Search results for: multiple disabilities

Authors: Aodai Abdul-Illah Ismail

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Even though the dramatic progress that has been made in traffic safety, but still millions of peoples get killed or injured as a result of traffic crashes, besides the huge amount of economic losses due to these crashes. So traffic safety continues to be one of the most important serious issues worldwide, and it affects everyone who uses the road network system, whether you drive, walk, cycle, or push a pram. One of the most important sides that offers promise for further progress in relation to traffic safety is related to risky groups (special population groups) who may have higher potential to be involved in accidents. Traffic safety needs of risky groups are different from each other and also from the average population. Due to the various limitations between these special groups from each other and from the average population, it is not possible to address all the issues –at the same time- raising the importance ranking among the other safety issues. This paper explains a procedure used to identify the most critical traffic safety issues of five risky groups, which include younger, older and female drivers, people with disabilities and school aged children. Multi criteria used in selecting the critical issues because the single criteria is not sufficient. Highway safety professionals were surveyed to obtain the ranking of importance among the risky groups and then to develop the final ranking among issues by applying weight for each of the criteria.

Keywords: traffic safety, risky groups, old drivers, young drivers

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Authors: Pooja Khanal, Huaming Zhang

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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn will result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers, and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision according to Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this paper, we propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method shows better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: handover, HetNets, interference, MADM, small cells, TOPSIS, weight

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

Procedia PDF Downloads 139

Authors: Justin Orimisan Ijigbade

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The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.

Keywords: climate variability, honeybees production, humidity, rainfall and temperature

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Authors: Yoonjung An, Yongtae Park

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Offering a Product-Service System (PSS) is a well-accepted strategy that companies may adopt to provide a set of systemic solutions to customers. PSSs were initially provided in a simple form but now take diversified and complex forms involving multiple services, products and technologies. With the growing interest in the PSS, frameworks for the PSS development have been introduced by many researchers. However, most of the existing frameworks fail to examine various relations existing in a complex PSS. Since designing a complex PSS involves full integration of multiple products and services, it is essential to identify not only product-service relations but also product-product/ service-service relations. It is also equally important to specify how they are related for better understanding of the system. Moreover, as customers tend to view their purchase from a more holistic perspective, a PSS should be developed based on the whole system’s requirements, rather than focusing only on the product requirements or service requirements. Thus, we propose a framework to develop a complex PSS that is coordinated fully with the requirements of both worlds. Specifically, our approach adopts a multi-domain matrix (MDM). A MDM identifies not only inter-domain relations but also intra-domain relations so that it helps to design a PSS that includes highly desired and closely related core functions/ features. Also, various dependency types and rating schemes proposed in our approach would help the integration process.

Keywords: inter-domain relations, intra-domain relations, multi-domain matrix, product-service system design

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Huafeng Wei

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Dementia in Alzheimer’s Disease (AD) is the number one cause of dementia internationally, without effective treatments. Increasing evidence suggest that disruption of intracellular calcium homeostasis, primarily pathological elevation of cytosol and mitochondria but reduction of endoplasmic reticulum (ER) calcium concentrations, play critical upstream roles on multiple pathologies and associated neurodegeneration, impaired neurogenesis, synapse, and cognitive dysfunction in various AD preclinical studies. The last federal drug agency (FDA) approved drug for AD dementia treatment, memantine, exert its therapeutic effects by ameliorating N-methyl-D-aspartate (NMDA) glutamate receptor overactivation and subsequent calcium dysregulation. More research works are needed to develop other drugs targeting calcium dysregulation at multiple pharmacological acting sites for future effective AD dementia treatment. Particularly, calcium channel blockers for the treatment of hypertension and dantrolene for the treatment of muscle spasm and malignant hyperthermia can be repurposed for this purpose. In our own research work, intranasal administration of dantrolene significantly increased its brain concentrations and durations, rendering it a more effective therapeutic drug with less side effects for chronic AD dementia treatment. This review summarizesthe progress of various studies repurposing drugs targeting calcium dysregulation for future effective AD dementia treatment as potentially disease-modifying drugs.

Keywords: alzheimer, calcium, cognitive dysfunction, dementia, neurodegeneration, neurogenesis

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Szymon Kowieski, Zygmunt Mikno

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The study involved the optimization of process parameters during resistance spot welding of Al-coated martensitic boron steel 22MnB5, applied in hot stamping, performed using a programme with a multiple current impulse mode and a programme with variable pressure force. The aim of this research work was to determine the possibilities of a growth in welded joint strength and to identify the expansion of a welding lobe. The process parameters were adjusted on the basis of welding process simulation and confronted with experimental data. 22MnB5 steel is known for its tendency to obtain high hardness values in weld nuggets, often leading to interfacial failures (observed in the study-related tests). In addition, during resistance spot welding, many production-related factors can affect process stability, e.g. welding lobe narrowing, and lead to the deterioration of quality. Resistance spot welding performed using the above-named welding programme featuring 3 levels of force made it possible to achieve 82% of welding lobe extension. Joints made using the multiple current impulse program, where the total welding time was below 1.4s, revealed a change in a peeling mode (to full plug) and an increase in weld tensile shear strength of 10%.

Keywords: 22MnB5, hot stamping, interfacial fracture, resistance spot welding, simulation, single lap joint, welding lobe

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Authors: W. Mughees, M. Alahmad

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Water is the most significant entity that controls local and global development. For the Gulf region, especially Saudi Arabia, with its limited potable water resources, the potential of the fresh water problem is highly considerable. In this research, the study involves the design and analysis of pinch-based water/wastewater networks. Multiple water/wastewater networks were developed using pinch analysis involving direct recycle/material recycle method. Property-integration technique was adopted to carry out direct recycle method. Particularly, a petroleum refinery was considered as a case study. In direct recycle methodology, minimum water discharge and minimum fresh water resource targets were estimated. Re-design (or retrofitting) of water allocation in the networks was undertaken. Chemical Oxygen Demand (COD) and hardness properties were taken as pollutants. This research was based on single and double contaminant approach for COD and hardness and the amount of fresh water was reduced from 340.0 m3/h to 149.0 m3/h (43.8%), 208.0 m3/h (61.18%) respectively. While regarding double contaminant approach, reduction in fresh water demand was 132.0 m3/h (38.8%). The required analysis was also carried out using mathematical programming technique. Operating software such as LINGO was used for these studies which have verified the graphical method results in a valuable and accurate way. Among the multiple water networks, the one possible water allocation network was developed based on mass exchange.

Keywords: minimization, water pinch, water management, pollution prevention

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Authors: Badriah Alayidi, Emad Alyahya

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Background: Most people with Multiple Sclerosis (MS) report worsening balance as the condition progresses. Poor balance control is also well known to be a significant risk factor for both falling and fear of falling. The increased risk of falls with disease progression thus makes balance control an essential target of gait rehabilitation amongst people with MS. Intervention programs have developed various methods to improve balance control, and accumulating evidence suggests that exercise programs may help people with MS improve their balance. Among these methods, virtual reality (VR) is growing in popularity as a balance-training technique owing to its potential benefits, including better compliance and greater user happiness. However, it is not clear if a VR environment will induce different balance control mechanisms in MS as compared to healthy individuals or traditional environments. Therefore, this study aims to examine how individuals with MS control their balance in a VR setting. Methodology: The proposed study takes an empirical approach to estimate and determine the role of balance response in persons with MS using a VR environment. It will use primary data collected through patient observations, physiological and biomechanical evaluation of balance, and data analysis. Results: The preliminary systematic review and meta-analysis indicated that there was variability in terms of the outcome assessing balance response in people with MS. The preliminary results of these assessments have the potential to provide essential indicators of the progression of MS and contribute to the individualization of treatment and evaluation of the interventions’ effectiveness. The literature describes patients who have had the opportunity to experiment in VR settings and then used what they have learned in the real world, suggesting that this VR setting could be more appealing than conditional settings. The findings of the proposed study will be beneficial in estimating and determining the effect of VR on balance control in persons with MS. In previous studies, VR was shown to be an interesting approach to neurological rehabilitation, but more data are needed to support this approach in MS. Conclusions: The proposed study enables an assessment of balance and evaluations of a variety of physiological implications related to neural activity as well as biomechanical implications related to movement analysis.

Keywords: multiple sclerosis, virtual reality, postural control, balance

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Authors: Oscar Norman Nekesa, Yoshitaka Kajita

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Tom Mboya Street is a vital urban corridor within the spectrum of Nairobi city, it experiences high volumes of pedestrian and vehicular traffic. Despite past intervention measures to lessen this catastrophe, rates have remained high. This highlights significant safety concerns that need urgent attention. This study investigates the correlation and pedestrian accident predictability with significant independent variables using multiple linear regression to model to develop effective mobility management strategies for accident mitigation. The methodology involves collecting and analyzing data on pedestrian accidents and various related independent variables. Data sources include the National Transport and Safety Authority (NTSA), Kenya National Bureau of Statistics, and Nairobi City County records, covering five years. This study aims to investigate that traffic volumes (pedestrian and vehicle), Vehicular speed, human factors, illegal parking, policy issues, urban-land use, built environment, traffic signals conditions, inadequate lighting, and insufficient traffic control measures significantly have predictability with the rate of pedestrian accidents. Explanatory variables related to road design and geometry are significant in predictor models for the Tom Mboya Road link but less influential in junction along the 5 km stretch road models. The most impactful variable across all models was vehicular traffic flow. The study recommends infrastructural improvements, enhanced enforcement, and public awareness campaigns to reduce accidents and improve urban mobility. These insights can inform policy-making and urban planning to enhance pedestrian safety along the dense packed Tom Mboya Street and similar urban settings. The findings will inform evidence-based interventions to enhance pedestrian safety and improve urban mobility.

Keywords: multiple linear regression, urban mobility, traffic management, Nairobi, Tom Mboya street, infrastructure conditions., pedestrian safety, correlation and prediction

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Authors: Anitha Naittee Abraham, N. Sreedevi

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Individuals with Down syndrome (DS) have relatively better expressive language compared to other individuals with intellectual disabilities. Reduced speech intelligibility is one of the major concerns of this group of individuals due to their anatomical and physiological differences. The study investigated the vowel articulation of Malayalam speaking children with DS in the age range of 5-10 years. The vowel production of 10 children with DS was compared with typically developing children in the same age range. Vowels were extracted from 3 words with the corner vowels /a/, /i/ and /u/ in the word-initial position, using Praat (version 5.3.23) software. Acoustic analysis was based on vowel space area (VSA), Formant centralization ration (FCR) and F2i/F2u. The findings revealed increased formant values for the control group except for F2a and F2u. Also, the experimental group had higher FCR, lower VSA, and F2i/F2u values suggestive of imprecise vowel articulation due to restricted tongue movements. The results of the independent t-test revealed a significant difference in F1a, F2i, F2u, VSA, FCR and F2i/F2u values between the experimental and control group. These findings support the fact that children with DS have imprecise vowel articulation that interferes with the overall speech intelligibility. Hence it is essential to target the oromotor skills to enhance the speech intelligibility which in turn benefit in the social and vocational domains of these individuals.

Keywords: Down syndrome, FCR, vowel articulation, vowel space

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Authors: Puteri Zarina M. K., Haddi J. K., Zolkepli N., Shu M. H. B., Hosshan H., Saad M. A.

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This paper provides an overview of the current state of ESL instruction for children with autism in Malaysia. Equal rights, independence, and active participation are guaranteed by the 2006 Convention on the Rights of Persons with Disabilities. Every child is entitled to receive education in an inclusive atmosphere that embraces diversity and ensures equal opportunity for all. The primary objective of the research was to investigate if English as a Second Language (ESL) teachers employ distinct instructional methods and strategies while teaching children diagnosed with autism. Moreover, the objective was to assess the similarities in the challenges faced by teachers when teaching ESL to children with autism in Malaysia. The study aimed to increase understanding of the challenges faced by ESL teachers in teaching autistic students. The study was structured as a qualitative research endeavour. A total of twelve (12) ESL teachers from selected primary schools in Malaysia were involved in this study. The research findings accurately depict the actual state of teaching ESL to autistic children. They confirm the imperative need for additional support in order to facilitate the successful integration of these children into the educational system.

Keywords: autism spectrum disorder, ESL, inclusion, Malaysia, special educational needs

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Authors: Nail Nazarov, Vladimir Zobov, Alexandra Vyshtakalyuk, Vyacheslav Semenov, Irina Galyametdinova, Vladimir Reznik

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There have been studied effects of xymedon and six new pyrimidine derivatives, that are close and distant analogs of xymedon, on rats' working capacity in the test 'swimming to failure'. It has been shown that a single administration of the studied compounds did not have a statistically significant effect in the test. In the conditions of multiple intraperitoneal administration of the studied pyrimidine derivatives, the compound L-ascorbate, 1-(2-hydroxyethyl)-4.6-dimethyl-1.2-dihydropyrimidine-2-one had the lowest toxicity and the most pronounced actoprotective effect. Introduction in the dose of 20 mg/kg caused a statistically significant increase 440 % in the duration of swimming of rats on the 14th day of the experiment compared with the control group. Multiple administration of the compound in the conditions of physical load did not affect leucopoiesis but stimulates erythropoiesis resulting in an increase in the number of erythrocytes and a hemoglobin level. The substance introduction under mixed exhausting loads prevented such changes of blood biochemical parameters as reduction of glucose, increased of urea and lactic acid levels, what indicates improvement in the animals' tolerability of loads and an anti-catabolic effect of the compound. Absence of hepato and cardiotoxic effects of the substance has been shown. This work was performed with the financial support of Russian Science Foundation (grant № 14-50-00014).

Keywords: actoprotectors, physical working capacity, pyrimidine derivatives, xymedon

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Authors: A. Bruce Janati, Muhammad Umair Khan, Naif Alghassab, Ibrahim Alzeir, Assem Mahmoud, M. Sammour

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Rationale: Lennox-Gastaut syndrome(LGS) is an electro-clinical syndrome composed of the triad of mental retardation, multiple seizure types, and the characteristic generalized slow spike-wave complexes in the EEG. In this article, we report on two patients with LGS whose brain MRI showed dysgenesis of corpus callosum(CC). We review the literature and stress the role of CC in the genesis of secondary bilateral synchrony(SBS). Method: This was a clinical study conducted at King Khalid Hospital. Results: The EEG was consistent with LGS in patient 1 and unilateral slow spike-wave complexes in patient 2. The MRI showed hypoplasia of the splenium of CC in patient 1, and global hypoplasia of CC combined with Joubert syndrome in patient 2. Conclusion: Based on the data, we proffer the following hypotheses: 1-Hypoplasia of CC interferes with functional integrity of this structure. 2-The genu of CC plays a pivotal role in the genesis of secondary bilateral synchrony. 3-Electrodecremental seizures in LGS emanate from pacemakers generated in the brain stem, in particular the mesencephalon projecting abnormal signals to the cortex via thalamic nuclei. 4-Unilateral slow spike-wave complexes in the context of mental retardation and multiple seizure types may represent a variant of LGS, justifying neuroimaging studies.

Keywords: EEG, Lennox-Gastaut syndrome, corpus callosum , MRI

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Diana Serbezeanu, Ionela-Daniela Carja, Tachita Vlad-Bubulac, Sergiu Sova

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New phosphorus-containing monomers having methoxy end functional groups were prepared from methyl 4-hydroxybenzoate and two different dichlorides with phosphorus, namely phenyl phosphonic dichloride and phenyl dichlorophosphate. The structures of the monomers were confirmed by FTIR and NMR spectroscopy. The assignments for the 1H, 13C and 31P chemical shifts are based on 1D and 2D NMR homo- and heteronuclear correlations (H,H-COSY (Correlation Spectroscopy), H,C-HMQC (Heteronuclear Multiple Quantum Correlation and H,C-HMBC (Heteronuclear Multiple Bond Correlation)) and 31P-13C couplings. The monomers exhibited good solubility in common organic solvents. Dimethyl sulfoxide was to be a good solvent to grow crystals of considerable size which were investigated by X-ray analysis. One of these two new monomers presented thermotropic liquid crystalline behaviour, as revealed by differential scanning calorimetry (DSC), polarized light microscopy (PLM) and X-ray diffraction (XRD). The transition temperature from crystal to liquid crystalline state (K→LC) was 143°C and from the LC to isotropic state (LC→I) was 167°C. Upon heating, bis(4-(methoxycarbonyl)phenyl formed fine textures, difficult to be ascribed to smectic or nematic phases. Upon cooling from the isotropic state, bis(4-(methoxycarbonyl)phenyl exhibited a mosaic-type texture. X-ray diffraction measurements at small angles (SAXS) of bis(4-(methoxycarbonyl)phenyl showed two peaks at 1.8 Å and 3.5 Å, respectively suggesting organization at supramolecular level.

Keywords: phosphorus-containing monomers, polarized light microscopy, structure investigation, thermotropic liquid crystalline properties

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Authors: Virgil Miranda, Gissele Mosqueda, Pablo Delgado, Yimesker Yihun

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Muscular fatigue affects the muscle activation that is needed for producing the desired clinical outcome. Integrating optimal muscle relaxation periods into a variety of health care rehabilitation protocols is important to maximize the efficiency of the therapy. In this study, four muscle relaxation periods (30, 60, 90, and 120 seconds) and their effectiveness in producing consistent muscle activation of the muscle biceps brachii between sets of elbow flexion and extension task was investigated among a sample of 10 subjects with no disabilities. The same resting periods were then utilized in a controlled exoskeleton-based exercise for a sample size of 5 subjects and have shown similar results. On average, the muscle activity of the biceps brachii decreased by 0.3% when rested for 30 seconds, and it increased by 1.25%, 0.76%, and 0.82% when using muscle relaxation periods of 60, 90, and 120 seconds, respectively. The preliminary results suggest that a muscle relaxation period of about 60 seconds is needed for optimal continuous muscle activation within rehabilitation regimens. Robot-based rehabilitation is good to produce repetitive tasks with the right intensity, and knowing the optimal resting period will make the automation more effective.

Keywords: rest intervals, muscle biceps brachii, robot rehabilitation, muscle fatigue

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Authors: Neda Valizadeh, Mani Mofidi, Sama Haghighi, Ali Hashemaghaee, Soudabeh Shafiee Ardestani

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Background: There are many systems and parameters to evaluate trauma patients in the emergency department. Most of these evaluations are to distinguish patients with worse conditions so that the care systems have a better prediction of condition for a better care-giving. The purpose of this study is to determine the relationship between axillary body temperature and mortality in patients hospitalized in the intensive care unit (ICU) with multiple traumas and with other clinical and para-clinical factors. Methods: All patients between 16 and 75 years old with multiple traumas who were admitted into Emergency Department then hospitalized in the ICU were included in our study. An axillary temperature in the first and the second day of admission, Glasgow cola scale (GCS), systolic blood pressure, Serum glucose levels, and white blood cell counts of all patients at the admission day were recorded and their relationship with mortality were analyzed by SPSS software with suitable statistical tests. Results: Axillary body temperatures in the first and second day were statistically lower in expired traumatic patients (p=0.001 and p<0,001 respectively). Patients with lower GCS had a significantly lower first-day temperature and a significantly higher mortality. (p=0.006 and p=0.006 respectively). Furthermore, the first-day axillary temperature was significantly lower in patients with a lower first-day systolic blood pressure (p=0.014). Conclusion: Our results showed that lower axillary body temperature in the first day is associated with higher mortality, lower GCS, and lower systolic blood pressure. Thus, this could be used as a predictor of mortality in evaluation of traumatic patients in emergency settings.

Keywords: fever, trauma, mortality, emergency

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Authors: Hassen Hamouda, Mohamed Ouwais Kabaou, Med Salim Bouhlel

Abstract:

The growth of wireless technology made opportunistic scheduling a widespread theme in recent research. Providing high system throughput without reducing fairness allocation is becoming a very challenging task. A suitable policy for resource allocation among users is of crucial importance. This study focuses on scheduling multiple streaming flows on the downlink of a WiMAX system based on orthogonal frequency division multiple access (OFDMA). In this paper, we take the first step in formulating and analyzing this problem scrupulously. As a result, we proposed a new scheduling scheme based on Round Robin (RR) Algorithm. Because of its non-opportunistic process, RR does not take in account radio conditions and consequently it affect both system throughput and multi-users diversity. Our contribution called MORRA (Modified Round Robin Opportunistic Algorithm) consists to propose a solution to this issue. MORRA not only exploits the concept of opportunistic scheduler but also takes into account other parameters in the allocation process. The first parameter is called courtesy coefficient (CC) and the second is called Buffer Occupancy (BO). Performance evaluation shows that this well-balanced scheme outperforms both RR and MaxSNR schedulers and demonstrate that choosing between system throughput and fairness is not required.

Keywords: OFDMA, opportunistic scheduling, fairness hierarchy, courtesy coefficient, buffer occupancy

Procedia PDF Downloads 296

Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

Abstract:

Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

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Authors: Hsin-Yi Lo, Huang-Ju Jiun, Yu-Chiao Chu

Abstract:

Hemodynamic monitoring is an important in the intensive care unit. Advances in medical technology in recent years, more diversification of intensive care equipment, there are many kinds of instruments available for monitoring of hemodynamics, Edwards Lifesciences Hemodynamic Monitoring (FloTrac) is one of them. The recent medical safety incidents in parameters were changed, nurses have not to notify doctor in time, therefore, it is hoped to analyze the current problems and find effective improvement strategies. In August 2021, the survey found that only 74.0% of FloTrac correctness of operation, reasons include lack of education, the operation manual is difficulty read, lack of audit mechanism, nurse doesn't know those numerical changes need to notify doctor, work busy omission, unfamiliar with operation and have many nursing records then omissions. Improvement methods include planning professional nurse education, formulate the secret arts of FloTrac, enacting an audit mechanism, establish FloTrac action learning, make「follow the sun」care map, hold simulated training and establish monitoring data automatically upload nursing records. After improvement, FloTrac correctness of operation increased to 98.8%. The results are good, implement to the ICU of the hospital.

Keywords: hemodynamic monitoring, edwards lifesciences hemodynamic monitoring, multiple strategies, intensive care

Procedia PDF Downloads 79

Authors: Chuanzhi Chen, Wenjing Yu

Abstract:

Parabolic cylindrical deployable antenna has the characteristics of wide cutting width, strong directivity, high gain, and easy automatic beam scanning. While, due to its large size, high flexibility, and strong coupling, the deployment process of parabolic cylindrical deployable antenna presents such problems as unsynchronized deployment speed, large local deformation and discontinuous switching of deployment state. A large deployable parabolic cylindrical antenna is taken as the research object, and the problem of unfolding process instability of cylindrical antenna is studied in the paper, which is caused by multiple factors such as multiple closed loops, elastic deformation, motion friction, and gap collision. Firstly, the multi-flexible system dynamics model of large-scale parabolic cylindrical antenna is established to study the influence of friction and elastic deformation on the stability of large multi-closed loop antenna. Secondly, the evaluation method of antenna expansion stability is studied, and the quantitative index of antenna configuration design is proposed to provide a theoretical basis for improving the overall performance of the antenna. Finally, through simulation analysis and experiment, the development dynamics and stability of large-scale parabolic cylindrical antennas are verified by in-depth analysis, and the principles for improving the stability of antenna deployment are summarized.

Keywords: multibody dynamics, expandable parabolic cylindrical antenna, stability, flexible deformation

Procedia PDF Downloads 142

Authors: H. N. Cheung

Abstract:

Self-compassion encourages one to accept oneself, reduce self-criticism and self-judgment, and see one’s shortcomings and setbacks in a balanced view. Adolescent self-compassion is a crucial protective factor against mental illness. It is, however, affected by gender. Given the scarcity of self-compassion scales for adolescents, the current study evaluates the Self-Compassion Scale for Youth (SCS-Y) in a large cross-cultural sample and investigates how the subscales of SCS-Y relate to the dimensions of depressive symptoms across gender. Through the internet-based Qualtrics, a total of 2881 teenagers aged 12 to 18 years were recruited from Hong Kong (HK), China, and the United Kingdom. A Multiple Indicator Multiple Cause (MIMIC) model was used to evaluate measurement invariance of the SCS-Y, and differential item functioning (DIF) was checked across gender. Upon the establishment of the best model, a multigroup structural equation model (SEM) was built between factors of SCS-Y and Multidimensional depression assessment scale (MDAS) which assesses four dimensions of depressive symptoms (emotional, cognitive, somatic and interpersonal). The SCS-Y was shown to have good reliability and validity. The MIMIC model produced a good model fit for a hypothetical six-factor model (CFI = 0.980; TLI = 0.974; RMSEA = 0.038) and no item was flagged for DIF across gender. A gender difference was observed between SCS-Y factors and depression dimensions. Conclusions: The SCS-Y exhibits good psychometric characteristics, including measurement invariance across gender. The study also highlights the gender difference between self-compassion factors and depression dimensions.

Keywords: self compassion, gender, depression, structural equation modelling, MIMIC model

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Authors: Kearney Dover, Viviene Temple, Lynneth Stuart-Hill

Abstract:

Heart Rate Variability (HRV) is the beat-to-beat variation in adjacent heartbeats. HRV is a non-invasive measure of the autonomic nervous system (ANS) and provides information about the sympathetic (SNS) and parasympathetic (PNS) nervous systems. The HRV of a well-conditioned heart is generally high at rest, whereas low HRV has been associated with adverse outcomes/conditions, including congestive heart failure, diabetic neuropathy, depression, and hospital admissions. HRV has received very little research attention among individuals with intellectual disabilities in general or Special Olympic athletes. Purpose: 1) Having a longer post-exercise rest and recovery time to establish how long it takes for the athletes’ HRV components to return to pre-exercise levels, 2) To determine if greater familiarization with the testing processes influences HRV. Participants: Two separate samples of 10 adult Special Olympics athletes will be recruited for 2 separate studies. Athletes will be between 18 and 50 years of age and will be members of Special Olympics BC. Anticipated Findings: To answer why the Special Olympics athletes display poor cardiac responsiveness to changes in autonomic modulation during exercise. By testing the cortisol levels in the athletes, we can determine their stress levels which will then explain their measured HRV.

Keywords: 6MWT, autonomic modulation, cortisol levels, intellectual disability

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Authors: Jagadish Rao Padubidri, Mehak Bhandary, Sowmya J. Rao

Abstract:

Introduction: The significance of the human foot and its measurements in identifying an individual has been proved a lot of times by different studies in different geographical areas and its association to the stature and gender of the individual has been justified by many researches. In our study we have used different foot measurements including the length, width, malleol height and navicular height for establishing its association to stature and gender and to find out its accuracy. The purpose of this study is to show the relation of foot measurements with stature and gender, and to derive Multiple and Logistic regression equations for stature and gender estimation in South Indian population. Materials and Methods: The subjects for this study were 200 South Indian students out of which 100 were females and 100 were males, aged between 18 to 24 years. The data for the present study included the stature, foot length, foot breath, foot malleol height, foot navicular height of both right and left foot. Descriptive statistics, T-test and Pearson correlation coefficients were derived between stature, gender and foot measurements. The stature was estimated from right and left foot measurements for both male and female South Indian population using multiple regression analysis and logistic regression analysis for gender estimation. Results: The means, standard deviation, stature, right and left foot measurements and T-test in male population were higher than in females. LFL (Left foot length) is more than RFL (Right Foot length) in male groups, but in female groups the length of both foot are almost equal [RFL=226.6, LFL=227.1]. There is not much of difference in means of RFW (Right foot width) and LFW (Left foot width) in both the genders. Significant difference were seen in mean values of malleol and navicular height of right and left feet in male gender. No such difference was seen in female subjects. Conclusions: The study has successfully demonstrated the correlation of foot length in stature estimation in all the three study groups in both right and left foot. Next in parameters are Foot width and malleol height in estimating stature among male and female groups. Navicular height of both right and left foot showed poor relationship with stature estimation in both male and female groups. Multiple regression equations for both right and left foot measurements to estimate stature were derived with standard error ranging from 11-12 cm in males and 10-11 cm in females. The SEE was 5.8 when both male and female groups were pooled together. The logistic regression model which was derived to determine gender showed 85% accuracy and 92.5% accuracy using right and left foot measurements respectively. We believe that stature and gender can be estimated with foot measurements in South Indian population.

Keywords: foot length, gender, stature, South Indian

Procedia PDF Downloads 331