Search results for: brain training

Authors: Bolormaa Dalanbayar, Batsaikhan Ulaankhuu, Bayarmaa Tsogtbaatar

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In this study, we surveyed employers and students to identify compliance between employers' needs and student self-assessment of skills. Employers' survey consisted of fifteen questions to determine employers' assessment of the knowledge and skills of graduates in heavy equipment repairer's programs from four TVET schools. We also compared a survey questionnaire with Liebherr brands' job duty requirements, which determines the training needs and qualification level of their new workers. The study shows more than 76% of employers assessed professional knowledge as sufficient, more than 47% of employers assessed vocational skills as sufficient and more than 43% of employers rated attitudes as sufficient. Therefore, we can state there is a skill mismatch between the employer's assessment and students' self-assessment.

Keywords: skill mismatch, employers needs, competence-based curriculum

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Authors: S. Bahrami, A. Rezaie, Z. Boroumand, S. Ghavami

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Neospora caninum is protozoan parasite which can cause a serious disease in dogs and cattle. It has been shown that birds may be a permissive intermediate host for N. caninum since parasite DNA has been detected in tissues from birds. It is showed that embryonated chicken egg can be used as an animal model for experimental infection. The aim of present study was to compare experimental infection of Neospora in chicken and pigeons embryonated eggs. An infection with N. caninum Nc1 isolate was conducted in chicken and pigeons embryonated eggs to evaluate LD50. After calculation of LD50, 2LD50 of tachyzoites were injected to eggs. Macroscopic changes of each embryo were noticed and to investigate the parasite distribution in tissues immunohistochemistry (IHC) and molecular methods were used. In the present study, histopathological changes were considered and sections to those used for histopathological examination including heart, liver, brain and chorioallantoic (CA) membrane were subjected to IHC, too. For PCR procedure, primer pair Np21/Np6 was used for amplification of the Nc5 gene. Pigeon's embryo showed more macroscopic changes than chicken embryo. A hemorrhage of the CA was the main grass lesion. All the infected tissues had histopathological changes. Microscopic examination of tissues revealed acute neosporosis due to hemorrhage, necrosis and infiltration of mononuclear inflammatory cells. Based on IHC and molecular results, the parasite aggregation in the heart was more predominant than in the other tissues. These results reinforce that there is genetic susceptibility to N. caninum in pigeons embryonated eggs like chickens embryonated eggs and provide new insights to research an inexpensive and available animal model for N. caninum.

Keywords: immunohistochemistry, Neospora caninum, PCR, pigeon embryonated egg

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Authors: Manisha Singh, Padam Simkhada

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Background: Although mental health policy has been adapted in Nepal since 1997, the implementation of the policy framework is yet to happen. The fact that mental health services are largely concentrated in urban areas more specific to treatment only provides a clear picture of the scarcity of mental health services in the country. The shreds of evidence from around the world, along with WHO’s (World Health Organization) Mental Health Gap Action Program (mhGAP) suggest that effective mental health services can be provided from Primary Health Care (PHC) centers through community-based programs without having to place a specialized health worker. However, the country is still facing the same challenges to date with very few psychiatrists and psychologists, but they are largely based in cities. Objectives: The main objectives of this study are; (a) to understand the perception of health workers at PHC on maternal mental health, and (b) to assess the availability of the mental health services at PHC to address maternal mental health. Methods: This study used a qualitative approach where an in-depth interview was conducted with the health workers at the primary level. “Mayadevi” rural municipality in Rupendehi District that comprised of 13 small villages, was chosen as the study site. A total 8 health institutions which covered all 13 sites were included where either the health post in- charge or health worker working in maternal and child health care was interviewed for the study. All the health posts in the study area were included in the study. The interviews were conducted in Nepali; later, they were translated in English, transcribed, and triangulated. NViVO was used for the analysis. Results: The findings show that most of the health workers understood what maternal mental health was and deemed it as a public health issue. They could explain the symptoms and knew what medication to prescribe if need be. However, the majority of them failed to name the screening tools in place for maternal mental health. Moreover, they hadn’t even seen one. None of the health care centers had any provision for screening mental health status. However, one of the centers prescribed medication when the patients displayed symptoms of depression. But they believed there were a significant number of hidden cases in the community due to the stigma around mental health and being a woman with mental health problem makes the situation even difficult. Nonetheless, the health workers understood the importance of having screening tools and acknowledged the need of training and support in order to provide the services from PHC. Conclusion: Community health workers can identify cases with mental health problems and prevent them from deteriorating further. But there is a need for robust training and support to build the capacity of the health workers. The screening tools on mental health needs to be encouraged to be used in the PHC levels. Furthermore, community-based culture-sensitive programs need to be initiated and implemented to mitigate the stigma related issues around mental health.

Keywords: maternal mental health, health care providers, screening, Nepal

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Authors: Yang Zhuo

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This study explores the integration of MIDI technology as one of the important digital technologies in music teaching, from the perspective of teaching practice, into the process of cultivating students' teaching skills. At the same time, the framework elements of the learning environment for music education students are divided into four aspects: digital technology supported learning space, new knowledge learning, teaching methods, and teaching evaluation. In teaching activities, more attention should be paid to students' subjectivity and interaction between them so as to enhance their emotional experience in teaching practice simulation. In the process of independent exploration and cooperative interaction, problems should be discovered and solved, and basic knowledge of music and teaching methods should be exercised in practice.

Keywords: music education, educational technology, MIDI, teacher training

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Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

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Authors: Alfredo Soeiro

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Rehabilitation in construction or built environment is a particular type of operations when concerning prevention of accidents. In fact, it is also a different type of task in construction itself. Therefore, due to the complex characteristics of construction rehabilitation tasks and due to the intrinsic difficulty of preventing accidents in construction, a major challenge faces the responsibility for implementing adequate safety levels in this type of safety management. This paper addresses a set of proposed generic measures to face the unknown characteristics of built environment in terms of stability, materials and actual performance of buildings or other constructions. It is also addressed the necessary adaptation of preventive guidelines to this type of delicate refurbishing and renovating of existing facilities. Training, observation and reflective approaches are necessary to perform this safety management in the rehabilitation of built environment.

Keywords: built environment, rehabilitation, construction safety, accident prevention, safety plan

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Authors: Malcolm Richardson, Gabriele Richardson

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This paper illustrates how historical problems can be studied successfully using GIS even in cases in which data, in the modern sense, is fragmentary. The overall problem under investigation is how early (1300-1500) English schools of Common Law moved from apprenticeship training in random individual London inns run in part by clerks of the royal chancery to become what is widely called 'the Third University of England,' a recognized system of independent but connected legal inns. This paper focuses on the preparatory legal inns, called the Inns of Chancery, rather than the senior (and still existing) Inns of Court. The immediate problem studied in this paper is how the junior legal inns were organized, staffed, and located from 1292 to about 1500, and what maps tell us about the role of the chancery clerks as managers of legal inns. The authors first uncovered the names of all chancery clerks of the period, most of them unrecorded in histories, from archival sources in the National Archives, Kew. Then they matched the names with London property leases. Using ArcGIS, the legal inns and their owners were plotted on a series of maps covering the period 1292 to 1500. The results show a distinct pattern of ownership of the legal inns and suggest a narrative that would help explain why the Inns of Chancery became serious centers of learning during the fifteenth century. In brief, lower-ranking chancery clerks, always looking for sources of income, discovered by 1370 that legal inns could be a source of income. Since chancery clerks were intimately involved with writs and other legal forms, and since the chancery itself had a long-standing training system, these clerks opened their own legal inns to train fledgling lawyers, estate managers, and scriveners. The maps clearly show growth patterns of ownership by the chancery clerks for both legal inns and other London properties in the areas of Holborn and The Strand between 1450 and 1417. However, the maps also show that a royal ordinance of 1417 forbidding chancery clerks to live with lawyers, law students, and other non-chancery personnel had an immediate effect, and properties in that area of London leased by chancery clerks simply stop after 1417. The long-term importance of the patterns shown in the maps is that while the presence of chancery clerks in the legal inns likely created a more coherent education system, their removal forced the legal profession, suddenly without a hostelry managerial class, to professionalize the inns and legal education themselves. Given the number and social status of members of the legal inns, the effect on English education was to free legal education from the limits of chancery clerk education (the clerks were not practicing common lawyers) and to enable it to become broader in theory and practice, in fact, a kind of 'finishing school' for the governing (if not noble) class.

Keywords: GIS, law, London, education

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

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The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: Ignatio Madanhire, Charles Mbohwa

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This research examines the effect of a human resource strategy and the overall equipment effectiveness as well as assessing how the combination of the two can increase a firm’s productivity. The human resource aspect is looked at in detail to assess motivation of operators through training to reduce wastage on the manufacturing shop floor. The waste was attributed to operators, maintenance personal, idle machines, idle manpower and break downs. This work seeks to investigate the concept of Total Productive Maintenance (TPM) in addressing these short comings in the manufacturing case study. The impact of TPM to increase production while, as well as increasing employee morale and job satisfaction is assessed. This can be resource material for practitioners who seek to improve overall equipment efficiency (OEE) to achieve higher level productivity and competitiveness.

Keywords: maintenance, TPM, efficiency, productivity, strategy

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Authors: Keivan Jamshidi

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Myiasis is defined as the infestation of living tissues of vertebrates by larvae of flies. Gingival myiasis is an uncommon type of myiasis. In oral inspection of a death dog (Garmsar, Iran) for routine training postmortem investigation, gingival myiasis was found. Only one larva was removed from the lesions and sent to a parasitology laboratory for identification. For histopathological studies, affected area of the gingiva was cut and placed in 10% formalin, and then sent to pathology laboratory. On parasitological examination the causative agent of this condition was found as larva of Wohlfahrtia magnifica. Histopathological examination of the injured gingiva showed hyperplasia of squamous epithelial tissue and acanthosis in mucosal membrane, hyperemia and infiltration of mononuclear cells and eosinophils into lamina propria. The present report seems to be the first report of gingival myiasis in dog in Iran.

Keywords: Wohlfahrtia magnifica, gingiva, myiasis, dog

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Yesim Özogul, Fethiye Takadaş, Mustafa Durmus, Yılmaz Ucar, Ali Rıza Köşker, Gulsun Özyurt, Fatih Özogul

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It has been well documented that polyunsaturated fatty acids (PUFAs), especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have beneficial effects on health, regarding prevention of cardiovascular diseases, cancer and autoimmune disorders, development the brain and retina and treatment of major depressive disorder etc. Thus, an adequate intake of omega PUFA is essential and generally marine fish are the richest sources of PUFA in human diet. Thus, this study was conducted to evaluate the efficiency of different extraction methods (Bligh and Dyer, soxhlet, microwave and ultrasonics) on the fat content and fatty acid profiles of marine fish species (Mullus babatus, Upeneus moluccensis, Mullus surmuletus, Anguilla anguilla, Pagellus erythrinus and Saurida undosquamis). Fish species were caught by trawl in Mediterranean Sea and immediately iced. After that, fish were transported to laboratory in ice and stored at -18oC in a freezer until the day of analyses. After extracting lipid from fish by different methods, lipid samples were converted to their constituent fatty acid methyl esters. The fatty acid composition was analysed by a GC Clarus 500 with an autosampler (Perkin Elmer, Shelton, CT, USA) equipped with a flame ionization detector and a fused silica capillary SGE column (30 m x 0.32 mm ID x 0.25 mm BP20 0.25 UM, USA). The results showed that there were significant differences (P < 0.05) in fatty acids of all species and also extraction methods affected fat contents and fatty acid profiles of fish species.

Keywords: extraction methods, fatty acids, marine fish, PUFA

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Authors: Sumanta Daw, Gopal Chandra Saha

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The present study was conducted to explore the basic pulmonary functions which may generally vary according to the bio-physical characteristics including age, height, body weight, and environment etc. of the sports performers. Regular and specific training exercises also change the characteristics of an athlete’s prowess and produce a positive effect on the physiological functioning, mostly upon cardio-pulmonary efficiency and thereby improving the body mechanism. The objective of the present study was to compare the differences in cardio-respiratory functions between aquatics and track and field performers. As cardio-respiratory functions are influenced by pulse rate and blood pressure (systolic and diastolic), so both of the factors were also taken into consideration. The component selected under cardio-respiratory functions for the present study were i) FEVI/FVC ratio (forced expiratory volume divided by forced vital capacity ratio, i.e. the number represents the percentage of lung capacity to exhale in one second) ii) FVC1 (this is the amount of air which can force out of lungs in one second) and iii) FVC (forced vital capacity is the greatest total amount of air forcefully breathe out after breathing in as deeply as possible). All the three selected components of the cardio-respiratory efficiency were measured by spirometry method. Pulse rate was determined manually. The radial artery which is located on the thumb side of our wrist was used to assess the pulse rate. Blood pressure was assessed by sphygmomanometer. All the data were taken in the resting condition. 36subjects were selected for the present study out of which 18were water polo players and rest were sprinters. The age group of the subjects was considered between 18 to 23 years. In this study the obtained data inform of digital score were treated statistically to get result and draw conclusions. The Mean and Standard Deviation (SD) were used as descriptive statistics and the significant difference between the two subject groups was assessed with the help of statistical ‘t’-test. It was found from the study that all the three components i.e. FEVI/FVC ratio (p-value 0.0148 < 0.01), FVC1 (p-value 0.0010 < 0.01) and FVC (p-value 0.0067 < 0.01) differ significantly as water polo players proved to be better in terms of cardio-respiratory functions than sprinters. Thus study clearly suggests that the exercise training as well as the medium of practice arena associated with water polo players has played an important role to determine better cardio respiratory efficiency than track and field athletes. The outcome of the present study revealed that the lung function in land-based activities may not provide much impact than that of in water activities.

Keywords: cardio-respiratory efficiency, spirometry, water polo players, sprinters

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Mahdi Farajzadeh Ajirlou

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The detailed serious adverse effects raised the stresses around the safety of individuals who have gotten COVID-19 vaccines. Numerous verification referrers that disease with COV-19 causes neurological dysfunction in a significant proportion of influenced patients, where these side effects show up seriously amid the disease, and still less is known approximately the potential long-term results for the brain, where the loss of olfaction could be a neurological sign and simple indications of COVID-19. Since publishing effective clinical trial results of mRNA coronavirus disease 2019 (COVID-19) and injecting it to the volunteers in 2020, numerous reports have emerged approximately about cardiovascular complications followed by the mRNA vaccination. Vaccination-associated adenopathy could be a constant imaging finding after the organization of COVID-19 antibodies that will lead to a symptomatic problem in patients with shown or suspected cancer, in whom it may be vague from dangerous nodal inclusion. In spite of all the benefits and viability of the coronavirus infection 2019 (COVID-19) antibodies specified in later clinical trials, a few other post-vaccination side impacts, such as lymphadenopathy (LAP), were observed. Also, numerous variables, including financial conditions, have played a critical part in expanding the number of people with COVID-19 infection and also much more side effects in that country. Amid the Coronavirus widespread, Iran has been experiencing extreme sanctions, which has faced this nation with an extreme financial crisis. Additionally, with COVID-19 widespread, there was a developing concern around the abuse of imaging exams extraordinarily within the pediatric populace, which highlights the issues pointed out by this review.

Keywords: radiology, vaccines, COVID-19, side effect

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Authors: Javed Mohammed

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Robotics is the fastest growing industry in the world, poised to become the largest in the next decade. The use of robots requires design, application and implementation of the appropriate safety controls in order to avoid creating hazards to production personnel, programmers, maintenance specialists and systems engineers. The increasing use of artificial intelligence (AI) and related technologies in the workplace are dramatically changing the employment landscape. The impact of robotics technology on workplace policy is dramatic and complex. The robotics revolution calls for a comprehensive approach to job training, and retraining, to mitigate worker displacement and enable workers to benefit from the new jobs that the technology will generate. It calls for a thoughtful, forward-thinking approach by lawmakers, regulators and employers to prepare for the oncoming transformation of the workplace and workforce.

Keywords: design, artificial intelligence, programmers, system engineers, robotics, transformation

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Authors: Jiří Barta

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The paper deals with simulation programs of spread of harmful substances. Air pollution has a direct impact on the quality of human life and environmental protection is currently a very hot topic. Therefore, the paper focuses on the simulation of release of harmful substances. The first part of article deals with perspectives and possibilities of implementation outputs of simulations programs into the system which is education and of practical training of the management staff during emergency events in the frame of critical infrastructure. The last part shows the practical testing and evaluation of simulation programs. Of the tested simulations software been selected Symos97. The tool offers advanced features for setting leakage. Gradually allows the user to model the terrain, location, and method of escape of harmful substances.

Keywords: Computer Simulation, Symos97, Spread, Simulation Software, Harmful Substances

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Authors: G. C. Phiri, E. A. Heil, A. A. Kalimbira, E. Muehlhoff, C. Masangano, B. M. Mtimuni, J. Herrmann, M. B. Krawinkel, I. Jordan

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Background and objectives: High prevalence of undernutrition in Malawi is caused by poor complementary foods. Lack of knowledge of age appropriate food within the household might affect utilization of available resources. FAO-Malawi implemented nutrition education (NE) sessions in 200 villages in Kasungu and Mzimba districts from December 2012 to April 2013 targeting 15 caregivers per village of children aged 6-18 months, grandmothers, spouses and community leaders. Two trained volunteers per village facilitated 10 NE sessions on breastfeeding, food safety and hygiene and complementary feeding using locally available resources. This study assessed the reported dietary diversification practices of infant and young child after nutrition education and the factors that influenced adoption of the practice. Methodology: Questionnaire-based interviews with caregivers were conducted in 16 randomly selected villages (n=108) before training-(t1) and seven months after training-(t2). Knowledge score (KS) was calculated on the indicators breastfeeding, hygiene and complementary feeding. Count regression was performed using SPSS 22. Eight focus group discussions (FGDs) were separately conducted among caregivers and grandmothers in 4 villages. Content analysis was used to analyze FGDs data. Results: Following NE, caregivers' KS significantly increased (p<0.001) between t1 and t2 for breastfeeding (7.7 vs. 9.8, max=18), hygiene (3.8 vs. 5.9, max=7) and complementary feeding (10.2 vs. 16.2, max=26). Caregivers indicated that they stopped preparation of plain-refined maize meal porridge after they gained knowledge on dietary diversification of complementary foods. They learnt mushing and pounding of ingredients for enriched porridge. Whole-maize meal or potatoes were often enriched with vegetables, legumes, small fish or eggs and cooking oil. Children liked the taste of enriched porridge. Amount of enriched porridge consumed at each sitting increase among previously fussy-eater children. Meal frequency increased by including fruits as snacks in child’s diet. Grandmothers observed preparation of enriched porridge among the mothers using locally available foods. Grandmothers liked the taste of enriched porridge and not the greenish color of the porridge. Both grandmothers and mothers reported that children were playing independently after consuming enriched porridge and were strong and healthy. These motivated adoption of the practice. Conclusion: Increased knowledge and skill of preparation and utilisation of locally available foods promoted children’s dietary diversification. Children liking the enriched porridge motivated adoption of dietary diversification.

Keywords: behaviour change, complementary feeding, dietary diversification, IYCN

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Authors: Anna Fowler

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When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

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Authors: Reza Bazargan lari, Mohammad H. Fattahi

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Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for pre-processing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based pre-processing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.

Keywords: wavelet, de-noising, predictability, time series fractal analysis, valid length, ANN

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Authors: Xingyu Pan, Laure Tougne

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For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: coin, detection, character recognition, topology

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Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

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Authors: Ayda Youssef, Mohammed Ali Khalaf, Tarek Rafaat

Abstract:

Background: Langerhans cell histiocytosis (LCH) is a rare multi-systemic disease that shows an abnormal proliferation of these kinds of cells associated with a granular infiltration that affects different structures of the human body, including the lung, liver, spleen, lymph nodes, brain, mucocutaneous, soft tissue (head and neck), and salivary glands. Evaluation of the extent of disease is one of the major predictors of patient outcome. Objectives: To recognize the pathogenesis of Langerhans cell histiocytosis (LCH), describe the radiologic criteria that are suggestive of LCH in different organs rather than the bones and to illustrate the appropriate differential diagnoses for LCH in each of the common extra-osseous sites. Material and methods: A retrospective study was done on 150 biopsy-proven LCH patients from 2007 to 2012. All patients underwent imaging studies, mostly US, CT, and MRI. These patients were reviewed to assess the extra-skeletal manifestations of LCH. Results: In 150 patients with biopsy-proven LCH, There were 33 patients with liver affection, 5 patients with splenic lesions, 55 patients with enlarged lymph nodes, 9 patient with CNS disease and 11 patients with lung involvement. Conclusions: Because of the frequent LCH children and evaluation of the extent of disease is one of the major predictors of patient outcome. Radiologist need to be familiar with its presentation in different organs and regions of body outside the commonest site of affection (bones). A high-index suspicion should be raised a biopsy is recommended in the presence of radiological suspicion. Chemotherapy is the preferred therapeutic modality.

Keywords: langerhans cell histiocytosis, extra-skeletal, pediatrics, radiology

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

Abstract:

One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples acquired from Felda Johor Bulker Sdn Bhd were studied. A FOSS NIRSystem was used to tak e absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Partial Least Square Regression (PLSR) prediction model with 50 optimal number of principal components was implemented to study the relationship between the measured Free Fatty Acid (FFA) values and the measured spectral absorption. PLSR showed predictive ability of FFA values with correlative coefficient (R) of 0.9808 for the training set and 0.9684 for the testing set.

Keywords: palm oil, fatty acid, NIRS, PLSR

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Authors: Zahara Abdulhussan Al-Awadai

Abstract:

In recent years, serious games have started to gain an increasing interest as a tool to support learning across different educational and training fields. It began to serve as a powerful educational tool for improving learning outcomes. In this research, we discuss the potential of virtual experiences and games research outside of the games industry and explore the multifaceted impact of serious games and related technologies on various aspects of our lives. We highlight the usage of serious games as a tool to improve education and other applications with a purpose beyond the entertainment industry. One of the main contributions of this research is proposing a model that facilitates the design and development of serious games in a flexible and easy-to-use way. This is achieved by exploring different requirements to develop a model that describes a serious game structure with a focus on both aspects of serious games (educational and entertainment aspects).

Keywords: game development, requirements, serious games, serious game model

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Authors: Elena Roadhouse

Abstract:

“When it take the kitchen middens from the latest canning session out to the compost before going to bed, the orchestra is in full chorus. Night vapors and scents from the earth mingle with the fragrance of honeysuckle nearby and basil grown in the compost. They merge into the rhythmic pulse of night”. William Longgood Carl Jung did not specifically recognize scent and olfactory function as a window into the psyche. He did recognize instinct and the natural history of mankind as key to understanding and reconnecting with the Psyche. The progressive path of modern humans has brought incredible scientific and industrial advancements that have changed the human relationship with Mother Earth, the primal wisdom of mankind, and led to the loss of instinct. The olfactory bulbs are an integral part of our ancient brain and has evolved in a way that is proportional to the human separation with the instinctual self. If olfaction is a gateway to our instinct, then it is also a portal to the soul. Natural aromatics are significant and powerful instruments for supporting the mind, our emotional selves, and our bodies. This paper aims to shed light on the important role of scent in the understanding of the existence of the psyche, generational trauma, and archetypal fragrance. Personalized Natural Perfume combined with mindfulness practices can be used as an effective behavioral conditioning tool to promote the healing of transgenerational and individual trauma, the fragmented self, and the physical body.

Keywords: scentscape of the soul, psyche, individuation, epigenetics, depth psychology, carl Jung, instinct, trauma, archetypal scent, personal myth, holistic wellness, natural perfumery

Procedia PDF Downloads 104