Search results for: task demands

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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Authors: Vaclav Mentl, Josef Volak

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In many industrial applications, materials are subjected to degradation of mechanical properties as a result of real service conditions, temperature, cyclic loading, humidity or other corrosive media, irradiation, their combination etc. The assessment of the remaining lifetime of components and structures is commonly based on correlated procedures including numerous destructive, non-destructive and mathematical techniques that should guarantee reasonably precise assessment of the current damage extent of materials in question and the remaining lifetime evaluation of the component under consideration. The answers to demands of customers to extend the lifetime of existing components beyond their original design life must be based on detailed assessment of the current degradation extent, what can be rarely realised by means of traditional mechanical (standardised) tests that need relatively large volumes of representative material for the test specimen manufacturing. This fact accelerated the research of miniaturised test specimen that can be sampled non-invasively from the component.

Keywords: small punch test, correlation, creep, mechanical properties

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud computing is becoming more and more matured over the last few years and consequently the demands for better cloud services is increasing rapidly. One of the research topics to improve cloud services is the desktop computing in virtualized environment. This paper aims at the development of an adaptive virtual desktop service in cloud computing platform based on our previous research on the virtualization technology. We implement cloud virtual desktop and application software streaming technology that make it possible for providing Virtual Desktop as a Service (VDaaS). Given the development of remote desktop virtualization, it allows shifting the user’s desktop from the traditional PC environment to the cloud-enabled environment, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. Users no longer need to burden the platform maintenances and drastically reduces the overall cost of hardware and software licenses. Moreover, this flexible remote desktop service represents the next significant step to the mobile workplace, and it lets users access their desktop environments from virtually anywhere.

Keywords: cloud computing, virtualization, virtual desktop, VDaaS

Procedia PDF Downloads 269

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

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

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

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Authors: L. Mathew, D. Thomas

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Qatar is a desert country with scarce fresh water resources, low rainfall and very high evaporation rate. It meets the majority of its water requirement through desalination process which is very expensive. Pressures are expected to mount on account of high population growth rate and demands posed by being the venue for 2022 FIFA World cup. This study contributes towards advancing the knowledge of the factors affecting sustainable water consumption in water-challenged societies by examining the case of Doha, Qatar. Survey research methods have been predominantly used for this research. Surveys were conducted using self-administered questionnaires. Focused group interviews and personal interviews with Qatar’s residents were also used to obtain deeper insights. Salient socio-cultural factors that drive the water consumption behavior of the public and which in turn affect sustainable water management practices are determined. Suggestions for reducing water consumption as well as fiscal and punitive measures to curb overuse and misuse of water are also identified.

Keywords: Middle East, Qatar, water consumption, water management, sustainability

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Authors: S. Akinde, Jubril Olatunbosun

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In recent years, most of the urban centers in Nigeria are fast experiencing housing problems such as unaffordable housing and environmental challenges, all of which determine the nature of housing quality. The population continues to increase and the demand for quality housing increases probably at the same rate. Several kinds of houses serve various purposes; the objectives of the low cost housing schemes as the name suggests is to make houses quality to both the middle and lower classes of people in Lagos. A casual look into the study area of Iba Low Cost Housing Estate and the Unity Low Cost Housing Estate, Ojo and Alimosho respectively in Lagos State have shown a huge demands for houses. The study area boasts of a large population all engaged in various commercial activities with income at various levels. It would be fair to say that these people are mainly of the middle class and lower class. This means the low cost housing scheme truly serves these purposes. A Low Cost Housing Scheme of Iba which is publicly owned and Low Cost Housing Scheme of Unity Estate (UE) is privately owned.  

Keywords: housing, residential quality, low cost housing scheme, public, private estates

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Authors: Manirath Wongsim

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Wen-Jye Shyr, Chun-Yuan Chang, Bo-Lin Wei, Chia-Ming Lin

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The task of creating an augmented reality technology was described in this study to give operators a user interface that might be a part of an automated storage and retrieval system. Its objective was to give graduate engineering and technology students a system of tools with which to experiment with the creation of augmented reality technologies. To collect and analyze data for maintenance applications, the students used augmented reality technology. Our findings support the evolution of artificial intelligence towards Industry 4.0 practices and the planned Industry 4.0 research stream. Important first insights into the study's effects on student learning were presented.

Keywords: augmented reality, storage and retrieval system, user interface, programmable logic controller

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Authors: Rimac Smiljanic Ana, Pepur Sandra, Bulog Ivana

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Financial decision-making in the household is not simple, and it demands that the decision-maker has proper knowledge and skills. Usually, high uncertainty, risk, and stress surround household financial decision-making since it is extremely important and critical for household wealth accumulation and for the well-being of all household members. Generally, skilful people tend to have higher confidence in certain tasks they perform, and they achieve better results. Therefore, in the household context, the possession of certain skills by the ones who make financial decisions for the household is of particular importance. This paper addresses financial literacy as an important skill for household decision-making. Apart from financial literacy, the paper also considers other factors, such as employment, education, and age, as significant for household financial decision-making. The analysis is based on quantitative individual-level survey data. The data collection was conducted during January and February 2021 in Croatia through an online survey. To reach a wide variety of participants, the snowball sampling method was used. The result revealed interesting and somewhat puzzling results. Our results point to the importance of financial literacy skills for household decision-making.

Keywords: skill, financial literacy, decision-making, household financijal decision making

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

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Authors: John Gray, Andy Smith, Hazel James

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With the introduction of projects such as GP referral and other medical exercise schemes, there has been a shift in the cosmology underpinning exercise leadership. That is, the knowledge base of exercise leaders, specifically personal trainers, has moved from a cosmology based on aesthetic and physical fitness demands to one requiring interaction with the dominant biomedical model underpinning contemporary medicine. In line with this shift research has demonstrated that personal trainer education has aligned itself to a biotechnological model. However, whilst there is a need to examine exercise as medicine, and consider the role of personal trainers as prescribers of these interventions, the possible issues surrounding the growing medicalization of the exercise cosmology have not been explored. Using a phenomenological methodology, and the novel approach of photo-elicitation, this research examined the practices of successful personal trainers. The findings highlight that a growing focus on an iatro-biological based scientific process of exercise prescription may prove problematical. Through the development of a model of practitioner-based knowledge, it is argued there is a possible growing disconnection between the theoretical basis of exercise science and the working cosmology of exercise practitioners.

Keywords: biomedicine, cosmology, personal training, photo-elicitation

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Authors: S. Abou El-Azm, U. Kruchonak, M. Gostkin, A. Guskov, A. Zhemchugov

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Semiconductor detectors are widely used in nuclear physics and high-energy physics experiments. The application of semiconductor detectors could be limited by their ultimate radiation resistance. The increase of radiation defects concentration leads to significant degradation of the working parameters of semiconductor detectors. The investigation of radiation defects properties in order to enhance the radiation hardness of semiconductor detectors is an important task for the successful implementation of a number of nuclear physics experiments; we presented some information about radiation hardness materials like diamond, sapphire and CdTe. Also, the results of measurements I-V characteristics, charge collection efficiency and its dependence on the bias voltage for different doses of high resistivity (GaAs: Cr) and Si at LINAC-200 accelerator and reactor IBR-2 are presented.

Keywords: semiconductor detectors, radiation hardness, GaAs, Si, CCE, I-V, C-V

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Authors: Abolfazl Hosseinpour, Javad Marzbanrad

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In this research, the topology and shape optimization of a Macpherson control arm has been accomplished to achieve lighter weight. Present automotive market demands low cost and light weight component to meet the need of fuel efficient and cost effective vehicle. This in turn gives the rise to more effective use of materials for automotive parts which can reduce the mass of vehicle. Since automotive components are under dynamic loads which cause fatigue damage, considering fatigue criteria seems to be essential in designing automotive components. At first, in order to create severe loading condition for control arm, some rough roads are generated through power spectral density. Then, the most critical loading conditions are obtained through multibody dynamics analysis of a full vehicle model. Then, the topology optimization is performed based on fatigue life criterion using HyperMesh software, which resulted to 50 percent mass reduction. In the next step a CAD model is created using CATIA software and shape optimization is performed to achieve accurate dimensions with less mass.

Keywords: topology optimization, shape optimization, fatigue life, MacPherson control arm

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Authors: H. Ucar, U. Aridogan

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Composite structures become intriguing for the design of aerospace, automotive and marine applications due to weight reduction, corrosion resistance and radar signature reduction demands and requirements. Studies on piezoelectric ceramic transducers (PZT) for diagnostics and health monitoring have gained attention for their sensing capabilities, however PZT structures are prone to fail in case of heavy operational loads. In this paper, we develop a piezo-based Glass Fiber Reinforced Polymer (GFRP) composite finite element (FE) model, validate with experimental setup, and identify the applicability and limitations of PZTs for a marine application. A case study is conducted to assess the piezo-based sensing capabilities in a representative marine composite structure. A FE model of the composite structure combined with PZT patches is developed, afterwards the response and functionality are investigated according to the sea conditions. Results of this study clearly indicate the blockers and critical aspects towards industrialization and wide-range use of PZTs for marine composite applications.

Keywords: FRP composite, operational challenges, piezoelectric transducers, FE modeling

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

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Authors: Perminderjit Singh, Sukhvir Singh

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Total Quality Management (TQM) refers to management methods used to enhance quality and productivity in business organizations. Total Quality Management (TQM) has become a frequently used term in discussions concerning quality. Total Quality management has brought rise in demands on the organizations policy and the customers have gained more importance in the organizations focus. TQM is considered as an important management tool, which helps the organizations to satisfy their customers. In present research critical success factors includes management commitment, customer satisfaction, continuous improvement, work culture and environment, supplier quality management, training and development, employee satisfaction and product/process design are studied. A questionnaire is developed to implement these critical success factors in implementation of total quality management in Indian industry. Questionnaires filled by consulting different industrial organizations. Data collected from questionnaires is analyzed by descriptive and importance indexes.

Keywords: total quality management, critical success factor, employee satisfaction, supplier quality management, customer focus, quality information, quality measurement

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Authors: Roshni Raha, Karthikeyan S.

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The world's largest livestock population resides in India. Existing strategies must be modified to increase the production of livestock and their by-products in order to meet the demands of the growing human population. Even though India leads the world in both milk production and the number of cows, average production is not very healthy and productive. This may be due to the animals' poor nutrition caused by a chronic under-availability of high-quality fodder and feed. This article explores Azolla pinnata to be a promising source to produce high-quality unconventional feed and fodder for effective livestock production and good quality breeding in India. This article is an exploratory study using a literature survey and experimentation analysis. In the realm of agri-biotechnology, azolla sp gained attention for helping farmers achieve sustainability, having minimal land requirements, and serving as a feed element that doesn't compete with human food sources. It has high methionine content, which is a good source of protein. It can be easily digested as the lignin content is low. It has high antioxidants and vitamins like beta carotene, vitamin A, and vitamin B12. Using this concept, the paper aims to investigate and develop a model of using azolla plants as a novel, high-potential feed source to combat the problems of low production and poor quality of animals in India. A representative sample of animal feed is collected where azolla is added. The sample is ground into a fine powder using mortar. PITC (phenylisothiocyanate) is added to derivatize the amino acids. The sample is analyzed using HPLC (High-Performance Liquid Chromatography) to measure the amino acids and monitor the protein content of the sample feed. The amino acid measurements from HPLC are converted to milligrams per gram of protein using the method of amino acid profiling via a set of calculations. The amino acid profile data is then obtained to validate the proximate results of nutrient enhancement of the composition of azolla in the sample. Based on the proximate composition of azolla meal, the enhancement results shown were higher compared to the standard values of normal fodder supplements indicating the feed to be much richer and denser in nutrient supply. Thus azolla fed sample proved to be a promising source for animal fodder. This would in turn lead to higher production and a good breed of animals that would help to meet the economic demands of the growing Indian population. Azolla plants have no side effects and can be considered as safe and effective to be immersed in the animal feed. One area of future research could begin with the upstream scaling strategy of azolla plants in India. This could involve introducing several bioreactor types for its commercial production. Since azolla sp has been proved in this paper as a promising source for high quality animal feed and fodder, large scale production of azolla plants will help to make the process much quicker, more efficient and easily accessible. Labor expenses will also be reduced by employing bioreactors for large-scale manufacturing.

Keywords: azolla, fodder, nutrient, protein

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Authors: Fereshteh Nazeri Bahadori

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In today's competitive environment, any company that aims to operate in a market, whether industrial or consumer markets, must know that it cannot address all the tastes and demands of customers at once and serve them all. The study of consumer memory is considered an important subject in marketing research, and many companies have conducted studies on this subject and the factors affecting it due to its importance. Therefore, the current study tries to investigate the relationship between consumers' attention, literacy, and memory. Memory has a very close relationship with learning. Memory is the collection of all the information that we have understood and stored. One of the important subjects in consumer behavior is information processing by the consumer. One of the important factors in information processing is the mental involvement of the consumer, which has attracted a lot of attention in the past two decades. Since consumers are the turning point of all marketing activities, successful marketing begins with understanding why and how consumers behave. Therefore, in the current study, the role of executive attention and literacy on consumers' memory has been investigated. The results showed that executive attention and literacy would play a significant role in the long-term and short-term memory of consumers.

Keywords: literacy, consumer memory, executive attention, psychology of consumer behavior

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Authors: D. Y. Fong, C. Y. Kuo, Y. T. Chiang, W. C. Lin

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Objectives: Qigong is an ancient Chinese practice in pursuit of a healthier body and a more peaceful mindset. It emphasizes on the restoration of vital energy (Qi) in body, mind, and spirit. The practice is the combination of gentle movements and mild breathing which help the doers reach the condition of tranquility. On account of the features of Qigong, first, we use cross-sectional methodology to compare the differences among the varied levels of Qigong practitioners on cognitive function with event-related potential (ERP) and electroencephalography (EEG). Second, we use the longitudinal methodology to explore the effects on the Qigong trainees for pretest and posttest on ERP and EEG. Current study adopts Attentional Network Test (ANT) task to examine the participants’ cognitive function, and aging-related researches demonstrated a declined tread on the cognition in older adults and exercise might ameliorate the deterioration. Qigong exercise integrates physical posture (muscle strength), breathing technique (aerobic ability) and focused intention (attention) that researchers hypothesize it might improve the cognitive function in aging adults. Method: Sixty participants were involved in this study, including 20 young adults (21.65±2.41 y) with normal physical activity (YA), 20 Qigong experts (60.69 ± 12.42 y) with over 7 years Qigong practice experience (QE), and 20 normal and healthy adults (52.90±12.37 y) with no Qigong practice experience as experimental group (EG). The EG participants took Qigong classes 2 times a week and 2 hours per time for 24 weeks with the purpose of examining the effect of Qigong intervention on cognitive function. ANT tasks (alert network, orient network, and executive control) were adopted to evaluate participants’ cognitive function via ERP’s P300 components and P300 amplitude topography. Results: Behavioral data: 1.The reaction time (RT) of YA is faster than the other two groups, and EG was faster than QE in the cue and flanker conditions of ANT task. 2. The RT of posttest was faster than pretest in EG in the cue and flanker conditions. 3. No difference among the three groups on orient, alert, and execute control networks. ERP data: 1. P300 amplitude detection in QE was larger than EG at Fz electrode in orient, alert, and execute control networks. 2. P300 amplitude in EG was larger at pretest than posttest on the orient network. 3. P300 Latency revealed no difference among the three groups in the three networks. Conclusion: Taken together these findings, they provide neuro-electrical evidence that older adults involved in Qigong practice may develop a more overall compensatory mechanism and also benefit the performance of behavior.

Keywords: Qigong, cognitive function, aging, event-related potential (ERP)

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Authors: Betül Demirbağ, Nesrin Demir

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As a developmental period, early adulthood has a vital role in romantic relationships in young adult's life. lt's known that in this period, satisfaction of individual needs such as affiliation is essential for well-functioning and to be succeeded in sequent developmental task. Romantic relationships have an expected association with attachment style. But it's needed to get more information about indicators of romantic relationships in different cultural backgrounds. in this research it's aimed to investigate whether there is a relationship between romantic relationship beliefs and Ego identity status and also other possible indicators such as gender, age, socioeconomic status. Participants were undergraduate students training in various programs in Education Faculty in Adiyaman University. As data collection tool, Romantic Relationship Beliefs scale and Ego Identity Process Questionnaire which was adapted into Turkish were used. Results were discussed in the relevant literature.

Keywords: ego identity, romantic relationships, university counseling

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Authors: A. Hol

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21^st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation

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Authors: Taleb Hosni Abderrahmane, Berga Abdelmadjid

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The development of numerical analysis and its application to geomechanics problems have provided geotechnical engineers with extremely powerful tools. One of the most important problems in geotechnical engineering is the slope stability assessment. It is a very difficult task due to several aspects such the nature of the problem, experimental consideration, monitoring, controlling, and assessment. The main objective of this paper is to perform a comparative numerical study between the following methods: The Limit Equilibrium (LEM), Finite Element (FEM), Limit Analysis (LAM) and Distinct Element (DEM). The comparison is conducted in terms of the safety factors and the critical slip surfaces. Through the results, we see the feasibility to analyse slope stability by many methods.

Keywords: comparison, factor of safety, geomechanics, numerical methods, slope analysis, slip surfaces

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Authors: Nishant Singh, Christian Huyck, Vaibhav Gandhi, Alexander Jones

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A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Keywords: cell assembly, force sensitive resistor, robot, spiking neuron

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Authors: Robert Gilliland

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In any organization, a potential issue can arise and become a problem when management deviates from the standard norms set in the system development process of an IT system and the policies that pertain to it. In these instances, cybersecurity is a big challenge that organizations have to face in safeguarding the data that they generate and use. When a new idea, task, or process begins, specific standards must be followed, along with the policies and procedures that ensure the safeguard of data in the information system within the company. A good IT Strategy and Policy should have individuals who are in charge of overseeing the design, development, implementation, and auditing of these policies. Auditors are people who check to make sure that the issue conforms with the plan that is in place. Management has the ability through the role of the manager to potentially abuse power is given and to direct specific ideas, events, projects, and outcomes that are contrary to the vision or goals of the company.

Keywords: strategic policy, policy management, new policy, strategic planning

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Authors: Alexandre Barbosa de Almeida, Telma Woerle de Lima Soares

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Protein structure prediction is a challenging task in the bioinformatics field. The biological function of all proteins majorly relies on the shape of their three-dimensional conformational structure, but less than 1% of all known proteins in the world have their structure solved. This work proposes a deep learning model to address this problem, attempting to predict some aspects of the protein conformations. Throughout a process of multiobjective dominance, a recurrent neural network was trained to abstract the particular bias of each individual multiobjective algorithm, generating a heuristic that could be useful to predict some of the relevant aspects of the three-dimensional conformation process formation, known as protein folding.

Keywords: Ab initio heuristic modeling, multiobjective optimization, protein structure prediction, recurrent neural network

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Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

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The coaxial transformer-coupled push-pull circuitry has been used widely in HF and VHF amplifiers for many decades without significant changes in the topology of the transformers. Basic changes over the years concerned the construction and turns ratio of the transformers as has been imposed upon the newer technologies active devices demands. The balun transmission line transformers applied in push-pull amplifiers enable input/output impedance transformation, but are mainly used to convert the balanced output into unbalanced and the input unbalanced into balanced. A simple and affordable alternative solution over the traditional coaxial transformer is the coreless planar balun. A key advantage over the traditional approach lies in the high specifications repeatability; simplifying the amplifier construction requirements as the planar balun constitutes an integrated part of the PCB copper layout. This paper presents the performance analysis of a planar LDMOS MRFE6VP5600 Push-Pull amplifier that enables robust operation in Band III, DVB-T, DVB-T2 standards but functions equally well in Band II, for DRM+ new generation transmitters.

Keywords: amplifier, balun, complex impedance, LDMOS, planar-transformers

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Authors: Khaled Shaaban

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Distracted driving, which includes anything that distracts a driver from the main task of driving, is one of the main causes of traffic accidents in modern societies. The objective of this research was to understand the type of activities that young drivers perform while driving in Qatar and to identify which activities cause the most distraction to the driver based on their experience. The data was collected through administered questionnaires in the city of Doha, Qatar. According to the participants, the majority reported that they use their cell phone all the time or occasionally while driving. Other significantly cited activities while driving included listening to music or radio, talking with passengers, and eating, drinking or smoking. When asked about the activities that distract the driver, using cell phone was listed as the most distracting activity followed by mental activities and adjusting GPS and audio device vehicle.

Keywords: driver distraction, young drivers, cell phone use, Qatar

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Authors: Druzhinenko-Silhan Daria, Metz Claire

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In this paper, we introduce the findings of the "Conjugal violence: mothers' parenting and court decisions" (VIC-PADEJ) study, focusing on the motherhood experiences of domestic violence victims. Utilizing a longitudinal research protocol that encompassed clinical interviews, projective methods, and various questionnaires, we detail the outcomes derived from seven clinical interviews with mothers alongside a comprehensive analysis. The findings reveal a pronounced decline in security and an imperative need for structuring both social and internal realities. The convergence of these findings indicates that parenting, post-experiencing domestic violence, may become an unattainable task due to the deficiency of internal resources.

Keywords: domestic violence, parenthood, mothers victims, projective methods, longitudinal research, alceste analysis

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

Procedia PDF Downloads 91