VIDEO LOCALIZATION USING ARRAY OF MICORPHONES

Object localization helps to improve the surveillance system and provide extra information from the camera. In this study DCS 5220 PT camera and array of microphones are used to achieve camera localization based on audio inputs, the system consists of microphones, multiplexing circuit, computer and PT camera. The results obtains clearly demonstrates that this techniques is usable for videodiscussion applications. The localization algorithm is based on comparing the amplitude level of the signals from all microphones and then selects the one with higher amplitude, strong noise presence is one of the limitations of this techniques, however the type of noise add can be clearly identified in the frequency spectrum, and for this reason signals are compared in their frequency spectrum after the noise is been trimmed off. The DCS 5220 PT camera is IP camera manufactured by Dlink, it can pan and tilt by using URL command; to utilize the camera a network is been created by using DR 300 wireless router with data rate up to 54 Mbps and can accommodate up to 4 network elements. The system is been developed for closed room localization but it can also be extended to outdoor applications by using suitable sensors and suitable cameras, in video discussions the system can be used in conferences and in parliament halls where such a system can be used as an automatic cameraman

3D VISUAL TRACKING USING A SINGLE CAMERA

automated surveillance and motion based recognition. 3D tracking address the localization of moving target is the 3D space. Therefore, 3D tracking requires 3D measurement of the moving object which cannot be obtained from 2D cameras. Existing 3D tracking systems use multiple cameras for computing the depth of field and it is only used in research laboratories. Millions of surveillance cameras are installed worldwide and all of them capture 2D images. Therefore, 3D tracking cannot be performed with these cameras unless multiple cameras are installed at each location in order to compute the depth. This means installing millions of new cameras which is not a feasible solution. This work introduces a novel depth estimation method from a single 2D image using triangulation. This method computes the absolute depth of field for any object in the scene with high accuracy and short computational time. The developed method is used for performing 3D visual tracking using a single camera by providing the depth of field and ground coordinates of the moving object for each frame accurately and efficiently. Therefore, this technique can help in transforming existing 2D tracking and 2D video analytics into 3D without incurring additional costs. This makes video surveillance more efficient and increases its usage in human life. The proposed methodology uses background subtraction process for detecting a moving object in the image. Then, the newly developed depth estimation method is used for computing the 3D measurement of the moving target. Finally, the unscented Kalman filter is used for tracking the moving object given the 3D measurement obtained by the triangulation method. This system has been test and validated using several video sequences and it shows good performance in term of accuracy and computational complexity

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

DEVELOPMENT OF POINT CLOUD DESCRIPTORS FOR ROBUST 3D RECOGNITION

Object recognition allows machines to understand the nature of objects it encounters in the surrounding environment. Descriptors are the most important element for robust object recognition system as they assign a unique identification to each object that withstands pose and illumination variations. Among many surface descriptors proposed in the literature, orientation based descriptors are the most commonly used, however they are represented with large and sparse histograms. Moreover, existing descriptors are highly susceptible to noise and viewpoint variations. These limitation prevented object recognition algorithms from being implemented on embedded devices (e.g: smartphones) and mobile robots specially for mapping applications

DEVELOPMENT OF POINT CLOUD DESCRIPTORS FOR ROBUST 3D RECOGNITION

Object recognition allows machines to understand the nature of objects it encounters in the surrounding environment. Descriptors are the most important element for robust object recognition system as they assign a unique identification to each object that withstands pose and illumination variations. Among many surface descriptors proposed in the literature, orientation based descriptors are the most commonly used, however they are represented with large and sparse histograms. Moreover, existing descriptors are highly susceptible to noise and viewpoint variations. These limitation prevented object recognition algorithms from being implemented on embedded devices (e.g: smartphones) and mobile robots specially for mapping applications

Workplace violence against healthcare workers during the COVID‐19 pandemic in Sudan: A cross‐sectional study

Abstract Background Workplace violence (WPV) against healthcare workers (HCWs) is a growing global issue. During the coronavirus diseases‐2019 (COVID‐19) pandemic, violent attacks on HCWs have been documented worldwide. This study aimed to investigate the magnitude and pattern of WPV among HCWs in Sudan during the COVID‐19 pandemic. Methods A web‐based cross‐sectional study of WPV was conducted among registered medical and health workers (pharmacists, physicians, dentists, nurses, laboratory technicians, and administrative and paramedical staff) during the COVID‐19 pandemic in Sudan. Data were collected from August to December 2021 using a self‐administered questionnaire distributed through social media platforms. Results A total of 792 HCWs returned the online questionnaire. The mean age was 33.5 ± 8.6 years, where more than half were females (54.9%) and working during the day shift (58.8%). During the COVID‐19 pandemic, three out of every four participants (78.3%) reported experiencing violence, with 65.8 % experiencing it more than three times. The common types of violence experienced were verbal (91.6%), physical (50.0%), and sexual abuse (11.0%). The emergency department reported the highest number of violent incidents (46.9%). Half of these violent events were not reported (50.3%), primarily due to a lack of a reporting system. The demographic factors that were significantly associated with exposure to violence were participants’ occupation (p < 0.001), age (p = 0.001), marital status (p = 0.002), and years of working experience (p = 0.020). Conclusion WPV was rampant among the HCWs in Sudan during the COVID‐19 pandemic. The current findings are presented to draw the attention of policy leaders and stakeholders in Sudan to this alarming problem prompting the pressing need for policy and system interventions

Healthcare Utilization with Drug Acquisition and Expenses at the National Health Insurance Fund in Sudan

Background: Understanding the pattern of care use can provide valuable information for reform interventions. This study investigates the pattern of healthcare utilization and its association with drug acquisition patterns and expenses in the National Health Insurance Fund (NHIF) of Al Jazira State in Sudan. Methods: A cross-sectional survey was conducted at NHIF primary healthcare centers of Al Jazirah state in Sudan. Results: A total of 768 beneficiaries were interviewed, of which 63.2% reported using out-of-network physician care, while 36.8% receive care from the NHIF physician network only. More than half (60.8%) of NHIF-interviewed clients reported a heavy burden of medication costs. The pattern of physician utilization was significantly associated with the number and source of regular drugs, the burden of out-of-pocket payment, and monthly out-of-pocket expenditures on medications, (p &lt; 0.001). The regression analysis revealed that gender, marital status, number of chronic diseases, and number of regular drugs were the significant predictors of the pattern of physician care utilization; these factors explained nearly 36% of the variance in respondents&rsquo; pattern of physician care utilization. Conclusions: An impressive proportion of out-of-network care was found in Al Jazirah State in Sudan. The NHIF stakeholders should consider medication subsidy as a potential strategy for decreasing patient leakage to out-of-network services

Healthcare Utilization with Drug Acquisition and Expenses at the National Health Insurance Fund in Sudan

Background: Understanding the pattern of care use can provide valuable information for reform interventions. This study investigates the pattern of healthcare utilization and its association with drug acquisition patterns and expenses in the National Health Insurance Fund (NHIF) of Al Jazira State in Sudan. Methods: A cross-sectional survey was conducted at NHIF primary healthcare centers of Al Jazirah state in Sudan. Results: A total of 768 beneficiaries were interviewed, of which 63.2% reported using out-of-network physician care, while 36.8% receive care from the NHIF physician network only. More than half (60.8%) of NHIF-interviewed clients reported a heavy burden of medication costs. The pattern of physician utilization was significantly associated with the number and source of regular drugs, the burden of out-of-pocket payment, and monthly out-of-pocket expenditures on medications, (p < 0.001). The regression analysis revealed that gender, marital status, number of chronic diseases, and number of regular drugs were the significant predictors of the pattern of physician care utilization; these factors explained nearly 36% of the variance in respondents’ pattern of physician care utilization. Conclusions: An impressive proportion of out-of-network care was found in Al Jazirah State in Sudan. The NHIF stakeholders should consider medication subsidy as a potential strategy for decreasing patient leakage to out-of-network services