Search results for: support interference

Authors: Andrea Palazzo, Daniel Macek, Veronika Malinova

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Contour processing is the new technology challenge for architects and construction companies. The many advantages it promises make it one of the most interesting solutions for construction in terms of automation of building processes. The technology for 3D printing houses offers many application possibilities, from low-cost construction, to being considered by NASA for visionary projects as a good solution for building settlements on other planets. Another very important point is that clients, as architects, will no longer have many limits in design concerning ideas and creativity. The prices for real estate are constantly increasing and the lack of availability of construction materials as well as the speculation that has been created around it in 2021 is bringing prices to such a level that in the future it will be difficult for developers to find customers for these ultra-expensive homes. Hence, this paper starts with the introduction of 3D printing, which now has the potential to gain an important position in the market, becoming a valid alternative to the classic construction process. This technology is not only beneficial from an economic point of view but it is also a great opportunity to have an impact on the environment by reducing CO2 emissions. Further on in the article we will also understand if, after the COP 26 (2021 United Nations Climate Change Conference), world governments could also push towards building technologies that reduce the waste materials that are needed to be disposed of and at the same time reduce emissions with the contribution of governmental funds. This paper will give us insight on the multiple benefits of 3D printing and emphasize the importance of finding new solutions for materials that can be used by the printer. Therefore, based on the type of material, it will be possible to understand the compatibility with current regulations and how the authorities will be inclined to support this technology. This will help to enable the rise and development of this technology in Europe and in the rest of the world on actual housing projects and not only on prototypes.

Keywords: Additive manufacturing, building development building regulation, contour crafting, printing material.

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Authors: Berardina De Carolis, Giovanni Cozzolongo

Abstract:

In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.

Keywords: Ambient intelligence, agent-based systems, influence diagrams.

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

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A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

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Authors: Sang Su Lee, Sang Woo Lee, Yong Sung Jeon, Ki Young Kim

Abstract:

IPsec protocol[1] is a set of security extensions developed by the IETF and it provides privacy and authentication services at the IP layer by using modern cryptography. In this paper, we describe both of H/W and S/W architectures of our router system, SRS-10. The system is designed to support high performance routing and IPsec VPN. Especially, we used Cavium-s CN2560 processor to implement IPsec processing in inline-mode.

Keywords: IP, router, VPN, IPsec.

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Authors: G. H. B. Dilhari, A. A. D. T. Saparamadu

Abstract:

Sri Lanka is one of the prominent countries for the coir production. The coir is one of the by-products of the coconut and the coir industry is considered to be one of the traditional industries in Sri Lanka. Because of the inherent nature of the coir industry, labourers play a significant role in the coir production process. The study has analyzed the determinants of the income of the household level coir yarn labourers. The study was conducted in the Kumarakanda Grama Niladhari division. Simple random sampling was used to generate a sample of 100 household level coir yarn labourers and structured questionnaire, personal interviews, and discussion were performed to gather the required data. The obtained data were statistically analyzed by using Statistical Package for Social Science (SPSS) software. Mann-Whitney U and Kruskal-Wallis test were performed for mean comparison. The findings revealed that the household level coir yarn industry is dominated by the female workers and it was identified that fewer numbers of workers have engaged in this industry as the main occupation. In addition to that, elderly participation in the industry is higher than the younger participation and most of them have engaged in the industry as a source of extra income. Level of education, the methods of engagement, satisfaction, engagement in the industry by the next generation, support from the government, method of government support, working hours per day, employed as a main job, number of completed units per day, suffering from job related diseases and type of the diseases were related with income level of household level coir yarn laboures. The recommendations as to flourish in future includes, technological transformation for coir yarn production, strengthening the raw material base and regulating the raw material supply, introduction of new technologies, markets and training programmes, the establishment of the labourers’ association, the initiation of micro credit schemes and better consideration about the job oriented diseases.

Keywords: Coir, Income, Sri Lanka.

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Authors: Beata Ślusarczyk, Sebastian Kot

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In subjective terms, Polish SME sector occupies a prominent position in the national economic development, in which planning of the management strategies should be primarily based on identifying and meeting the innovation needs. As a research sample, there is chosen a printing sector of industry. SMEs share in printing sector in Poland is estimated at the level of 81% of all enterprises. In recent years, the printing industry achieved one of the highest levels of EU support in Poland. There is a relatively high increase in the development of technological innovations in equipment and the associated significant increase in production capacity. It can be also noticed that on average, every third enterprise belonging to the printing industry has implemented innovations, but not all of them effected in better economic results. Therefore, the aim of this article is to evaluate the impact of the implementation of innovation projects financed from the EU funds for performance of SMEs in the printing industry. As the results of research of EU funds co-financing effects on the development of innovation in the printing industry, it was specified that examined SMEs prefer to implement product innovation to receive a grant to the project at a level between 40% to 60%, the remaining part of the investment is usually covered with equity. The most common type of innovation had indicated a single implementation, related only to the change in process, technology, or organization. The relationship between variables of the EU funds and management of innovative activities was verified. It has been observed that the identified variables arising from the support in a form of the EU funds had a positive effect on the level of earned revenue, the increase in margin and in increase in employment as well. It was confirmed that the implemented innovations supported by the European funds have a positive impact on the performance of the printing companies. Although there is a risk that due to the decreasing demand for printing services such a high level of funding the companies in this sector will significantly increase competition in the long term, that may also contribute to the economic problems of the enterprises belonging to the analyzed branch.

Keywords: Innovations, SMEs, performance, results.

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Authors: Rehan Jamil, Irfan Jamil, Ming Li, Zhao Jinquan

Abstract:

Energy is the important source for the development of the society and it‘s the basic support of national economy and the base for human living. As the development of economy, abrupt increase of population and continuous improvement of living standards, the demand of energy increases continuously, which caused the impetuous scramble of energy source in the world, and urged the attention of the countries for current status and development trends of energy.

Keywords: Energy, Energy Supply Situation, Energy Production & Consumption.

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Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: Hydrofining, kinetic, modeling, optimization.

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Authors: Hideki.Kobayashi, Hiroshi.Osada

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The service industry accounts for about 70% of GDP of Japan, and the importance of the service innovation is pointed out. The importance of the system use and the support service increases in the information system that is one of the service industries. However, because the system is not used enough, the purpose for which it was originally intended cannot often be achieved in the CRM system. To promote the use of the system, the effective service method is needed. It is thought that the service model's making and the clarification of the success factors are necessary to improve the operation service of the CRM system. In this research the model of the operation service in the CRM system is made.

Keywords: Information system, Operation service, Serviceinnovation, Solution

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Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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Authors: Anna V. Zhdanova, Uwe Keller

Abstract:

We summarize information that facilitates choosing an ontology language for knowledge intensive applications. This paper is a short version of the ontology language state-of-the-art and evolution analysis carried out for choosing an ontology language in the IST Esperonto project. At first, we analyze changes and evolution that took place in the filed of Semantic Web languages during the last years, in particular, around the ontology languages of the RDF/S and OWL family. Second, we present current trends in development of Semantic Web languages, in particular, rule support extensions for Semantic Web languages and emerging ontology languages such as WSMO languages.

Keywords: OWL, RDF/S, Semantic Web Languages, WSML

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Authors: Tsuyoshi Okita, Tatsuya Niwa

Abstract:

For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem.

Keywords: Formal language, statistical inference problem, reduction.

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Authors: A. Faro, D. Giordano, M. Pennisi, G. Scarciofalo, C. Spampinato, F. Tramontana

Abstract:

The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia and to measure the positive effect, if any, of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.

Keywords: TMS, SIVD, Electromiography , Fuzzy Logic.

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Authors: Changjin Xu

Abstract:

In this paper, we consider a two-neuron system with time-delayed connections between neurons. By analyzing the associated characteristic transcendental equation, its linear stability is investigated and Hopf bifurcation is demonstrated. Some explicit formulae for determining the stability and the direction of the Hopf bifurcation periodic solutions bifurcating from Hopf bifurcations are obtained by using the normal form theory and center manifold theory. Some numerical simulation results are given to support the theoretical predictions. Finally, main conclusions are given.

Keywords: Two-neuron system, delay, stability, Hopf bifurcation.

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

Abstract:

Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: Artificial Neural Network, Decision Support System, drug abuse, drug addiction, Multilayer Perceptron.

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Authors: Kejun Zhuang

Abstract:

In this paper, a delayed physiological control system is investigated. The sufficient conditions for stability of positive equilibrium and existence of local Hopf bifurcation are derived. Furthermore, global existence of periodic solutions is established by using the global Hopf bifurcation theory. Finally, numerical examples are given to support the theoretical analysis.

Keywords: Physiological control system, global Hopf bifurcation, periodic solutions.

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Authors: Hasanul Ferdaus, Sazzadur Rahman, Kamrul Islam

Abstract:

With the rapid usage of portable devices mobility in IP networks becomes more important issue in the recent years. IETF standardized Mobile IP that works in Network Layer, which involves tunneling of IP packets from HA to Foreign Agent. Mobile IP suffers many problems of Triangular Routing, conflict with private addressing scheme, increase in load in HA, need of permanent home IP address, tunneling itself, and so on. In this paper, we proposed mobility management in Application Layer protocol SIP and show some comparative analysis between Mobile IP and SIP in context of mobility.

Keywords: Mobility, mobile IP, SIP, tunneling.

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Authors: Dhany Saputra, Dayang R. A. Rambli, Oi Mean Foong

Abstract:

In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use sufficient data structure for Seq-Tree framework and separator database to reduce the execution time and memory usage. Thus, with I-PrefixSpan there is no in-memory database stored after index set is constructed. The experimental result shows that using Java 2, this method improves the speed of PrefixSpan up to almost two orders of magnitude as well as the memory usage to more than one order of magnitude.

Keywords: ArrayList, ArrayIntList, minimum support, sequence database, sequential patterns.

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Authors: Prisa Damrongsiri, Kittinan Pongpianskul, Mario Kubek, Herwig Unger

Abstract:

Apps are today the most important possibility to adapt mobile phones and computers to fulfill the special needs of their users. Location- and context-sensitive programs are hereby the key to support the interaction of the user with his/her environment and also to avoid an overload with a plenty of dispensable information. The contribution shows, how a trusted, secure and really bi-directional communication and interaction among users and their environment can be established and used, e.g. in the field of home automation.

Keywords: Apps, context-sensitive, location-sensitive, selfconfiguration, mobile computing, smart home.

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Authors: Ahmad Alshammari, Abdulaziz Bagabas

Abstract:

Rhodamine B (RB) is a toxic dye used extensively in textile industry, which must be remediated before its drainage to environment. In the present study, supported gold nanoparticles on commercially available titania and zincite were successfully prepared and then their activity on the photodegradation of RB under UV A light irradiation were evaluated. The synthesized photocatalysts were characterized by ICP, BET, XRD, and TEM. Kinetic results showed that Au/TiO2 was an inferior photocatalyst to Au/ZnO. This observation could be attributed to the strong reflection of UV irradiation by gold nanoparticles over TiO2 support.

Keywords: Supported AuNPs, Semiconductor photocatalyst, Photodegradation, Rhodamine B.

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Authors: Chun-Lang Chang

Abstract:

According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

Keywords: Data mining, Hearing impairment, Logistic regression analysis, Support vector machines

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Authors: Ling-fei Xu, Qi Zhao, Yan-ru Chen, Mu-chun Zhou, Meng Zhang, Shi-xue Xu

Abstract:

SVM ( Support Vector Machine ) is a new method in the artificial neural network ( ANN ). In the steel making, how to use computer to predict the end point of BOF accuracy is a great problem. A lot of method and theory have been claimed, but most of the results is not satisfied. Now the hot topic in the BOF end point predicting is to use optical way the predict the end point in the BOF. And we found that there exist some regular in the characteristic curve of the flame from the mouse of pudding. And we can use SVM to predict end point of the BOF, just single spectrum intensity should be required as the input parameter. Moreover, its compatibility for the input space is better than the BP network.

Keywords: SVM, predict, BOF, single spectrum intensity.

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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Authors: V. Holeva, V. Aliki Nikopoulou, P. Kechayas, M. Dialechti Kerasidou, M. Papadopoulou, G. A. Papakostas, V. G. Kaburlasos, A. Evangeliou

Abstract:

Cognitive Behavioral Therapy (CBT) has been proven an effective tool to address anger and anxiety issues in children and adolescents with Autism Spectrum Disorders (ASD). Robot-enhanced therapy has been used in psychosocial and educational interventions for children with ASD with promising results. Whenever CBT-based techniques were incorporated in robot-based interventions, they were mainly performed in group sessions. Objectives: The study’s main objective was the implementation and evaluation of the effectiveness of a relaxation training intervention for children with ASD, delivered by the social robot NAO. Methods: 20 children (aged 7–12 years) were randomly assigned to 16 sessions of relaxation training implemented twice a week. Two groups were formed: the NAO group (children participated in individual sessions with the support of NAO) and the control group (children participated in individual sessions with the support of the therapist only). Participants received three different relaxation scenarios of increasing difficulty (a breathing scenario, a progressive muscle relaxation scenario and a body scan medication scenario), as well as related homework sheets for practicing. Pre- and post-intervention assessments were conducted using the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire for parents (SDQ-P). Participants were also asked to complete an open-ended questionnaire to evaluate the effectiveness of the training. Parents’ satisfaction was evaluated via a questionnaire and children satisfaction was assessed by a thermometer scale. Results: The study supports the use of relaxation training with the NAO robot as instructor for children with ASD. Parents of enrolled children reported high levels of satisfaction and provided positive ratings of the training acceptability. Children in the NAO group presented greater motivation to complete homework and adopt the learned techniques at home. Conclusions: Relaxation training could be effectively integrated in robot-assisted protocols to help children with ASD regulate emotions and develop self-control.

Keywords: Autism spectrum disorders, CBT, children relaxation training, robot-assisted therapy.

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Authors: Nebi Gedik, Ayten Atasoy

Abstract:

This paper investigates successful sub-bands of wave atom transform via classification of mammograms, when the coefficients of sub-bands are used as features. A computer-aided diagnosis system is constructed by using wave atom transform, support vector machine and k-nearest neighbor classifiers. Two-class classification is studied in detail using two data sets, separately. The successful sub-bands are determined according to the accuracy rates, coefficient numbers, and sensitivity rates.

Keywords: Breast cancer, wave atom transform, SVM, k-NN.

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Authors: Ivana Nacinovic, Lovorka Galetic, Nevenka Cavlek

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Continuous innovation is becoming a necessity if firms want to stay competitive. Different factors influence the rate of innovation in a firm, among which corporate culture has often been recognized among the most important factors. In this paper we argue that the development of corporate culture that will support and foster innovation must be accompanied with an appropriate reward system. A research conducted among Croatian firms showed that a statistically significant relationship exists among corporate culture that supports innovations and reward system features.

Keywords: Corporate culture, innovation, reward systems, Croatia.

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Authors: M. R. Yadav, A. K. Sharma, B. S. Thakur

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The purpose of this paper is to present a best proximity point theorems through rational expression for a combination of contraction condition, Kannan and Chatterjea nonlinear cyclic contraction in what we call MT-K and MT-C rational cyclic contraction. Some best proximity point theorems for a mapping satisfy these conditions have been established in metric spaces. We also give some examples to support our work.

Keywords: Cyclic contraction, rational cyclic contraction, best proximity point and complete metric space.

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Authors: T. Niracharapa

Abstract:

The research studied and examined the competitiveness of the animation industry in Thailand. Data were collected based on articles, related reports and websites, news, research, and interviews of key persons from both public and private sectors. The diamond model was used to analyze the study. The major factor driving the Thai animation industry forward includes a quality workforce, their creativity and strong associations. However, discontinuity in government support, infrastructure, marketing, IP creation and financial constraints were factors keeping the Thai animation industry less competitive in the global market.

Keywords: Animation, competitiveness, digital content, Thailand.

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Authors: Adilson M. Enes, Juliana A. Fracarolli, Inácio M. Dal Fabbro, Silvestre Rodrigues

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This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.

Keywords: Biospeckle, papaya, mechanical damages, vegetable bruising.

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Authors: Rekha V. Dundur , M.V.Latte, S.Y. Kulkarni, M.K.Venkatesha

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The advent of multi-million gate Field Programmable Gate Arrays (FPGAs) with hardware support for multiplication opens an opportunity to recreate a significant portion of the front end of a human cochlea using this technology. In this paper we describe the implementation of the cochlear filter and show that it is entirely suited to a single device XC3S500 FPGA implementation .The filter gave a good fit to real time data with efficiency of hardware usage.

Keywords: Cochlea, FPGA, IIR (Infinite Impulse Response), Multiplier.

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