Jenny Frogner, Halvor Melbye Hanisch, Lisbeth Kvam, Aud Elisabeth Witsø
Based on data from ethnographic fieldwork in Norway, we explore relationships of care between workers with intellectual disabilities (ID) and staff in the context of sheltered employment. Care relations in a sheltered workshop are analysed using Annemarie Mol’s (2008) ‘logic of care’, which we combine with the concept ‘the logic of the market’. In this context, relations of care enable persons with ID as workers, but tensions between care and market logics influence the operation of the workshop and its workers. We argue that processes of care transform market logics, and at the same time, market logics also transform processes of care. The logics are found to support each other, but the balance between them is fragile. This results in unstable conditions for care in the sheltered workshop.
{"title":"A Glass House of Care: Sheltered Employment for Persons with Intellectual Disabilities","authors":"Jenny Frogner, Halvor Melbye Hanisch, Lisbeth Kvam, Aud Elisabeth Witsø","doi":"10.16993/sjdr.992","DOIUrl":"https://doi.org/10.16993/sjdr.992","url":null,"abstract":"Based on data from ethnographic fieldwork in Norway, we explore relationships of care between workers with intellectual disabilities (ID) and staff in the context of sheltered employment. Care relations in a sheltered workshop are analysed using Annemarie Mol’s (2008) ‘logic of care’, which we combine with the concept ‘the logic of the market’. In this context, relations of care enable persons with ID as workers, but tensions between care and market logics influence the operation of the workshop and its workers. We argue that processes of care transform market logics, and at the same time, market logics also transform processes of care. The logics are found to support each other, but the balance between them is fragile. This results in unstable conditions for care in the sheltered workshop.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136202865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rheumatoid arthritis (RA), a chronic autoimmune disorder, can cause joint deformity and disability. The Janus kinases (JAKs), intracellular tyrosine kinases family (includes JAK1, JAK2, and JAK3), play an essential role in the signaling of various cytokines and are implicated in the pathogenesis of inflammatory diseases, including RA. Consequently, JAKs have attracted significant attention in recent years as therapeutic targets of RA. In the current study, we explored the role of a set of biomolecules from marine sources that could be used as specific inhibitors of JAKs and treat arthritis. The binding affinity of these molecules including astaxanthin (ATX), fucoxanthin (FX), fuscoside E (FsE), fucosterol (Fs), and phlorofucofuroeckol (PFFE) JAK3 has been analyzed. In addition, the details of relative structural interactions have been compared to those of the recently Food and Drug Administration-approved inhibitor, tofacitinib. Interestingly, some of these marine biomolecules showed a higher binding energy (b.e.) and specific binding to JAK3 active/potential sites when compared to the approved inhibitors. For instance, FsE binds to two key regulator residues of JAK3 required for its activity and for inhibitor stability, CYS909 and LYS905, with higher b.e. (-9.6) than the approved inhibitors. Thus, FsE may have a potential inhibitory action on JAKs and especially on JAK3. Additionally, PFFE can bind to several kinase critical regulators of JAK3 and the b.e. may reach -10.7. Based on the evaluation of oral availability, drug-likeness, pharmacokinetics, and medicinal chemistry friendliness, FsE seems to be the most appropriate potential inhibitor for JAK3.
类风湿性关节炎(RA)是一种慢性自身免疫性疾病，可导致关节畸形和残疾。Janus激酶(JAKs)，细胞内酪氨酸激酶家族(包括JAK1, JAK2和JAK3)，在各种细胞因子的信号传导中起重要作用，并与炎性疾病(包括RA)的发病机制有关。因此，jak作为类风湿性关节炎的治疗靶点近年来引起了人们的极大关注。在目前的研究中，我们探索了一组来自海洋的生物分子的作用，这些生物分子可以用作jak的特异性抑制剂并治疗关节炎。这些分子包括虾青素(ATX)、岩藻黄素(FX)、fuscoside E (FsE)、focus甾醇(Fs)和间苯二氟呋喃酚(PFFE) JAK3，它们的结合亲和力已被分析。此外，还将相关结构相互作用的细节与最近获得美国食品和药物管理局批准的抑制剂tofacitinib进行了比较。有趣的是，与已批准的抑制剂相比，其中一些海洋生物分子显示出更高的结合能(b.e)和对JAK3活性/潜在位点的特异性结合。例如，FsE结合JAK3的活性和抑制剂稳定性所需的两个关键调节残基，CYS909和LYS905，比批准的抑制剂具有更高的b.e值(-9.6)。因此，FsE可能对jakk，尤其是JAK3具有潜在的抑制作用。此外，PFFE可以结合JAK3的几个激酶关键调节因子，其b.e.可能达到-10.7。基于口服利用度、药物相似性、药代动力学和药物化学友好性的评估，FsE似乎是最合适的JAK3潜在抑制剂。
{"title":"Virtual Screening-based Molecular Analysis of Marine Bioactive Molecules as Inhibitors for Janus Kinase 3","authors":"E. Ahmed, S. Abdelsalam","doi":"10.57197/jdr-2023-0012","DOIUrl":"https://doi.org/10.57197/jdr-2023-0012","url":null,"abstract":"Rheumatoid arthritis (RA), a chronic autoimmune disorder, can cause joint deformity and disability. The Janus kinases (JAKs), intracellular tyrosine kinases family (includes JAK1, JAK2, and JAK3), play an essential role in the signaling of various cytokines and are implicated in the pathogenesis of inflammatory diseases, including RA. Consequently, JAKs have attracted significant attention in recent years as therapeutic targets of RA. In the current study, we explored the role of a set of biomolecules from marine sources that could be used as specific inhibitors of JAKs and treat arthritis. The binding affinity of these molecules including astaxanthin (ATX), fucoxanthin (FX), fuscoside E (FsE), fucosterol (Fs), and phlorofucofuroeckol (PFFE) JAK3 has been analyzed. In addition, the details of relative structural interactions have been compared to those of the recently Food and Drug Administration-approved inhibitor, tofacitinib. Interestingly, some of these marine biomolecules showed a higher binding energy (b.e.) and specific binding to JAK3 active/potential sites when compared to the approved inhibitors. For instance, FsE binds to two key regulator residues of JAK3 required for its activity and for inhibitor stability, CYS909 and LYS905, with higher b.e. (-9.6) than the approved inhibitors. Thus, FsE may have a potential inhibitory action on JAKs and especially on JAK3. Additionally, PFFE can bind to several kinase critical regulators of JAK3 and the b.e. may reach -10.7. Based on the evaluation of oral availability, drug-likeness, pharmacokinetics, and medicinal chemistry friendliness, FsE seems to be the most appropriate potential inhibitor for JAK3.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"12 1-4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72530151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Taking Power, Telling Stories: Using Collaborative Autoethnography to Explore Transitions to Adulthood with and without Disability Identities","authors":"Lauren Hislop, K. Davies, Shaylie Pryer","doi":"10.16993/sjdr.915","DOIUrl":"https://doi.org/10.16993/sjdr.915","url":null,"abstract":"","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67470311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Ayouni, Mohamed Maddeh, Shaha T. Al-Otaibi, M. Alazzam, Nazik Alturki, Fahima Hajjej
An Internet of Things-based automated patient condition monitoring and detection system is discussed and built in this work. The proposed algorithm that underpins the smart-bed system is based on deep learning. The movement and posture of the patient’s body may be determined with the help of wearable sensor-based devices. In this work, an internet protocol camera device is used for monitoring the smart bed, and sensor data from five key points of the smart bed are core components of our approach. The Mask Region Convolutional Neural Network approach is used to extract data from many important areas from the body of the patient by collecting data from sensors. The distance and the time threshold are used to identify motions as being either connected with normal circumstances or uncomfortable ones. The information from these key locations is also utilised to establish the postures in which the patient is lying in while they are being treated on the bed. The patient’s body motion and bodily expression are constantly monitored for any discomfort if present. The results of the experiments demonstrate that the suggested system is valuable since it achieves a true-positive rate of 95% while only yielding a false-positive rate of 4%.
{"title":"Development of a Smart Hospital Bed Based on Deep Learning to Monitor Patient Conditions","authors":"S. Ayouni, Mohamed Maddeh, Shaha T. Al-Otaibi, M. Alazzam, Nazik Alturki, Fahima Hajjej","doi":"10.57197/jdr-2023-0017","DOIUrl":"https://doi.org/10.57197/jdr-2023-0017","url":null,"abstract":"An Internet of Things-based automated patient condition monitoring and detection system is discussed and built in this work. The proposed algorithm that underpins the smart-bed system is based on deep learning. The movement and posture of the patient’s body may be determined with the help of wearable sensor-based devices. In this work, an internet protocol camera device is used for monitoring the smart bed, and sensor data from five key points of the smart bed are core components of our approach. The Mask Region Convolutional Neural Network approach is used to extract data from many important areas from the body of the patient by collecting data from sensors. The distance and the time threshold are used to identify motions as being either connected with normal circumstances or uncomfortable ones. The information from these key locations is also utilised to establish the postures in which the patient is lying in while they are being treated on the bed. The patient’s body motion and bodily expression are constantly monitored for any discomfort if present. The results of the experiments demonstrate that the suggested system is valuable since it achieves a true-positive rate of 95% while only yielding a false-positive rate of 4%.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80249592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hadeel Alsolai, F. Al-Wesabi, Abdelwahed Motwakel, Suhanda Drar
Anomaly detection in pedestrian walkways of visually impaired people (VIP) is a vital research area that utilizes remote sensing and aids to optimize pedestrian traffic and improve flow. Researchers and engineers can formulate effective tools and methods with the power of machine learning (ML) and computer vision (CV) to identifying anomalies (i.e. vehicles) and mitigate potential safety hazards in pedestrian walkways. With recent advancements in ML and deep learning (DL) areas, authors have found that the image recognition problem ought to be devised as a two-class classification problem. Therefore, this manuscript presents a new sine cosine algorithm with deep learning-based anomaly detection in pedestrian walkways (SCADL-ADPW) algorithm. The proposed SCADL-ADPW technique identifies the presence of anomalies in the pedestrian walkways on remote sensing images. The SCADL-ADPW techniques focus on the identification and classification of anomalies, i.e. vehicles in the pedestrian walkways of VIP. To accomplish this, the SCADL-ADPW technique uses the VGG-16 model for feature vector generation. In addition, the SCA approach is designed for the optimal hyperparameter tuning process. For anomaly detection, the long short-term memory (LSTM) method can be exploited. The experimental results of the SCADL-ADPW technique are studied on the UCSD anomaly detection dataset. The comparative outcomes stated the improved anomaly detection results of the SCADL-ADPW technique.
{"title":"Assisting Visually Impaired People Using Deep Learning-based Anomaly Detection in Pedestrian Walkways for Intelligent Transportation Systems on Remote Sensing Images","authors":"Hadeel Alsolai, F. Al-Wesabi, Abdelwahed Motwakel, Suhanda Drar","doi":"10.57197/jdr-2023-0021","DOIUrl":"https://doi.org/10.57197/jdr-2023-0021","url":null,"abstract":"Anomaly detection in pedestrian walkways of visually impaired people (VIP) is a vital research area that utilizes remote sensing and aids to optimize pedestrian traffic and improve flow. Researchers and engineers can formulate effective tools and methods with the power of machine learning (ML) and computer vision (CV) to identifying anomalies (i.e. vehicles) and mitigate potential safety hazards in pedestrian walkways. With recent advancements in ML and deep learning (DL) areas, authors have found that the image recognition problem ought to be devised as a two-class classification problem. Therefore, this manuscript presents a new sine cosine algorithm with deep learning-based anomaly detection in pedestrian walkways (SCADL-ADPW) algorithm. The proposed SCADL-ADPW technique identifies the presence of anomalies in the pedestrian walkways on remote sensing images. The SCADL-ADPW techniques focus on the identification and classification of anomalies, i.e. vehicles in the pedestrian walkways of VIP. To accomplish this, the SCADL-ADPW technique uses the VGG-16 model for feature vector generation. In addition, the SCA approach is designed for the optimal hyperparameter tuning process. For anomaly detection, the long short-term memory (LSTM) method can be exploited. The experimental results of the SCADL-ADPW technique are studied on the UCSD anomaly detection dataset. The comparative outcomes stated the improved anomaly detection results of the SCADL-ADPW technique.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"84 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88498006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite the current terminology debate, little is known about the terminology experiences of people with disabilities and their relatives. Therefore, their interviews and letters to editors about disability terminology experiences published in Dutch newspapers between 1950 and 2020 were examined using inductive qualitative analysis. Three themes were derived. Contributors (1) objected to the use of particular terms and explained why a change in disability terminology was required; (2) argued that a change in disability terminology was viable; and (3) opposed proposed terminological changes. Contributors stated that derogatory and outmoded terms did not accurately depict the abilities of people with disabilities, resulting in stigmatisation and exclusion. Few contributors addressed a cross-disability perspective, and there was no mention of disability policy in the terminology debate. Meaningful associations between disability terminology experiences and the visibility and onset of the disability could be established. The newspaper contributions reflected the growing self-awareness of people with disabilities and their relatives.
{"title":"Layers of Disability Terminology Experiences of People with Disabilities and their Relatives: An Analysis of Dutch Newspapers between 1950–2020","authors":"Aartjan Ter Haar, S. Hilberink, A. Schippers","doi":"10.16993/sjdr.1000","DOIUrl":"https://doi.org/10.16993/sjdr.1000","url":null,"abstract":"Despite the current terminology debate, little is known about the terminology experiences of people with disabilities and their relatives. Therefore, their interviews and letters to editors about disability terminology experiences published in Dutch newspapers between 1950 and 2020 were examined using inductive qualitative analysis. Three themes were derived. Contributors (1) objected to the use of particular terms and explained why a change in disability terminology was required; (2) argued that a change in disability terminology was viable; and (3) opposed proposed terminological changes. Contributors stated that derogatory and outmoded terms did not accurately depict the abilities of people with disabilities, resulting in stigmatisation and exclusion. Few contributors addressed a cross-disability perspective, and there was no mention of disability policy in the terminology debate. Meaningful associations between disability terminology experiences and the visibility and onset of the disability could be established. The newspaper contributions reflected the growing self-awareness of people with disabilities and their relatives.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67468383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hadeel Alsolai, F. Al-Wesabi, Abdelwahed Motwakel, Suhanda Drar
Deep learning technique has been efficiently used for assisting visually impaired people in different tasks and enhancing total accessibility. Designing a vision-based anomaly detection method on surveillance video specially developed for visually challenged people could considerably optimize awareness and safety. While it is a complex process, there is potential to construct a system by leveraging machine learning and computer vision algorithms. Anomaly detection in surveillance video is a tedious process because of the uncertain definition of abnormality. In the complicated surveillance scenario, the types of abnormal events might co-exist and are numerous, like long-term abnormal activities, motion and appearance anomaly of objects, etc. Conventional video anomaly detection techniques could not identify this kind of abnormal action. This study designs an Improved Chicken Swarm Optimizer with Vision-based Anomaly Detection (ICSO-VBAD) on surveillance videos technique for visually challenged people. The purpose of the ICSO-VBAD technique is to identify and classify the occurrence of anomalies for assisting visually challenged people. To obtain this, the ICSO-VBAD technique utilizes the EfficientNet model to produce a collection of feature vectors. In the ICSO-VBAD technique, the ICSO algorithm was exploited for the hyperparameter tuning of the EfficientNet model. For the identification and classification of anomalies, the adaptive neuro fuzzy inference system model was utilized. The simulation outcome of the ICSO-VBAD system was tested on benchmark datasets and the results pointed out the improvements of the ICSO-VBAD technique compared to recent approaches with respect to different measures.
{"title":"Improved Chicken Swarm Optimizer with Vision-based Anomaly Detection on Surveillance Videos for Visually Challenged People","authors":"Hadeel Alsolai, F. Al-Wesabi, Abdelwahed Motwakel, Suhanda Drar","doi":"10.57197/jdr-2023-0024","DOIUrl":"https://doi.org/10.57197/jdr-2023-0024","url":null,"abstract":"Deep learning technique has been efficiently used for assisting visually impaired people in different tasks and enhancing total accessibility. Designing a vision-based anomaly detection method on surveillance video specially developed for visually challenged people could considerably optimize awareness and safety. While it is a complex process, there is potential to construct a system by leveraging machine learning and computer vision algorithms. Anomaly detection in surveillance video is a tedious process because of the uncertain definition of abnormality. In the complicated surveillance scenario, the types of abnormal events might co-exist and are numerous, like long-term abnormal activities, motion and appearance anomaly of objects, etc. Conventional video anomaly detection techniques could not identify this kind of abnormal action. This study designs an Improved Chicken Swarm Optimizer with Vision-based Anomaly Detection (ICSO-VBAD) on surveillance videos technique for visually challenged people. The purpose of the ICSO-VBAD technique is to identify and classify the occurrence of anomalies for assisting visually challenged people. To obtain this, the ICSO-VBAD technique utilizes the EfficientNet model to produce a collection of feature vectors. In the ICSO-VBAD technique, the ICSO algorithm was exploited for the hyperparameter tuning of the EfficientNet model. For the identification and classification of anomalies, the adaptive neuro fuzzy inference system model was utilized. The simulation outcome of the ICSO-VBAD system was tested on benchmark datasets and the results pointed out the improvements of the ICSO-VBAD technique compared to recent approaches with respect to different measures.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89269623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The usage of radiological investigations is increasing rapidly in Saudi Arabia. It has been estimated that 7.1% of the populace in the Kingdom of Saudi Arabia is disabled. Out of 32.94 million citizens, 1,445,723 (52.2% males and 47.8% females) millions are considered disabled. Disabled individuals are frequently undergoing medical imaging procedures, and there are not enough studies regarding the risk of radiation exposure to disabled patients from these machines. This study aims to quantify the frequency of medical procedures and estimate the collective dose for disabled individuals to predict the overall cancer risk from medical exposure. A total of 108 computed tomography (CT) procedures were carried out for disabled patients. The procedures include the brain, chest, abdomen, pelvis, and cervical spine. A 128-slice CT machine was used in this study Philips Ingenuity (Philips, Netherlands). The CT machine is subjected to regular quality control tests to ensure compliance with national recommendations. In this study, 108 [11 (10.2%) females and 97 (89.8%) males] CT procedures were carried out for disabled patients at the radiology department, King Khalid Hospital and Prince Sultan Center. The average and standard deviation radiation dose per CT procedure [DLP (mGy.cm)] for the brain, chest, abdomen, pelvis, and cervical spine were 1183.4 ± 187, 352.8 ± 88, 654 ± 73, 803 ± 800, and 527 ± 186, respectively. The estimated cancer risk is 1 cancer per 1000 to 10,000 CT procedures. Patient doses are comparable with those of previous studies carried out for normal patients. However, the protection of disabled patients from unnecessary radiation exposure is crucial to reduce the projected radiation risks and minimize the number of repeated CT scans and unproductive radiation exposure.
{"title":"Assessment of the Radiation Exposure and Cancer Risks of Disabled People Undergoing Different Computed Tomography Scans","authors":"A. Sulieman, M. Almuwannis","doi":"10.57197/jdr-2023-0014","DOIUrl":"https://doi.org/10.57197/jdr-2023-0014","url":null,"abstract":"The usage of radiological investigations is increasing rapidly in Saudi Arabia. It has been estimated that 7.1% of the populace in the Kingdom of Saudi Arabia is disabled. Out of 32.94 million citizens, 1,445,723 (52.2% males and 47.8% females) millions are considered disabled. Disabled individuals are frequently undergoing medical imaging procedures, and there are not enough studies regarding the risk of radiation exposure to disabled patients from these machines. This study aims to quantify the frequency of medical procedures and estimate the collective dose for disabled individuals to predict the overall cancer risk from medical exposure. A total of 108 computed tomography (CT) procedures were carried out for disabled patients. The procedures include the brain, chest, abdomen, pelvis, and cervical spine. A 128-slice CT machine was used in this study Philips Ingenuity (Philips, Netherlands). The CT machine is subjected to regular quality control tests to ensure compliance with national recommendations. In this study, 108 [11 (10.2%) females and 97 (89.8%) males] CT procedures were carried out for disabled patients at the radiology department, King Khalid Hospital and Prince Sultan Center. The average and standard deviation radiation dose per CT procedure [DLP (mGy.cm)] for the brain, chest, abdomen, pelvis, and cervical spine were 1183.4 ± 187, 352.8 ± 88, 654 ± 73, 803 ± 800, and 527 ± 186, respectively. The estimated cancer risk is 1 cancer per 1000 to 10,000 CT procedures. Patient doses are comparable with those of previous studies carried out for normal patients. However, the protection of disabled patients from unnecessary radiation exposure is crucial to reduce the projected radiation risks and minimize the number of repeated CT scans and unproductive radiation exposure.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90481963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Maashi, M. Al-Hagery, Mohammed Rizwanullah, A. Osman
Visual impairment affects the major population of the world, and impaired vision people need assistance for their day-to-day activities. With the enormous growth and usage of new technologies, various devices were developed to help them with object identification in addition to navigation in the indoor and outdoor surroundings. Gesture detection and classification for blind people aims to develop technologies to assist those people to navigate their surroundings more easily. To achieve this goal, using machine learning and computer vision techniques is a better solution to classify and detect hand gestures. Such methods are utilized for finding the shape, position, and movement of the hands in real-time. With this motivation, this article presents a robust gesture recognition and classification using growth optimizer with deep stacked autoencoder (RGRC-GODSAE) model for visually impaired persons. The goal of the RGRC-GODSAE technique lies in the accurate recognition and classification of gestures to assist visually impaired persons. The RGRC-GODSAE technique follows the Gabor filter approach at the initial stage to remove noise. In addition, the RGRC-GODSAE technique uses the ShuffleNet model as a feature extractor and the GO algorithm as a hyperparameter optimizer. Finally, the deep stacked autoencoder model is exploited for the automated recognition and classification of gestures. The experimental validation of the RGRC-GODSAE technique is carried out on the benchmark dataset. The extensive comparison study showed better gesture recognition performance of the RGRC-GODSAE technique over other deep learning models.
{"title":"Robust Gesture Recognition and Classification for Visually Impaired Persons Using Growth Optimizer with Deep Stacked Autoencoder","authors":"M. Maashi, M. Al-Hagery, Mohammed Rizwanullah, A. Osman","doi":"10.57197/jdr-2023-0029","DOIUrl":"https://doi.org/10.57197/jdr-2023-0029","url":null,"abstract":"Visual impairment affects the major population of the world, and impaired vision people need assistance for their day-to-day activities. With the enormous growth and usage of new technologies, various devices were developed to help them with object identification in addition to navigation in the indoor and outdoor surroundings. Gesture detection and classification for blind people aims to develop technologies to assist those people to navigate their surroundings more easily. To achieve this goal, using machine learning and computer vision techniques is a better solution to classify and detect hand gestures. Such methods are utilized for finding the shape, position, and movement of the hands in real-time. With this motivation, this article presents a robust gesture recognition and classification using growth optimizer with deep stacked autoencoder (RGRC-GODSAE) model for visually impaired persons. The goal of the RGRC-GODSAE technique lies in the accurate recognition and classification of gestures to assist visually impaired persons. The RGRC-GODSAE technique follows the Gabor filter approach at the initial stage to remove noise. In addition, the RGRC-GODSAE technique uses the ShuffleNet model as a feature extractor and the GO algorithm as a hyperparameter optimizer. Finally, the deep stacked autoencoder model is exploited for the automated recognition and classification of gestures. The experimental validation of the RGRC-GODSAE technique is carried out on the benchmark dataset. The extensive comparison study showed better gesture recognition performance of the RGRC-GODSAE technique over other deep learning models.","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75157095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Inclusion Opportunities of Work 4.0? Employment Realities of People with Disabilities in Germany","authors":"Jan Jochmaring, Jana York","doi":"10.16993/sjdr.896","DOIUrl":"https://doi.org/10.16993/sjdr.896","url":null,"abstract":"","PeriodicalId":46073,"journal":{"name":"Scandinavian Journal of Disability Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67470409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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