Search results for: smart training

Authors: Barkha Ramteke, Sonali Ridhorkar

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An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

Procedia PDF Downloads 120

Authors: A. Gonzalez Aguna, J. M. Santamaria Garcia, J. L. Gomez Gonzalez, R. Barchino Plata, M. Fernandez Batalla, S. Herrero Jaen

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Background: Computer Science is a field that transcends other disciplines of knowledge because it allows to support all kinds of physical and mental tasks. Health centres have a greater number and complexity of technological devices and the population consume and demand services derived from technology. Also, nursing education plans have included competencies related to and, even, courses about new technologies are offered to health professionals. However, nurses still limit their performance to the use and evaluation of products previously built. Objective: Develop a teaching-learning methodology for acquiring skills on designing applications for care. Methodology: Blended learning teaching with a group of graduate nurses through official training within a Master's Degree. The study sample was selected by intentional sampling without exclusion criteria. The study covers from 2015 to 2017. The teaching sessions included a four-hour face-to-face class and between one and three tutorials. The assessment was carried out by written test consisting of the preparation of an IEEE 830 Standard Specification document where the subject chosen by the student had to be a problem in the area of care. Results: The sample is made up of 30 students: 10 men and 20 women. Nine students had a degree in nursing, 20 diploma in nursing and one had a degree in Computer Engineering. Two students had a degree in nursing specialty through residence and two in equivalent recognition by exceptional way. Except for the engineer, no subject had previously received training in this regard. All the sample enrolled in the course received the classroom teaching session, had access to the teaching material through a virtual area and maintained at least one tutoring. The maximum of tutorials were three with an hour in total. Among the material available for consultation was an example of a document drawn up based on the IEEE Standard with an issue not related to care. The test to measure competence was completed by the whole group and evaluated by a multidisciplinary teaching team of two computer engineers and two nurses. Engineers evaluated the correctness of the characteristics of the document and the degree of comprehension in the elaboration of the problem and solution elaborated nurses assessed the relevance of the chosen problem statement, the foundation, originality and correctness of the proposed solution and the validity of the application for clinical practice in care. The results were of an average grade of 8.1 over 10 points, a range between 6 and 10. The selected topic barely coincided among the students. Examples of care areas selected are care plans, family and community health, delivery care, administration and even robotics for care. Conclusion: The applied methodology of learning-teaching for the design of technologies demonstrates the success in the training of nursing professionals. The role of expert is essential to create applications that satisfy the needs of end users. Nursing has the possibility, the competence and the duty to participate in the process of construction of technological tools that are going to impact in care of people, family and community.

Keywords: care, learning, nursing, technology

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Authors: Yueh Hsiu Giffen Cheng, Teng Jung Wang

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According to the study of British national advisory council on creative and cultural education（NACCCE, what the present and the future need awesome innovative and creative people from the perspective of commercial human resources. Therefore, we can know from above, creativity plays an important role in today’s enterprise indeed. Besides, many companies are aimed at developing team work as their main goal, so “creativity” and “teamwork” become more and more important factors to succeed and team creativity also turn into an important issue gradually. Then, the study takes in-depth interviews of design companies’ leaders and uses self-designed questionnaire regarding affecting team creativity to conduct cross-analysis. The results show that for those creative-oriented integrated design companies, their design strategies don’t begin until data collection and their scripts are usually the best way to inspire creativity. Besides, passing down a legacy of experiences are their common educational training. Most important of all, their organizational resources and leaders can assist all the team to learn and grow effectively and the good interaction between the leader and the member can also bring work flexibility and efficiency. In short, the leader’s expectation of members’ performance can cause them to encourage each other to progress. Moreover, the analysis of questionnaire indicates that members who are open-minded and leaders who have transformational leadership style can both help to establish a good team interaction. Furthermore, abundant resources and training system are also good approaches to establish a harmonious relationship. Finally, through integrating the outcomes of interviews and questionnaires, we can infer that those integrated design companies’ circumstances of design progress are mainly from their leaders’ guidance. In addition, the analysis of design problems are focused on their creative strategies and their scripts and sketches can also inspire their creativity. In sum, the feature of all team is influenced by 4 factors: leaders who have transformational leadership style, open-minded members, flexible working environment, resources and interactive relationship. Ultimately, the study hopes that the result above can apply to the design-related industries or help general companies elevate the team creativity.

Keywords: creativity, team creativity, integrated design companies, design process

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Authors: Catherine Mary Abou-Zaid, Sandra Goodwin

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This study was conducted in a cardiac center in Bahrain. The rise in the amount of obese patients’ both men and women, being admitted for surgical procedures has become an issue to the nurses and doctors as these patients pose a high risk of major complications arising from their problem. The cessation of obesity in the country is very high and obesity-related diseases has been the cause of concern among men and women, also related individual diseases such as cardiovascular, diabetes and chronic respiratory diseases are rising dramatically within Bahrain in the last 10 years. Rationale for the Study: The ontological approach will help to understand and assess the true nature of the social world and how the world looks at obesity. Obesity has to be looked at as being a realistic ongoing issue. The epistemological approach will look at the theory of the origins of the nature of knowledge, set the rule of validating and learning in the social world of what can be done to curb this concept and how this can help prevent otherwise preventable diseases. Design Methodology: The qualitative design methodology took the form of an ontological/epistemological approach using phenomenology as a framework. The study was based on a social research issue, therefore, ontological ‘realism and idealism’ will feature as the nature of the world from a social and natural context. Epistemological positions of the study will be how we as researchers will find the actual social world and the limiting of that knowledge. The one-to-one interviews will be transcribed and the taped verbatim will be coded and charted giving the thematic analytic results. Recommendations: The significance of the research brought many recommendations. These recommendations were taken from the themes and sub-themes and were presented to the centers management and the necessary arrangements for updating knowledge and attitudes towards obesity in cardiac patients was then presented to the in-service education department. Workshops and training sessions on promoting health education were organized and put into the educational calendar for the next academic year. These sessions would look at patient autonomy, the patients’ rights, healthy eating for patients and families and the risks associated with obesity in cardiac disease processes.

Keywords: cardiac patients, diabetes, education & training, obesity cessation, qualitative

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Authors: Muhammad N. Khan, Syed O. Gillani, Mohsin Jamil, Tarbia Iftikhar

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With the increasing demand of bandwidth and data rate, there is a dire need to implement antenna systems in mobile phones which are able to fulfill user requirements. A monopole antenna system with multi-antennas configurations is proposed considering the feasibility and user demand. The multi-antenna structure is referred to as multi-input multi-output (MIMO) antenna system. The multi-antenna system comprises of 4 antennas operating below 6 GHz frequency bands for 4G/LTE and 4 antenna for 5G applications at 28 GHz and the dimension of board is 120 × 70 × 0.8mm3. The suggested designs is feasible with a structure of low-profile planar-antenna and is adaptable to smart cell phones and handheld devices. To the best of our knowledge, this is the first design compared to the literature by having integrated antenna system for two standards, i.e., 4G and 5G. All MIMO antenna systems are simulated on commercially available software, which is high frequency structures simulator (HFSS).

Keywords: high frequency structures simulator (HFSS), mutli-input multi-output (MIMO), monopole antenna, slot antenna

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Hyungil Chae

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This work presents a method to reduce spinning current of a Hall-effect sensor for low-power magnetic sensor applications. Spinning current of a Hall-effect sensor changes the direction of bias current periodically and can separate signals from DC-offset. The bias current is proportional to the sensor sensitivity but also increases the power consumption. To achieve both high sensitivity and low power consumption, the bias current can be pulse-width modulated. When the bias current duration Tb is reduced by a factor of N compared to the spinning current period of Tₛ/2, the total power consumption can be saved by N times. N can be large as long as the Hall-effect sensor settles down within Tb. The proposed scheme is implemented and simulated in a 0.18um CMOS process, and the power saving factor is 9.6 when N is 10. Acknowledgements: This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (20160001360022003, Development of Hall Semi-conductor for Smart Car and Device).

Keywords: chopper stabilization, Hall-effect sensor, pulse width modulation, spinning current

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Authors: Maruf Farhan, Abdul Salih, Sikandar Ali Tahir

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Protecting patient information's confidentiality is paramount considering the widespread use of Internet of Things (IoT) gadgets in medical settings. This study's subjects are decentralized identifiers (DIDs) and verifiable credentials (VCs) in conjunction with an OAuth-based authorization framework, as they are the key to protecting IoT healthcare devices. DIDs enable autonomous authentication and trust formation between IoT devices and other entities. To authorize users and enforce access controls based on verified claims, VCs offer a secure and adaptable solution. Through the proposed method, medical facilities can improve the privacy and security of their IoT devices while streamlining access control administration. A Smart pill dispenser in a hospital setting is used to illustrate the advantages of this method. The findings demonstrate the value of DIDs, VCs, and OAuth-based delegation in protecting the IoT devices. Improved processes for authorizing and controlling access to IoT devices are possible thanks to the research findings, which also help ensure patient confidentiality in the healthcare sector.

Keywords: Iot, DID, authorization, verifiable credentials

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Authors: Gopal Chandra Saha, Sumanta Daw

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Warm-up is an essential component for optimizing performance in various sports before a physical fitness training session. This study investigated the immediate comparative effect of Self-Myofascial Release through vibration rolling (VR), non-vibration rolling (NVR), and static stretching as a part of a warm-up treatment on the functional fitness of young adults. Functional fitness is a classification of training that prepares the body for real-life movements and activities. For the present study 20male physical education students were selected as subjects. The age of the subjects was ranged from 20-25 years. The functional fitness variables undertaken in the present study were flexibility, muscle strength, agility, static and dynamic balance of the lower extremity. Each of the three warm-up protocol was administered on consecutive days, i.e. 24 hr time gap and all tests were administered in the morning. The mean and SD were used as descriptive statistics. The significance of statistical differences among the groups was measured by applying ‘F’-test, and to find out the exact location of difference, Post Hoc Test (Least Significant Difference) was applied. It was found from the study that only flexibility showed significant difference among three types of warm-up exercise. The observed result depicted that VR has more impact on myofascial release in flexibility in comparison with NVR and stretching as a part of warm-up exercise as ‘p’ value was less than 0.05. In the present study, within the three means of warm-up exercises, vibration roller showed better mean difference in terms of NVR, and static stretching exercise on functional fitness of young physical education practitioners, although the results were found insignificant in case of muscle strength, agility, static and dynamic balance of the lower extremity. These findings suggest that sports professionals and coaches may take VR into account for designing more efficient and effective pre-performance routine for long term to improve exercise performances. VR has high potential to interpret into an on-field practical application means.

Keywords: self-myofascial release, functional fitness, foam roller, physical education

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Authors: Oualid Walid Ben Ali

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Big Data has become one of the buzzwords today. The recent explosion of digital data has led the organization, either private or public, to a new era towards a more efficient decision making. At some point, business decided to use that concept in order to learn what make their clients tick with phrases like ‘sales funnel’ analysis, ‘actionable insights’, and ‘positive business impact’. So, it stands to reason that Big Data was viewed through green (read: money) colored lenses. Somewhere along the line, however someone realized that collecting and processing data doesn’t have to be for business purpose only, but also could be used for other purposes to assist law enforcement or to improve policing or in road safety. This paper presents briefly, how Big Data have been used in the fields of policing order to improve the decision making process in the daily operation of the police. As example, we present a big-data driven system which is sued to accurately dispatch the patrol cars in a geographic environment. The system is also used to allocate, in real-time, the nearest patrol car to the location of an incident. This system has been implemented and applied in the Emirate of Abu Dhabi in the UAE.

Keywords: big data, big data analytics, patrol car allocation, dispatching, GIS, intelligent, Abu Dhabi, police, UAE

Procedia PDF Downloads 474

Authors: Rahbel Rahman, Rogério Meireles Pinto, Margareth Santos Zanchetta

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Background: Existing shortcomings of current health-service delivery include poor teamwork, competencies that do not address consumer needs, and episodic rather than continuous care. Brazil’s Sistema Único de Saúde (Unified Health System, UHS) is acknowledged worldwide as a model for delivering community-based care through Estratégia Saúde da Família (FHS; Family Health Strategy) interdisciplinary teams, comprised of Community Health Agents (in Portuguese, Agentes Comunitário de Saude, ACS), nurses, and physicians. FHS teams are mandated to collectively offer clinical care, disease prevention services, vector control, health surveillance and social services. Our study compares medical providers (nurses and physicians) and community-based providers (ACS) on their perceptions of work environment, professional skills, cognitive capacities and job context. Global health administrators and policy makers can leverage on similarities and differences across care providers to develop interprofessional training for community-based primary care. Methods: Cross-sectional data were collected from 168 ACS, 62 nurses and 32 physicians in Brazil. We compared providers’ demographic characteristics (age, race, and gender) and job context variables (caseload, work experience, work proximity to community, the length of commute, and familiarity with the community). Providers perceptions were compared to their work environment (work conditions and work resources), professional skills (consumer-input, interdisciplinary collaboration, efficacy of FHS teams, work-methods and decision-making autonomy), and cognitive capacities (knowledge and skills, skill variety, confidence and perseverance). Descriptive and bi-variate analysis, such as Pearson Chi-square and Analysis of Variance (ANOVA) F-tests, were performed to draw comparisons across providers. Results: Majority of participants were ACS (64%); 24% nurses; and 12% physicians. Majority of nurses and ACS identified as mixed races (ACS, n=85; nurses, n=27); most physicians identified as males (n=16; 52%), and white (n=18; 58%). Physicians were less likely to incorporate consumer-input and demonstrated greater decision-making autonomy than nurses and ACS. ACS reported the highest levels of knowledge and skills but the least confidence compared to nurses and physicians. ACS, nurses, and physicians were efficacious that FHS teams improved the quality of health in their catchment areas, though nurses tend to disagree that interdisciplinary collaboration facilitated their work. Conclusion: To our knowledge, there has been no study comparing key demographic and cognitive variables across ACS, nurses and physicians in the context of their work environment and professional training. We suggest that global health systems can leverage upon the diverse perspectives of providers to implement a community-based primary care model grounded in interprofessional training. Our study underscores the need for in-service trainings to instill reflective skills of providers, improve communication skills of medical providers and curative skills of ACS. Greater autonomy needs to be extended to community based providers to offer care integral to addressing consumer and community needs.

Keywords: global health systems, interdisciplinary health teams, community health agents, community-based care

Procedia PDF Downloads 217

Authors: Malki Fatima Zahra Nadia, Kellal Cheiimaa, Brahimi Houria

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Total Quality Management (TQM) is one of the most important modern management systems in marketing, that help organizations to survive and remain competitive in the dynamic market with frequent changes. It assists them in gaining a competitive advantage, growth, and excellence compared to their competitors. To understand the impact of TQM on competitive advantage in economic companies, a study was conducted in Ooredoo Telecommunications Company. A questionnaire was designed and distributed to OOredoo' 75 employees in each of the departments of leadership, quality assurance, quality control, research and development, production, customer service, Similarly, resulting in the retrieval of 72 questionnaires. To analyze the descriptive results of the study, the SPSS software version 25 was used. Additionally, Structural Equation Modeling (SEM) with the help of Smart Pls4 software was utilized to test the study's hypotheses. The study concluded that there is an impact between total quality management and competitive advantage in Ooredoo company to different degrees. On this basis, the study recommended the need to implement the total quality management system at the level of all organizations and in various fields.

Keywords: total quality management, ISO system, competitive advantage, competitive strategies

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Authors: Musa Shu'aibu

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This paper centered on the abuse of secretarial profession by employers of labour. The paper further explains vividly the meaning of secretarial profession and that of a secretary. The paper also makes an attempt to explain the training of a secretary, duties and business attributes of a secretary. It further highlighted the personal attributes of a secretary, prospects of secretaries/secretarial profession and some abuses of the secretarial profession were discussed. It concluded that the rapid advancement in technology has changed today's offices which resulted in changing in the requirement of today's secretarial posts. Finally, recommendations were provided.

Keywords: abuse, employers, labour, profession

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Authors: Vimi Jham

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The banking sector has undergone tremendous change in all forms of service it provides to its customers. The efforts of the banks is to avoid customer defection and lead to customer satisfaction. The purpose of the study was to examine the linkages among the constructs such as customer perceived service quality, perceived service recovery quality and customer satisfaction in the banking industry. The moderating effect of negative brand perception due to service failure on recovery satisfaction were investigated. Random sampling methods are used to draw the sample from the population. Data was collected from 262 banking customers and were analyzed with the help of structural equation modelling approach using Smart PLS to understand the relationship among variables being studied. The results of the study contribute to the research by proving that customer service recovery satisfaction is dependent on customer perceived service quality and the moderating effect of negative brand perception due to service failure was insignificant.

Keywords: service recovery satisfaction, perceived service recovery quality, perceived service quality, structural equation modelling

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Authors: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: Nahid Tavakoli, Mohammad H. Yarmohammadian, Ali Samimi

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In earthquake situation, medical response communities such as field and referral hospitals are challenged with injured victims’ identification and tracking. In our project, it was developed a patient tracking platform (PTP) where first responders triage the patients with an electronic tag which report the location and some information of each patient during his/her movement. This platform includes: 1) near field communication (NFC) tags (ISO 14443), 2) smart mobile phones (Android-base version 4.2.2), 3) Base station laptops (Windows), 4) server software, 5) Android software to use by first responders, 5) disaster command software, and 6) system architecture. Our model has been completed through literature review, Delphi technique, focus group, design the platform, and implement in an earthquake exercise. This paper presents consideration for content, function, and technologies that must apply for patient tracking in medical emergencies situations. It is demonstrated the robustness of the patient tracking platform (PTP) in tracking 6 patients in a simulated earthquake situation in the yard of the relief and rescue department of Isfahan’s Red Crescent.

Keywords: test and evaluation, patient tracking platform, earthquake, simulation

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Gaurav Bansod, Swapnil Sutar, Abhijit Patil, Jagdish Patil

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This paper proposes an ultra-lightweight cipher NUX. NUX is a generalized Feistel network. It supports 128/80 bit key length and block length of 64 bit. For 128 bit key length, NUX needs only 1022 GEs which is less as compared to all existing cipher design. NUX design results into less footprint area and minimal memory size. This paper presents security analysis of NUX cipher design which shows cipher’s resistance against basic attacks like Linear and Differential Cryptanalysis. Advanced attacks like Biclique attack is also mounted on NUX cipher design. Two different F function in NUX cipher design results in high diffusion mechanism which generates large number of active S-boxes in minimum number of rounds. NUX cipher has total 31 rounds. NUX design will be best-suited design for critical application like smart grid, IoT, wireless sensor network, where memory size, footprint area and the power dissipation are the major constraints.

Keywords: lightweight cryptography, Feistel cipher, block cipher, IoT, encryption, embedded security, ubiquitous computing

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Authors: Sisira Edirippulige

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Background: Digital health education and training (DHET) is imperative for preparing current and future clinicians to work competently in digitally enabled environments. Despite rapid integration of digital health in modern health services, systematic education and training opportunities for health workers is still lacking. Objectives: This study aimed to investigate healthcare professionals’ perspectives and expectations regarding the knowledge, skills and competency needs in digital health for current and future healthcare workforce. Methods: A qualitative study design with semi-structured individual interviews was employed. A purposive sample method was adopted to collect relevant information from the health workers. Inductive thematic analysis was used to analyse data. Interviews were audio-recorded and transcribed verbatim. Consolidated Criteria for Reporting Qualitative Research (COREQ) was followed when we reported this study. Results: Two themes emerged while analysing the data: (1) what to teach in DHET and (2) how to teach DHET. Overall, healthcare professionals agreed that DHET is important for preparing current and future clinicians for working competently in digitally enabled environments. Knowledge relating to what is digital health, types of digital health, use of technology and human factors in digital health were considered as important to be taught in DHET. Skills relating to digital health consultations, clinical information system management and remote monitoring were considered important to be taught. Blended learning which combined e-learning and classroom-based teaching, simulation sessions and clinical rotations were suggested by healthcare professionals as optimal approaches to deliver the above-mentioned content. Conclusions: This study is the first of its kind to investigate health professionals’ perspectives and expectations relating to the knowledge, skills and competency needs in digital health for current and future healthcare workforce. Healthcare workers are keen to acquire relevant knowledge, skills and competencies related to digital health. Different modes of education delivery is of interest to fit in with busy schedule of health workers.

Keywords: digital health, telehealth, telemedicine, education, curriculum

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Authors: Ma. Dina Datiles Jimenez

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Service strategy and service Innovation has something to do with the success of the foodservice business. The foodservice business nowadays has become more competitive, and technology driven. This study aimed to determine and investigate the service innovation and strategies of the food service industry and the challenges during the pandemic to serve as the basis for a competitive advantage model. The study used mixed methods, including descriptive quantitative and qualitative methods. The Metro Manila foodservice managers were the target population of the study, which consisted of an estimated 1500 respondents from the selected cities. The assessment of service innovation for the following dimensions: product-related dimension; market-related dimension; process-related dimension; and organization-related dimension, when classified according to profile, was very large for age, gender, and educational attainment. When respondents are classified according to profile, the service strategy in terms of customer service strategy, after-sales service strategy, maintenance service strategy, research and development-oriented service strategy, and operational services strategy were all assessed with a very large extent of implementation. There was a significant difference in all four aspects of service innovation when classified based on age. However, for gender, only the market and process dimensions showed significant differences, while the product and organization conveyed no significant differences. Consequently, the evidence was not enough to prove that educational attainment differs from one another on the four aspects of service innovation. There was sufficient evidence to prove that the ages differ from one another in all aspects of service strategies. While gender and educational attainment showed no significant difference in the assessment of service strategies, Training on the trends in the foodservice industry during the pandemic is offered; technical maintenance is evident; the company allotted budget for outsourcing training; the quality control system; and online customer feedback were revealed as major indicators for service strategy. Fear of viruses, limited customers, a minimal work force, and low revenues were identified as challenges faced by the foodservice industry.

Keywords: foodservice industry, service innovation, service strategy, competitive advantage, sustainability, technology

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Authors: Ta-Huang Sun, Ming-Hao Hsieh, Min-Chuan Wang, Der-Jun Jan

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Electrochromism refers to the persistent and reversible change of optical properties by an applied voltage pulse. There are many transition metal oxides exhibiting electrochromism, e.g. oxides of W, Ni, Ir, V, Ti, Co and Mo. Organic materials especially some conducting polymers such as poly(aniline), poly(3, 4-propylene- dioxythiophene) also received much attention for electrochromic (EC) applications. Electrochromic materials attract considerable interest because of their potential applications, such as information displays, smart windows, variable reflectance mirrors, and variable-emittance thermal radiators. In this study, the EC characteristics are investigated on an all-solid-state EC device composed of a-WO₃ and Ni(OH)₂ with a Ta₂O₅ protective layer which is prepared by magnetron sputtering. It is found that the transmittance modulation increases with decreasing the film thickness of Ta₂O₅. On the other hand, the transmittance modulation is 57% as the Ni(OH)₂/ITO is prepared by the linear-sweep potential cycling of the sputter-deposited Ta₂O₅/NiO/ITO in a 0.5 M LiClO₄+H₂O electrolyte. However, when Ni(OH)₂/ITO is prepared by a 0.01 M HCl electrolyte, the transmittance modulation of EC device can be improved to 61%.

Keywords: electrochromic device, tungsten oxide, nickel, Ta₂O₅

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Authors: Ayesha Sanjana Kawser Parsha

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S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Hamed Mohammadi Mofarah, Mutalifu Abulikemu, Ghassan E. Jabbour

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Personal protective equipment (PPE) is finding increasing interest in incorporating silver nanoparticles (NPs) for various applications including microbial disinfection and shielding against electromagnetic waves. In this venue, we present an in situ reactive coating approach where silver nanoparticles are self-assembled on the surface of cotton yarn. The impacts of a variety of experimental parameters on the average size of the synthesized silver NPs were investigated. These include vacuum conditions, the concentration of the silver salt solution and reducer, temperature, and curing time. Silver NPs with an average size ranging from 10 to 50 nanometers were self-assembled as a result of careful regulation of such reaction conditions. The disinfection efficacy against the COVID surrogate virus of the functional textile reached a rate of 99.99%. On the other hand, the silver NPs decorated textile demonstrated an electromagnetic shielding ranging from 31 dB to 45 dB were achieved for the frequency range 8.2-12.4 GHz.

Keywords: antiviral, COVID, electromagnetic shielding, in-situ reactive coating, SARS CoV 2, silver nanoparticles, smart textile

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Authors: Adamu Mudi, Ibrahim Wahab Fawole, Abubakar Abba Kolo

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In this research paper, we present a microcontroller-based liquid level controller that identifies the various levels of a liquid, carries out certain actions, and is capable of communicating with the human being and other devices through the GSM network. This project is useful in ensuring that a liquid is not wasted. It also contributes to the internet of things paradigm, which is the future of the internet. The method used in this work includes designing the circuit and simulating it. The circuit is then implemented on a solderless breadboard, after which it is implemented on a strip board. A C++ computer program is developed and uploaded into the microcontroller. This program instructs the microcontroller on how to carry out its actions. In other to determine levels of the liquid, an ultrasonic wave is sent to the surface of the liquid similar to radar or the method for detecting the level of sea bed. Message is sent to the phone of the user similar to the way computers send messages to phones of GSM users. It is concluded that the routine of observing the levels of a liquid in a tank, refilling the tank when the liquid level is too low can be entirely handled by a programmable device without wastage of the liquid or bothering a human being with such tasks.

Keywords: Arduino Uno, HC-SR04 ultrasonic sensor, internet of things, IoT, SIM900 GSM module

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Authors: Ying Li, Yan Li

Abstract:

A new algorithm for single hidden layer feedforward neural networks (SLFN), Orthogonal Basis Extreme Learning (OBEL) algorithm, is proposed and the algorithm derivation is given in the paper. The algorithm can decide both the NNs parameters and the neuron number of hidden layer(s) during training while providing extreme fast learning speed. It will provide a practical way to develop NNs. The simulation results of function approximation showed that the algorithm is effective and feasible with good accuracy and adaptability.

Keywords: neural network, orthogonal basis extreme learning, function approximation

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Mohammad Parvaresh, Mahdi Babaee, Bahareh Arghand, Roushanak Fahimi Hanzaee, Davood Nourmohammadi

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Today, the intelligent network of water and wastewater as one of the key steps in realizing the smart city in the world. Use of pressure relief valves in urban water networks in order to reduce the pressure is necessary in Tehran city. But use these pressure relief valves lead to waste water, more power consumption, and environmental pollution because Tehran Province Water and Wastewater Co. use a quarter of industry 's electricity. In this regard, Tehran Province Water and Wastewater Co. identified solutions to reduce direct and indirect costs in energy use in the process of production, transmission and distribution of water because this company has extensive facilities and high capacity to realize green economy and industry. The aim of this study is to analyze the new project in water and wastewater industry to reach sustainable development.

Keywords: Tehran Province Water and Wastewater Company, water network efficiency, sustainable development, International Environmental Law

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Authors: Xinli Chi, Xiaoqi Wei

Abstract:

Background: Body-mind theory refers to the concept that the mind and body are interconnected; in this case, combining aerobic exercise and mindfulness-based training may be beneficial for mind-body health; however, there is limited evidence regarding their effects and potential mechanisms among Chinese university students. Therefore, the current study aims to examine the preliminary effects and feasibility of the combined intervention on depressive and insomnia symptoms, as well as to explore the underlying mechanisms. Methods: This is a two-arm pilot study of a randomized, controlled trial. Sixty-one Chinese university students were randomly allocated to 8-week combined intervention group (aerobic exercise plus mindfulness, N = 36) or control group (N = 36). In addition, 8 participants in combined intervention group were later volunteer to engage in semi-structured interview. The Self-Rating Depression Scale (SDS) and the Youth Self-Rating Insomnia Scales (YSIS) were used to measure depressive and insomnia symptoms, respectively. The intervention outcome and feasibility were tested by repeated-measures ANOVA, mediation model, and qualitative analysis. Results: The study included 31 participants in the intervention group and 30 participants in the control group, all of whom completed pre-test and post-test questionnaires. The results of the repeated-measures ANOVA showed that the combined intervention was effective in reducing depressive and insomnia symptoms among university students. Moreover, the mediation analysis suggested that improvement in insomnia symptoms might be a significant mechanism for the combined intervention. Qualitative analysis identified two main themes: “Helpful aspects of mind-body state” (including 7 sub-themes) and “Factors that influence the training effects” (including 3 sub-themes). Conclusions: The study confirmed the preliminary effect and feasibility of the combined intervention of mindfulness and aerobic exercise, while also exploring the potential mechanisms underlying this effect. Additionally, qualitative data provided valuable insights for optimizing future protocols.

Keywords: combined intervention, mindfulness, aerobic exercise, depressive symptoms, insomnia symptoms

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Authors: Yasser Y. Lenis, Amy Jo Montgomery, Diego F. Carrillo-Gonzalez

Abstract:

Introduction: The use of didactic instruments in different learning environments plays a pivotal role in enhancing the level of knowledge in veterinary science students. The direct instruction of basic animal reproduction concepts in students enrolled in veterinary medicine programs allows them to elucidate the biological and molecular mechanisms that perpetuate the animal species in an ecosystem. Therefore, universities must implement didactic strategies that facilitate the teaching and learning processes for students and, in turn, enrich learning environments. Objective: to evaluate the effect of the use of a didactic textbook on the level of theoretical knowledge in embryo-maternal recognition for veterinary medicine students. Methods: the participants (n=24) were divided into two experimental groups: control (Ctrl) and treatment (Treat). Both groups received 4 hours of theoretical training regarding the basic concepts in bovine embryo-maternal recognition. However, the Treat group was also exposed to a guided lecture and the activity play-to-learn from a cow reproduction didactic textbook. A pre-test and a post-test were applied to assess the prior and subsequent knowledge in the participants. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, a repeated measures model was applied where the effect of the intervention was considered. Results: no significant difference (p>0,05) was observed in the number of right answers for groups Ctrl (54,2%±12,7) and Treat (40,8%±16,8) in the pre-test. There was no difference (p>0,05) compering the number of right answers in Ctrl pre-test (54,2%±12,7) and post-test (60,8±18,8). However, the Treat group showed a significant (p>0,05) difference in the number of right answers when comparing pre-test (40,8%±16,8) and post-test (71,7%±14,7). Finally, after the theoretical training and the didactic activity in the Treat group, an increase of 10.9% (p<0,05) in the number of right answers was found when compared with the Ctrl group. Conclusion: the use of didactic tools that include guided lectures and activities like play-to-learn from a didactic textbook enhances the level of knowledge in an animal reproduction course for veterinary medicine students.

Keywords: animal reproduction, pedagogic, level of knowledge, learning environment

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