Search results for: individual differencesmobile computing

Authors: Rozo D. Juan Felipe, Ramírez L. Leonardo Juan, Puerta A. Gabriel Alberto

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The telemedicine services require correct computing resource management to guarantee productivity and efficiency for medical and non-medical staff. The aim of this study was to examine web management strategies to ensure the availability of resources and services in telemedicine so as to provide medical information management with an accessible strategy. In addition, to evaluate the quality-of-service parameters, the followings were measured: delays, throughput, jitter, latency, available bandwidth, percent of access and denial of services based of web management performance map with profiles permissions and database management. Through 24 different test scenarios, the results show 100% in availability of medical information, in relation to access of medical staff to web services, and quality of service (QoS) of 99% because of network delay and performance of computer network. The findings of this study suggest that the proposed strategy of web management is an ideal solution to guarantee the availability, reliability, and accessibility of medical information. Finally, this strategy offers seven user profile used at telemedicine center of Bogota-Colombia keeping QoS parameters suitable to telemedicine services.

Keywords: availability, medical information, QoS, strategy, telemedicine

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Authors: Rupali Chaudhary

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Shakespeare has been widely revisited by dramatists, critics, filmmakers and scholars around the globe. Shakespeare's kaleidoscopic work has been borrowed and redesigned into resonant patterns by artists, thus weaving myriad manifestations to pick from. Along with adaptation into wholly verbal medium (e.g., translations) the practice of indigenization through performing arts has played a great role in amplifying the reach of plays. The proliferation of Shakespeare's oeuvre commenced with the spread of colonialism itself. The plays illustrating the core values of Western tradition were introduced in the colonies. Therefore, the colonial domination extended to cultural domination. The plays were translated and adapted by the locals at times as it is and sometimes intermingled with the altered landscape and culture. The present paper discusses the global dimensions of Shakespearean cinema along with the historical cinematic shift from silent era to spoken dialogue in multiple languages. The methodology followed is descriptive in nature, and related information is availed from related literature, i.e., books, research articles and films. America and Europe dominated the silent era Shakespearean film production, thereby giving the term 'global' a less broad meaning. Five nations that dominated silent Shakespearean cinema were the United States, England, Italy, France, and Germany. Gradually the work of the exemplary figure with artistic and literary greatness surpassed the boundaries of the colonies and became a global legacy. Presently apart from English speaking nations Shakespearean films have been shot or produced in many of non-Anglophone locales. The findings indicate that when discussing about global dimensions of Shakespearean cinema various factors can be considered: involvement of actors and directors of foreign origin, transportability and universal comprehensibility of visual imagery across geographical borders, commodification of art or West's use of it as a tool of cultural hegemony or promotion of international amity, propagation of interculturalism through individual director's cultural translations and localization of Western art. Understanding of Shakespeare as a global export also depends on how an individual Shakespearean film works. Shakespeare's global appeal for cinema does not reside alone in his exquisite writings, distinctive characters, the setting, the story and the plots that have nurtured cinema since the medium's formative years. Shakespeare's global cinematic appeal is present in the spirit of cinema itself, i.e., the moving images capturing human behaviour and emotions that the plays invoke in audiences.

Keywords: adaptation, global dimensions, Shakespeare, Shakespearean cinema

Procedia PDF Downloads 120

Authors: Lily Ye

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The contemporary fashion industry has witnessed the global rise of Chinese fashion designers. China plays more and more important role in this sector globally. One of the key debates in contemporary time is the conception of Chinese fashion. A close look at previous discussions on Chinese fashion reveals that most of them are explored through the lens of cultural knowledge and assumptions, using the dichotomous models of East and West. The results of these studies generate an essentialist and orientalist notion of Chinoiserie and Chinese fashion, which sees individual designers from China as undifferential collective members marked by a unique and fixed set of cultural scripts. This study challenges this essentialist conceptualization and brings fresh insights to the discussion of Chinese fashion identity against the backdrop of globalisation. Different from a culturalist approach to researching Chinese fashion, this paper presents an alternative position to address the research agenda through the mobilisation of Giddens’ (1991) theory of reflexive identity formation, privileging individuals’ agency and reflexivity. This approach to the discussion of identity formation not only challenges the traditional view seeing identity as the distinctive and essential characteristics belonging to any given individual or shared by all members of a particular social category or group but highlights fashion designers’ strategic agency and their role as fashion activist. This study draws evidence from a textual analysis of published stories of a group of established Chinese designers such as Guo Pei, Huishan Zhang, Masha Ma, Uma Wang, and Ma Ke. In line with Giddens’ concept of 'reflexive project of the self', this study uses a narrative methodology. Narratives are verbal accounts or stories relating to experiences of Chinese fashion designers. This approach offers the fashion designers a chance to 'speak' for themselves and show the depths and complexities of their experiences. It also emphasises the nuances of identity formation in fashion designers, whose experiences cannot be captured in neat typologies. Thematic analysis (Braun and Clarke, 2006) is adopted to identify and investigate common themes across the whole dataset. At the centre of the analysis is individuals’ self-articulation of their perceptions, experiences and themselves in relation to culture, fashion and identity. The finding indicates that identity is constructed around anchors such as agency, cultural hybridity, reflexivity and sustainability rather than traditional collective categories such as culture and ethnicity. Thus, the old East-West dichotomy is broken down, and essentialised social categories are challenged by the multiplicity and fragmentation of self and cultural hybridity created within designers’ 'small narratives'.

Keywords: Chinoiserie, fashion identity, fashion activism, narrative inquiry

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Authors: Abbas Cheraghi

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A key predistribution scheme provides one method to distribute secret ahead of time. Blom’s scheme is a symmetric threshold key exchange protocol in cryptography. The scheme was proposed by the Swedish cryptographer Rolf Blom. In this kind of scheme, trusted authority gives each user a secret key and a public identifier, which enables any two users to create independently a shared key for communicating between each other. However, if an attacker can compromise the keys of at least Known numbers of users, he can break the scheme and reconstruct every shared key. In this paper generalized Blom’s Scheme by multivariate Lagrange interpolation formula. This scheme is a form of threshold secret sharing scheme. In this new scheme, the amount of information transmitted by the trusted authority is independent of the numbers of users. In addition, this scheme is unconditionally secure against any individual user.

Keywords: key predistribution, blom’s scheme, secret sharing, unconditional secure

Procedia PDF Downloads 414

Authors: Bonnie Clough, Tamara Ownsworth, Vladimir Estivill-Castro, Matt Stainer, Rene Hexel, Andrew Bulmer, Wendy Moyle, Allison Waters, David Neumann, Jayke Bennett

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The success of global vaccination programs is reliant on the uptake of vaccines to achieve herd immunity. Yet, many individuals do not obtain vaccines or venipuncture procedures when needed. Whilst health education may be effective for those individuals who are hesitant due to safety or efficacy concerns, for many of these individuals, the primary concern relates to blood or injection fear or phobia (BII). BII is highly prevalent and associated with a range of negative health impacts, both at individual and population levels. Exposure therapy is an efficacious treatment for specific phobias, including BII, but has high patient dropout and low implementation by therapists. Whilst virtual reality approaches exposure therapy may be more acceptable, they have similarly low rates of implementation by therapists and are often difficult to tailor to an individual client’s needs. It was proposed that a piloted robot may be able to adequately facilitate fear induction and be an acceptable approach to exposure therapy. The current study examined fear induction responses, acceptability, and feasibility of a piloted robot for BII exposure. A Nao humanoid robot was programmed to connect with a virtual reality head-mounted display, enabling live streaming and exploration of real environments from a distance. Thirty adult participants with BII fear were randomly assigned to robot-pilot or virtual reality exposure conditions in a laboratory-based fear exposure task. All participants also completed a computer-based two-dimensional exposure task, with an order of conditions counterbalanced across participants. Measures included fear (heart rate variability, galvanic skin response, stress indices, and subjective units of distress), engagement with a feared stimulus (eye gaze: time to first fixation and a total number of fixations), acceptability, and perceived treatment credibility. Preliminary results indicate that fear responses can be adequately induced via a robot-piloted platform. Further results will be discussed, as will implications for the treatment of BII phobia and other fears. It is anticipated that piloted robots may provide a useful platform for facilitating exposure therapy, being more acceptable than in-vivo exposure and more flexible than virtual reality exposure.

Keywords: anxiety, digital mental health, exposure therapy, phobia, robot, virtual reality

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Authors: Indu Gaur, Neha Bhadauria, Shilpi Shilpi, Susmita Goswami, Prem D. Sharma, Prabir K. Paul

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The concept of organic agriculture has been accepted as novelty in Indian society, but there is no data available on the human pathogens colonizing plant parts due to such practices. Also, the pattern and mechanism of their colonization need to be understood in order to devise possible strategies for their prevention. In the present study, human pathogenic bacteria were isolated from organically grown tomato plants and five of them were identified as Klebsiella pneumoniae, Enterobacter ludwigii, Serratia fonticola, Stenotrophomonas maltophilia and Chryseobacterium jejuense. Tomato plants were grown in controlled aseptic conditions with 25±1˚C, 70% humidity and 12 hour L/D photoperiod. Six weeks old plants were divided into 6 groups of 25 plants each and treated as follows: Group 1: K. pneumonia, Group 2: E. ludwigii, Group 3: S. fonticola, Group 4: S. maltophilia, Group 5: C. jejuense, Group 6: Sterile distilled water (control). The inoculums for all treatments were prepared by overnight growth with uniform concentration of 108 cells/ml. Leaf samples from above groups were collected at 0.5, 2, 4, 6 and 24 hours post inoculation for the colony forming unit counts (CFU/cm2 of leaf area) of individual pathogens using leaf impression method. These CFU counts were used for the in vivo colonization assay and adherence assay of individual pathogens. Also, resistance of these pathogens to at least 12 antibiotics was studied. Based on these findings S. fonticola was found to be most prominently colonizing the phylloplane of tomato and was further studied. Tomato plants grown in controlled aseptic conditions same as mentioned above were divided into 2 groups of 25 plants each and treated as follows: Group 1: S. fonticola, Group 2: Sterile distilled water (control). Leaf samples from above groups were collected at 0, 24, 48, 72 and 96 hours post inoculation and homogenized in suitable buffers for surface and cell wall protein isolation. Protein samples thus obtained were subjected to isocratic SDS-gel electrophoresis and analyzed. It was observed that presence of S. fonticola could induce the expression of at least 3 additional cell wall proteins at different time intervals. Surface proteins also showed variation in the expression pattern at different sampling intervals. Further identification of these proteins by MALDI-MS and bioinformatics tools revealed the gene(s) involved in the interaction of S. fonticola with tomato phylloplane.

Keywords: cell wall proteins, human pathogenic bacteria, phylloplane, solanum lycopersicum

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Authors: Seyedeh Belin Tavakoly Sany, Rosli Hashim, Majid Rezayi, Aishah Salleh, Omid Safari

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The purpose of this paper is to describe the main characteristics of macroinvertebrate species in response to environmental forcing factors. Overall, 23 species of Mollusca, 4 species of Arthropods, 3 species of Echinodermata and 3 species of Annelida were identified at the 9 sampling stations during four sampling periods. Individual species of Mollusca constituted 36.4% of the total abundance, followed by Arthropods (27.01%), Annelida (34.3%) and Echinodermata (2.4%). The results of Kruskal-Wallis test indicated that a significant difference (p <0.05) in the abundance, richness and diversity of the macro-benthic community in different stations. The correlation analysis revealed that anthropogenic pollution and natural variability caused by these variations in spatial scales.

Keywords: benthic invertebrates, diversity, abundance, West Port

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Authors: Yuzhi Cai

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In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

Procedia PDF Downloads 247

Authors: Khishig-Undrakh Mijgee, Yerkyejan Amanbyek, Yilina, Bayarkhuu Agvaanbayar, Anudari Chingiskhuu

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The study of happiness focuses on how people perceive their well-being, the ways they seek happiness, and the factors that affect their feelings of happiness, including self-esteem, depression, satisfaction, and the quality of life. Researchers also aim to explore the relationship between happiness, self-esteem, depression, satisfaction, and quality of life, with the goal of assessing people's sense of achievement. Happiness is strongly linked to an individual's sense of achievement and overall life satisfaction. In this article, we will discuss the findings of a study that examines the feelings of happiness and the factors that influence them among 562 high school students.

Keywords: happiness, high school students, feelings of happiness, happiness level

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Authors: Chantelle Francis, Karen McKenzie, Charlotte Emmerson

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In the context of the rise in mental health difficulties amongst pupils, this review explores the factors that have been indicated as affecting psychological well-being in mainstream school contexts. Search terms relating to school-based psychological well-being were entered into five databases, and twenty-two studies were included in the review. The results suggested that pupil psychological well-being is affected by both direct and indirect factors. The former included a sense of belonging and inclusion, relationships with teachers, and academic attainment. The latter included family socioeconomic status, whole-school approaches, and individual differences factors, such as gender and Special Educational Needs. The implications for policymakers and practitioners are discussed.

Keywords: psychological wellbeing, mainstream schools, special educational needs, school-based wellbeing

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Ala Hanetite

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The purpose of this article is to present, by means of a model, the determinants of organisational culture which influence creativity and innovation. A literature study showed that a model, based on the open systems theory and the work of Schein, can offer a holistic approach in describing organisational culture. The relationship between creativity, innovation and culture is discussed in this context. Against the background of this model, the determinants of organisational culture were identified. The determinants are strategy, structure, support mechanisms, behaviour that encourages innovation, and open communication. The influence of each determinant on creativity and innovation is discussed. Values, norms and beliefs that play a role in creativity and innovation can either support or inhibit creativity and innovation depending on how they influence individual and group behaviour. This is also explained in the article.

Keywords: attitudes, creativity, innovation, organisational culture

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Authors: Ahmed Elkholy

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Most power transmission cases use gearing in general, and worm gearing, in particular for energy utilization. Therefore, designing gears for minimum weight and maximum power transmission is the main target of this study. In this regard, a new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using a well-established criteria. By combining the results obtained for all slices, the entire worm gear set loading and stressing was determined. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analytical accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

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Authors: Qiaoyun Yang

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Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

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Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

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Authors: Najam U. Saqib

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Self-construal or an individual’s view of him or herself is an important variable by which culture affects the way people think and act. This notion of self-construal is identified with two distinct perspectives on the self. Within the independent construal, the self is seen as different from others, a way of defining the self, prominent in Western societies. The interdependent perspective which is typical for Eastern cultures emphasizes the connectedness of the self to others. The degree of independence-interdependence in one’s self-construal is thought to affect behavior, acceptance of social values, and decision making. This paper manipulates self-construal of Qatari consumers and investigates its effects on accepting incongruent changes in culture as a result of adopting market offerings and behavior that may be perceived as inconsistent with their self-construal. The research recommends strategies for policy makers in Qatar for successful advocacy of initiatives of national importance such as reducing diabetes and obesity by applying self-construal theory.

Keywords: cross-cultural, consumer behavior, self-construal, GCC (Gulf Cooperation Council)

Procedia PDF Downloads 174

Authors: Corbel Camille, Le Cerf Flora, Capriz Françoise, Vaillant-Ciszewicz Anne-Julie, Breaud Jean, Guerin Olivier, Corveleyn Xavier

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Background: The medical environment can generate stressful and anxiety-provoking situations for patients, particularly during painful care procedures for the older population. These stressful environments have deleterious effects on the quality of care and can even put the patient at risk and set the care team up for failure. The search for a solution is, therefore, imperative. The development of new technologies, such as virtual reality (VR), seems to be an answer to this problem. Objectives: The objective of this study is to compare the effects of virtual reality on pain and anxiety when caring for older hospitalized people with the effects of usual care. More precisely, different individual factors (age, cognitive level, individual preferences, etc.) and different virtual reality universes (personalized or non-personalized) are studied to understand the role of these factors in reducing pain and anxiety during care procedures. The aim of this study is to improve the quality of life of patients and caregivers in their work environment. Method: This mono-centered, randomized, controlled study was conducted from September 2023 to September 2024 on 120 participants recruited from the geriatric departments of the Cimiez Hospital, Nice, France. Participants are randomized into three groups: a control group, a personalized VR group and a non-personalized VR group. Each participant is followed during a painful care session. Data are collected before, during and after the care, using measures of pain (Algoplus and numerical scale) and anxiety (Hospital anxiety scale and numerical scale). Physiological assessments with an oximeter are also performed to collect both heart and respiratory rate measurements. The implementation of the care will be assessed among healthcare providers to evaluate its effects on the difficulty and fatigue associated with the care. Additionally, a questionnaire (System Usability Scale) will be administered at the conclusion of the study to determine the willingness of healthcare providers to integrate VR into their daily care practices. Result: The preliminary results indicate significant effects on anxiety (p=.001) and pain (p=<.001) following the VR intervention during care, as compared to the control group. Conclusion: The preliminary results suggest that VRI appears to be a suitable and effective method for reducing anxiety and pain among older hospitalized individuals compared with standard care. Finally, the experiences of healthcare professionals involved will also be considered to assess the impact of these interventions on working conditions and patient support.

Keywords: anxiety, care, pain, older adults, virtual reality

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Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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Authors: Michal Brazda, Miroslav Urbanek, Martina Koukolikova

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This work focuses on the development of functional surfaces and edges for cutting and forming tools created through the Directed Energy Deposition (DED) technology. In the context of growing challenges in modern engineering, additive technologies, especially DED, present an innovative approach to manufacturing tools for forming and cutting. One of the key features of DED is its ability to precisely and efficiently deposit Fully dense metals from powder feedstock, enabling the creation of complex geometries and optimized designs. Gradually, it becomes an increasingly attractive choice for tool production due to its ability to achieve high precision while simultaneously minimizing waste and material costs. Tools created using DED technology gain significant durability through the utilization of high-performance materials such as nickel alloys and tool steels. For high-temperature applications, Nimonic 80A alloy is applied, while for cold applications, M2 tool steel is used. The addition of ceramic materials, such as tungsten carbide, can significantly increase the tool's resistance. The introduction of functionally graded materials is a significant contribution, opening up new possibilities for gradual changes in the mechanical properties of the tool and optimizing its performance in different sections according to specific requirements. In this work, you will find an overview of individual applications and their utilization in the industry. Microstructural analyses have been conducted, providing detailed insights into the structure of individual components alongside examinations of the mechanical properties and tool life. These analyses offer a deeper understanding of the efficiency and reliability of the created tools, which is a key element for successful development in the field of cutting and forming tools. The production of functional surfaces and edges using DED technology can result in financial savings, as the entire tool doesn't have to be manufactured from expensive special alloys. The tool can be made from common steel, onto which a functional surface from special materials can be applied. Additionally, it allows for tool repairs after wear and tear, eliminating the need for producing a new part and contributing to an overall cost while reducing the environmental footprint. Overall, the combination of DED technology, functionally graded materials, and verified technologies collectively set a new standard for innovative and efficient development of cutting and forming tools in the modern industrial environment.

Keywords: additive manufacturing, directed energy deposition, DED, laser, cutting tools, forming tools, steel, nickel alloy

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Minna Pikkarainen, Yueqiang Xu

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The integration of digital technology with existing healthcare processes has been painfully slow, a huge gap exists between the fields of strictly regulated official medical care and the quickly moving field of health and wellness technology. We claim that the promises of preventive healthcare can only be fulfilled when this gap is closed – health care and self-care becomes seamless continuum “correct information, in the correct hands, at the correct time allowing individuals and professionals to make better decisions” what we call connected health approach. Currently, the issues related to security, privacy, consumer consent and data sharing are hindering the implementation of this new paradigm of healthcare. This could be solved by following MyData principles stating that: Individuals should have the right and practical means to manage their data and privacy. MyData infrastructure enables decentralized management of personal data, improves interoperability, makes it easier for companies to comply with tightening data protection regulations, and allows individuals to change service providers without proprietary data lock-ins. This paper tackles today’s unprecedented challenges of enabling and stimulating multiple healthcare data providers and stakeholders to have more active participation in the digital health ecosystem. First, the paper systematically proposes the MyData approach for healthcare and preventive health data ecosystem. In this research, the work is targeted for health and wellness ecosystems. Each ecosystem consists of key actors, such as 1) individual (citizen or professional controlling/using the services) i.e. data subject, 2) services providing personal data (e.g. startups providing data collection apps or data collection devices), 3) health and wellness services utilizing aforementioned data and 4) services authorizing the access to this data under individual’s provided explicit consent. Second, the research extends the existing four archetypes of orchestrator-driven healthcare data business models for the healthcare industry and proposes the fifth type of healthcare data model, the MyData Blockchain Platform. This new architecture is developed by the Action Design Research approach, which is a prominent research methodology in the information system domain. The key novelty of the paper is to expand the health data value chain architecture and design from centralization and pseudo-decentralization to full decentralization, enabled by blockchain, thus the MyData blockchain platform. The study not only broadens the healthcare informatics literature but also contributes to the theoretical development of digital healthcare and blockchain research domains with a systemic approach.

Keywords: blockchain, health data, platform, action design

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Authors: Michael Subbey, Kwame Takyi Danquah

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Finding a child's exceptional skills and abilities at a young age and nurturing them is a challenging process. The Social Learning Theory (SLT) of Albert Bandura is used to analyze the effects of early talent identification on children's growth and development. The study examines both the advantages and disadvantages of early talent identification and stresses the significance of a moral strategy that puts the welfare of the child first. The paper emphasizes the value of a balanced approach to early talent identification that takes into account individual differences, cultural considerations, and the child's social environment.

Keywords: early talent development, social learning theory, child development, child welfare

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Authors: Qiang Wang, Hongyang Yu, MingRong Lai, Miao Luo

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This paper presents a method for accurately localizing and interacting with known surface defects by overlaying patterns onto real-world surfaces using a projection system. Given the world coordinates of the defects, we project corresponding patterns onto the surfaces, providing an intuitive visualization of the specific defect locations. To enable users to interact with and retrieve more information about individual defects, we implement a gesture recognition system based on a pruned and optimized version of YOLOv6. This lightweight model achieves an accuracy of 82.8% and is suitable for deployment on low-performance devices. Our approach demonstrates the potential for enhancing defect identification, inspection processes, and user interaction in various applications.

Keywords: defect localization, projection mapping, gesture recognition, YOLOv6

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Authors: Shiva Ebrahimian Dehaghani, Afsaneh Doosti, Morteza Zare

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Background: There is no consensus regarding the association between dysphagia and cognition. Purpose: The aim of this study was to quantitatively and qualitatively analyze the available evidence on the direction and strength of association between dysphagia and cognition. Methodology: PubMed, Scopus, Embase and Web of Science were searched about the association between dysphagia and cognition. A random-effects model was used to determine weighted odds ratios (OR) and 95% confidence intervals (CI). Sensitivity analysis was performed to determine the impact of each individual study on the pooled results. Results: A total of 1427 participants showed that some cognitive disorders were significantly associated with dysphagia (OR = 3.23; 95% CI, 2.33–4.48). Conclusion: The association between cognition and swallowing disorders suggests that multiple neuroanatomical systems are involved in these two functions.

Keywords: adult, association, cognitive impairment, dysphagia, systematic review

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Authors: Farnaz Farhangi

Abstract:

Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

Abstract:

Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Elias Nemer, Greg Vines

Abstract:

Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

Abstract:

In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Abrar Almutairi, Alyaa Farouk, Amal Gouda

Abstract:

Background: Social capital is a factor that helps in bonding in a social network. The individual and the neighborhood social capital affect the health status of members of a particular society. In addition, to the influence of social health on the health of the population, social health has a significant effect on women, especially those with pregnancy. Study objective was to assess the impact of the social capital on the health status of pregnant women Design: A descriptive crosssectional correlational design was utilized in this study. Methods: A convenient sample of 210 pregnant women who attended the outpatient antenatal clinicsfor follow-up in King Fahad hospital (Ministry of National Guard Health Affairs/Riyadh) and King Abdullah bin Abdelaziz University Hospital (KAAUH, Ministry of Education /Riyadh) were included in the study. Data was collected using a self-administered questionnaire that was developed by the researchers based on the “World Bank Social Capital Assessment Tool” and SF-36 questionnaire (Short Form Health Survey). The questionnaire consists of 4 parts to collect information regarding socio-demographic data, obstetric and gynecological history, general scale of health status and social activity during pregnancy and the social capital of the study participants, with different types of questions such as multiple-choice questions, polar questions, and Likert scales. Data analysis was carried out by using Statistical Package for the Social Sciences version 23. Descriptive statistic as frequency, percentage, mean, and standard deviation was used to describe the sample characteristics, and the simple linear regression test was used to assess the relationship between the different variables, with level of significance P≤0.005. Result: This study revealed that only 31.1% of the study participants perceived that they have good general health status. About two thirds (62.8%) of the participants have moderate social capital, more than one ten (11.2٪) have high social capital and more than a quarter (26%) of them have low social capital. All dimensions of social capital except for empowerment and political action had positive significant correlations with the health status of pregnant women with P value ranging from 0.001 to 0.010in all dimensions. In general, the social capital showed high statistically significant association with the health status of the pregnant (P=0.002). Conclusion: Less than one third of the study participants had good perceived health status, and the majority of the study participants have moderate social capital, with only about one ten of them perceived that they have high social capital. Finally, neighborhood residency area, family size, sufficiency of income, past medical and surgical history and parity of the study participants were all significantly impacting the assessed health domains of the pregnant women.

Keywords: impact, social capital, health status, pregnant women

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