, whereas the ANN model had 82.35% and 86.76%

Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Voice Recognition

Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively

Optimizing hopfield neural network for super-resolution mapping

Remote sensing is a potential source of information of land covers on the surface of the Earth. Different types of remote sensing images offer different spatial resolution quality. High resolution images contain rich information, but they are expensive, while low resolution image are less detail but they are cheap. Super-resolution mapping (SRM) technique is used to enhance the spatial resolution of the low resolution image in order to produce land cover mapping with high accuracy. The mapping technique is crucial to differentiate land cover classes. Hopfield neural network (HNN) is a popular approach in SRM. Currently, numerical implementation of HNN uses ordinary differential equation (ODE) calculated with traditional Euler method. Although producing satisfactory accuracy, Euler method is considered slow especially when dealing with large data like remote sensing image. Therefore, in this paper several advanced numerical methods are applied to the formulation of the ODE in SRM in order to speed up the iterative procedure of SRM. These methods are an improved Euler, Runge-Kutta, and Adams-Moulton. Four classes of land covers such as vegetation, water bodies, roads, and buildings are used in this work. Results of traditional Euler produces mapping accuracy of 85.18% computed in 1000 iterations within 220-1020 seconds. Improved Euler method produces accuracy of 86.63% computed in a range of 60-620 iterations within 20-500 seconds. Runge-Kutta method produces accuracy of 86.63% computed in a range of 70-600 iterations within 20-400 seconds. Adams-Moulton method produces accuracy of 86.64% in a range of 40-320 iterations within 10-150 seconds

Does a working day keep the doctor away? A critical review of the impact of unemployment and job insecurity on health and social care utilisation

While the negative impact of unemployment on health is relatively well established, the extent to which that impact reflects on changes in health and social care utilisation is not well understood. This paper critically reviews the direction, magnitude and drivers of the impact of unemployment and job insecurity on health and social care utilisation across different care settings. We identified 28 relevant studies, which included 79 estimates of association between unemployment/job insecurity and healthcare utilisation. Positive associations dominated mental health services (N = 8 out of 11), but not necessarily primary care (N = 25 out of 43) or hospital care (N = 5 out of 22). We conducted a meta-analysis to summarise the magnitude of the impact and found that unemployed individuals were about 30% more likely to use health services compared to those employed, although this was largely driven by mental health service use. Key driving factors included financial pressure, health insurance, social network, disposable time and depression/anxiety. This review suggests that unemployment is likely to be associated with increased mental health service use, but there is considerable uncertainty around primary and hospital care utilisation. Future work to examine the impact across other settings, including community and social care, and further explore non-health determinants of utilisation is needed. The protocol was registered in PROSPERO (CRD42020177668)

Needs of Farmers for Guidance Publication to the Development of Agricultural Extension in Anbar, Iraq

Guidance publication one of the most important sources of information for farmers about crop techniques,knowledge, and cropping information to get high productivity. Targeted research to asses the relationship between the wheat grower information level and recommendations of the Scientific pamphlet of wheat and some independent variables studied, as well as identify social characteristics, and functional for extension workers, and determine the reasons for non-use of the indicative releases from the point of view of agricultural workers. Iraq determines the research community in all extension agents to maintain a (92 Advisor) and sample farmer b (145 farms) of village farmers discussed (414) farms, selected a random sample of 35% of the province's villages and all of the following villages: ( Qusaiba village, Parwana and sons Hassan and corner Walnhih , Znkorh and the village of Black Hill).Data were collected by personal interview from 3 January  to 28 March 2014 through the resolution, analysis of research data on the frequencies, percentages and arithmetic mean, standard deviation, range, as any simple correlation coefficient.  The most significant results show that (18.6%) are small and that the information category (31, 7%), them with the information medium, and that (49.6%) They are with high information. Moral relationship at 0.01 level (0.05) between the level of agricultural information and (Gender, age, cultural openness, sources of information), and non-moral moral level 0, 05 for each of the following independent variables (marital status, Farming, engagement, agricultural property type, participate in outreach activities, the trend towards agricultural innovations). Keywords: Guidance Publication, Farmers, Field crops, Agricultural Extension, and Iraq