Search results for: adaptive virtual reality training

Authors: Hadjer Messabih

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The M’zab architecture has preserved its identity that was able to endure for centuries conserving practically the same way of life and the same building techniques since the 11th century. Even more, the newly built ksar Tafilelt is also designed to meet the local tradition. In 1996, a community led project was initiated to build a “new ksar” named Tafilelt based on a traditional form of community-led cooperative housing. It is a unique experience in the field of community housing that reproduces traditional architectural patterns while addressing contemporary ways of life with their expected modern comfort. This research is based on the hypothesis that the process of producing ksar Tafilelt is culturally responsive to a conservative community that was characterized by certain values which were transmitted to this ksar manifesting as cultural continuity. It aims at investigating what type of cultural continuity manifests itself in the co-production of ksar Tafilelt and the way the settlement and its houses are produced and inhabited, as well as the new emerging values and adaptive transition in social relations. The research methodology is based on a combination of questionnaires, in depth interviews, photography, and site visit to record and demonstrate how these buildings respond to peoples’ needs. Post Occupancy Evaluation (POE) is also employed in order to understand the lessons that can be learned from this project. Finally, this study proves that the cultural continuity that was transmitted from the Ibadi community is sill manifested in ksar Tafilelt, which provided strong religious bonds and a strong sense of community. The research findings have resulted in a number of lessons and principles that can be learnt from the project of ksar Tafilelt which can inform future practices of housing provision and design in Algeria and other countries.

Keywords: community-led cooperative housing, conservative community, cultural continuity, post occupancy evaluation

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Bency Jacob, S.B. Waykar

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Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

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Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: Obe Olumide Olayinka, Victor Balanica, Eugen Neagoe

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The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.

Keywords: neural network, hypertension, data set, training set, supervised learning

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Authors: A. Kourou, S. Kyriakopoulos, N. Anyfanti

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A lot of children under the age of five spend their daytime hours away from their home, in a kindergarten. Caring for children is a serious subject, and their safety in case of earthquake is the first priority. Being aware of earthquakes helps to prioritize the needs and take the appropriate actions to limit the effects. Earthquakes occurring anywhere at any time require emergency planning. Earthquake planning is a cooperative effort and childcare providers have unique roles and responsibilities. Greece has high seismicity and Ionian Islands Region has the highest seismic activity of the country. The last five years Earthquake Planning and Protection Organization (EPPO), which is a national organization, has analyzed the needs and requirements of kindergartens on earthquake protection issues. In this framework it has been noticed that although the State requires child care centers to hold drills, the standards for emergency preparedness in these centers are varied, and a lot of them had not written plans for emergencies. For these reasons, EPPO supports the development of emergency planning guidance and familiarizes the day care centers’ staff being prepared for earthquakes. Furthermore, the Handbook on Day Care Earthquake Planning that has been developed by EPPO helps the providers to understand that emergency planning is essential to risk reduction. Preparedness and training should be ongoing processes, thus EPPO implements every year dozens of specific seminars on children’s disaster related needs. This research presents the results of a survey that detects the level of earthquake preparedness of kindergartens in all over the country and Ionian Islands too. A closed-form questionnaire of 20 main questions was developed for the survey in order to detect the aspects of participants concerning the earthquake preparedness actions at individual, family and day care environment level. 2668 questionnaires were gathered from March 2014 to May 2019, and analyzed by EPPO’s Department of Education. Moreover, this paper presents the EPPO’s educational activities targeted to the Ionian Islands Region that implemented in the framework of “Telemachus” Project. To provide safe environment for children to learn, and staff to work is the foremost goal of any State, community and kindergarten. This project is funded under the Priority Axis "Environmental Protection and Sustainable Development" of Operational Plan "Ionian Islands 2014-2020". It is increasingly accepted that emergency preparedness should be thought of as an ongoing process rather than a one-time activity. Creating an earthquake safe daycare environment that facilitates learning is a challenging task. Training, drills, and update of emergency plan should take place throughout the year at kindergartens to identify any gaps and to ensure the emergency procedures. EPPO will continue to work closely with regional and local authorities to actively address the needs of children and kindergartens before, during and after earthquakes.

Keywords: child care centers, education on earthquake, emergency planning, kindergartens, Ionian Islands Region of Greece

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Authors: L. Raczynski, P. Moskal, P. Kowalski, W. Wislicki, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, L. Kaplon, A. Kochanowski, G. Korcyl, J. Kowal, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, Z. Rudy, O. Rundel, P. Salabura, N.G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, M. Zielinski, N. Zon

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The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The J-PET detector improves the TOF resolution due to the use of fast plastic scintillators. Since registration of the waveform of signals with duration times of few nanoseconds is not feasible, a novel front-end electronics allowing for sampling in a voltage domain at four thresholds was developed. To take fully advantage of these fast signals a novel scheme of recovery of the waveform of the signal, based on ideas from the Tikhonov regularization (TR) and Compressive Sensing methods, is presented. The prior distribution of sparse representation is evaluated based on the linear transformation of the training set of waveform of the signals by using the Principal Component Analysis (PCA) decomposition. Beside the advantage of including the additional information from training signals, a further benefit of the TR approach is that the problem of signal recovery has an optimal solution which can be determined explicitly. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This step is crucial to introduce and prove the formula for calculations of the signal recovery error. It has been proven that an average recovery error is approximately inversely proportional to the number of samples at voltage levels. The method is tested using signals registered by means of the single detection module of the J-PET detector built out from the 30 cm long BC-420 plastic scintillator strip. It is demonstrated that the experimental and theoretical functions describing the recovery errors in the J-PET scenario are largely consistent. The specificity and limitations of the signal recovery method in this application are discussed. It is shown that the PCA basis offers high level of information compression and an accurate recovery with just eight samples, from four voltage levels, for each signal waveform. Moreover, it is demonstrated that using the recovered waveform of the signals, instead of samples at four voltage levels alone, improves the spatial resolution of the hit position reconstruction. The experiment shows that spatial resolution evaluated based on information from four voltage levels, without a recovery of the waveform of the signal, is equal to 1.05 cm. After the application of an information from four voltage levels to the recovery of the signal waveform, the spatial resolution is improved to 0.94 cm. Moreover, the obtained result is only slightly worse than the one evaluated using the original raw-signal. The spatial resolution calculated under these conditions is equal to 0.93 cm. It is very important information since, limiting the number of threshold levels in the electronic devices to four, leads to significant reduction of the overall cost of the scanner. The developed recovery scheme is general and may be incorporated in any other investigation where a prior knowledge about the signals of interest may be utilized.

Keywords: plastic scintillators, positron emission tomography, statistical analysis, tikhonov regularization

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Authors: Ginevra Addis

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The possibility of reproducing physical artifacts in a digital format is one of the opportunities offered by the technological advancements in information and communication most frequently promoted by museums. Indeed, the study and conservation of our cultural heritage have seen significant advancement due to the three-dimensional acquisition and modeling technology. A variety of laser scanning systems has been developed, based either on optical triangulation or on time-of-flight measurement, capable of producing digital 3D images of complex structures with high resolution and accuracy. It is necessary, however, to explore the challenges and opportunities that this practice brings within museums. The purpose of this paper is to understand what change is introduced by digital techniques in those museums that are hosting digital masterpieces. The methodology used will investigate three distinguished Italian exhibitions, related to the territory of Milan, trying to analyze the following issues about museum practices: 1) how digitizing art masterpieces increases the number of visitors; 2) what the need that calls for the digitization of artworks; 3) which techniques are most used; 4) what the setting is; 5) the consequences of a non-publication of hard copies of catalogues; 6) envision of these practices in the future. Findings will show how interconnection plays an important role in rebuilding a collection spread all over the world. Secondly how digital artwork duplication and extension of reality entail new forms of accessibility. Thirdly, that collection and preservation through digitization of images have both a social and educational mission. Fourthly, that convergence of the properties of different media (such as web, radio) is key to encourage people to get actively involved in digital exhibitions. The present analysis will suggest further research that should create museum models and interaction spaces that act as catalysts for innovation.

Keywords: digital masterpieces, education, interconnection, Italian museums, preservation

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Authors: Rafael Sousa Santos, Clara Pimena Do Vale, Barbara Bogoni, Poul Henning Kirkegaard

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The representative component, a determining aspect of the architect's training, has been marked by an exponential and unprecedented development. However, the multiplication of possibilities has also multiplied uncertainties about architectural design teaching, and by extension, about the very principles of architectural education. In this paper, it is intended to present the results of a research developed on the following problem: the relation between the forms of representation and the architectural design teaching-learning processes. The research had as its object the educational model of two schools – the Politecnico di Milano (POLIMI) and the Faculty of Architecture of the University of Porto (FAUP) – and was led by three main objectives: to characterize the educational model followed in both schools focused on the representative component and its role; to interpret the relation between forms of representation and the architectural design teaching-learning processes; to consider their possibilities of valorisation. Methodologically, the research was conducted according to a qualitative embedded multiple-case study design. The object – i.e., the educational model – was approached in both POLIMI and FAUP cases considering its Context and three embedded unities of analysis: the educational Purposes, Principles, and Practices. In order to guide the procedures of data collection and analysis, a Matrix for the Characterization (MCC) was developed. As a methodological tool, the MCC allowed to relate the three embedded unities of analysis with the three main sources of evidence where the object manifests itself: the professors, expressing how the model is assumed; the architectural design classes, expressing how the model is achieved; and the students, expressing how the model is acquired. The main research methods used were the naturalistic and participatory observation, in-person-interview and documentary and bibliographic review. The results reveal the importance of the representative component in the educational model of both cases, despite the differences in its role. In POLIMI's model, representation is particularly relevant in the teaching of architectural design, while in FAUP’s model, it plays a transversal role – according to an idea of 'general training through hand drawing'. In fact, the difference between models relative to representation can be partially understood by the level of importance that each gives to hand drawing. Regarding the teaching of architectural design, the two cases are distinguished in the relation with the representative component: while in POLIMI the forms of representation serve essentially an instrumental purpose, in FAUP they tend to be considered also for their methodological dimension. It seems that the possibilities for valuing these models reside precisely in the relation between forms of representation and architectural design teaching. It is expected that the knowledge base developed in this research may have three main contributions: to contribute to the maintenance of the educational model of POLIMI and FAUP; through the precise description of the methodological procedures, to contribute by transferability to similar studies; through the critical and objective framework of the problem underlying the forms of representation and its relation with architectural design teaching, to contribute to the broader discussion concerning the contemporary challenges on architectural education.

Keywords: architectural design teaching, architectural education, educational models, forms of representation

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Mustafa Mhawesh, Reza Langari

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This paper describes the development of a model of an impaired human arm performing a reaching motion, which will be used to predict hand path trajectories for people with reduced arm joint mobility. Assuming that the arm was in contact with a surface during the entire movement, the contact conditions at the initial and final task locations were determined and used to generate the entire trajectory. The model was validated by comparing it to experimental data, which simulated an arm joint impairment by physically constraining the joint motion with a brace. Future research will include using the model in the development of physical training protocols that avoid early recruitment of “healthy” Degrees-Of-Freedom (DOF) for reaching motions, thus facilitating an Active Range-Of-Motion Recovery (AROM) for a particular impaired joint.

Keywords: higher order kinematic specifications, human motor coordination, impaired movement, kinematic synthesis

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Authors: Elham Fathi, Seyed Mohammad Kalantarkousheh, Abolfazl Hatami Varzane

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The present study aimed to determine predict capacity of the relationship among attachment styles, humor styles and communication patterns in female married students. Statistical population consisted of female married students from Allameh Tabataba’i University. The research sample consisted of 104 married students selected through convenience sampling. They responded to study instruments that consisted of attachment styles, humor styles and Communication patterns questionnaires. Data was analyzed by means of correlation method. The results indicated significant positive relationship between secure attachment styles with adaptive humor styles, and anxious attachment styles with maladaptive humor styles. Also a negative relationship between avoidant attachment with affiliative humor, and anxious attachment with self-enhancing humor was found. Furthermore, a negative relationship between self- enhancing humor styles with demand – withdraw communication pattern, and between affiliative humor with mutual avoidant communication pattern and a positive relationship between affiliative humor with mutual constructive communication pattern was observed. The relationship between secure attachment with mutual constructive communication pattern was positive, while relationship between avoidant attachment to mutual constructive communication pattern was negative and significant and its relation with mutual avoidant communication pattern was significantly positive. The result of regression analysis indicated that affliative humor style and secure attachment style, positively predicted mutual constructive communication pattern. Avoidant attachment style positively and affliative humor style negatively predicted the mutual avoidant communication pattern. And self-enhancing humor style negatively predicted the demand – withdraw communication pattern style.

Keywords: attachment styles, communication patterns, humor styles, female married students

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Authors: R. Lekaviciene, D. Antiniene

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Attempts to split the construct of emotional intelligence (EI) into separate components – ability to understand own and others’ emotions and ability to control own and others’ emotions may be meaningful more theoretically than practically. In real life, a personality encounters various emotional situations that require exhibition of complex EI to solve them. Emotional situation solution tests enable measurement of such undivided EI. The object of the present study is to determine sociodemographic and other factors that are important for emotional situation solutions. The study involved 1,430 participants from various regions of Lithuania. The age of participants varied from 17 years to 27 years. Emotional social and interpersonal situation scale EI-DARL-V2 was used. Each situation had two mandatory answering formats: The first format contained assignments associated with hypothetical theoretical knowledge of how the situation should be solved, while the second format included the question of how the participant would personally resolve the given situation in reality. A questionnaire that contained various sociodemographic data of subjects was also presented. Factors, statistically significant for emotional situation solution, have been determined: gender, family structure, the subject’s relation with his or her mother, mother’s occupation, subjectively assessed financial situation of the family, level of education of the subjects and his or her parents, academic achievement, etc. The best solvers of emotional situations are women with high academic achievements. According to their chosen study profile/acquired profession, they are related to the fields in social sciences and humanities. The worst solvers of emotional situations are men raised in foster homes. They are/were bad students and mostly choose blue-collar professions.

Keywords: emotional intelligence, emotional situations, solution of situation, young people

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Authors: Victor Oluwaseyi Olowonisi

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The paper aimed at presenting an overview on the concept of e-learning as it relates to higher education and how it provides opportunities for students, instructors and the government in developing the educational sector. It also touched on the benefits and challenges attached to e-learning as a new medium of reaching more students especially in the Nigerian context. The opportunities attributed to e-learning in the paper includes breaking boundaries barriers, reaching a larger number of students, provision of jobs for ICT experts, etc. In contrary, poor power supply, cost of implementation, poor computer literacy, technophobia (fear of technology), computer crime and system failure were some of the challenges of e-learning discussed in the paper. The paper proffered that the government can help the people gain more from e-learning through its financing. Also, it was stated that instructors/lecturers and students need to undergo training on computer application in order for e-learning to be more effective in developing higher education in Nigeria.

Keywords: e-learning, education, higher education, increasing literacy

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Authors: Minh Dong Le, Viet Dung Nguyen, Do Huu Viet, Nguyen Huu Tu

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In this paper, we present a new method for circumscribed masses detection in mammograms. Our method is evaluated on 23 mammographic images of circumscribed masses and 20 normal mammograms from public Mini-MIAS database. The method is quite sanguine with sensitivity (SE) of 95% with only about 1 false positive per image (FPpI). To achieve above results we carry out a progression following: Firstly, the input images are preprocessed with the aim to enhance key information of circumscribed masses; Next, we calculate and evaluate statistically basic features of abnormal regions on training database; Then, mammograms on testing database are divided into equal blocks which calculated corresponding features. Finally, using priority order of basic features to classify blocks as an abnormal or normal regions.

Keywords: mammograms, circumscribed masses, evaluated statistically, priority order of basic features

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Authors: Romisaa Ali

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The Policy Gradient approach is one of the deep reinforcement learning families that combines deep neural networks (DNN) with reinforcement learning RL to discover the optimum of the control problem through experience gained from the interaction between the robot and its surroundings. In contrast to earlier policy gradient algorithms, which were unable to handle these two types of error because of over-or under-estimation introduced by the deep neural network model, this article will discuss the state-of-the-art SOTA policy gradient technique, trust region policy optimization (TRPO), by applying this method in various environments compared to another policy gradient method, the Proximal Policy Optimization (PPO), to explain their robust optimization, using this SOTA to gather experience data during various training phases after observing the impact of hyper-parameters on neural network performance.

Keywords: deep neural networks, deep reinforcement learning, proximal policy optimization, state-of-the-art, trust region policy optimization

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Authors: Chia-Yi Wu, Jung-Chen Chang, Wen-Yu Hu, Ming-Been Lee

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In nearly all physical health conditions, suicide risk is increased compared to healthy people even after adjustment for age, gender, mental health, and substance use diagnoses. In order to highlight the importance of suicide risk assessment for the inpatients and early identification and engagement for inpatients’ mental health problems, a study was designed aiming at developing a comprehensive psychosomatic nursing engagement (PSNE) model with standardized operation procedures informing how nurses communicate, assess, and engage with the inpatients with emotional distress. The purpose of the study was to promote the gatekeeping role of clinical nurses in performing brief assessment and interventions to detect depression and anxiety symptoms among the inpatients, particularly in non-psychiatric wards. The study will be carried out in a 2000-bed university hospital in Northern Taiwan in 2019. We will select a ward for trial and develop feasible procedures and in-job training course for the nurses to offer mental health care, which will also be validated through professional consensus meeting. The significance of the study includes the following three points: (1) The study targets at an important but less-researched area of PSNE model in the cultural background of Taiwan, where hospital service is highly accessible, but mental health and suicide risk assessment are hardly provided by non-psychiatric healthcare personnel. (2) The issue of PSNE could be efficient and cost-effective in the identification of suicide risks at an early stage to prevent inpatient suicide or to reduce future suicide risk by early treatment of mental illnesses among the high-risk group of hospitalized patients who are more than three-times lethal to suicide. (3) Utilizing a brief tool with its established APP ('The Five-item Brief Symptom Rating Scale, BSRS-5'), we will invent the standardized procedure of PSNE and referral steps in collaboration with the medical teams across the study hospital. New technological tools nested within nursing assessment/intervention will concurrently be invented to facilitate better care quality. The major outcome measurements will include tools for early identification of common mental distress and suicide risks, i.e., the BSRS-5, revised BSRS-5, and the 9-item Concise Mental Health Checklist (CMHC-9). The main purpose of using the CMHC-9 in clinical suicide risk assessment is mainly to provide care and build-up therapeutic relationship with the client, so it will also be used to nursing training highlighting the skills of supportive care. Through early identification of the inpatients’ depressive symptoms or other mental health care needs such as insomnia, anxiety, or suicide risk, the majority of the nursing clinicians would be able to engage in critical interventions that alleviate the inpatients’ suffering from mental health problems, given a feasible nursing input.

Keywords: mental health care, clinical outcome improvement, clinical nurses, suicide prevention, psychosomatic nursing

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Authors: Cathal Ffrench, Ryan Barrett, Mike Quayle

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It is accepted in social psychology that categorization leads to ingroup favoritism, without further thought given to the processes that may co-occur or even precede categorization. These categorizations move away from the conceptualization of the self as a unique social being toward an increasingly collective identity. Subsequently, many individuals derive much of their self-evaluations from these collective identities. The seminal literature on this topic argues that it is primarily categorization that evokes instances of ingroup favoritism. Apropos to these theories, we argue that categorization acts to enhance and further intergroup processes rather than defining them. More accurately, we propose categorization aids initial ingroup contact and this first contact is predictive of subsequent favoritism on individual and collective levels. This analysis focuses on Virtual Interaction APPLication (VIAPPL) based studies, a software interface that builds on the flaws of the original minimal group studies. The VIAPPL allows the exchange of tokens in an intra and inter-group manner. This token exchange is how we classified the first contact. The study involves binary longitudinal analysis to better understand the subsequent exchanges of individuals based on who they first interacted with. Studies were selected on the criteria of evidence of explicit first interactions and two-group designs. Our findings paint a compelling picture in support of a motivated contact hypothesis, which suggests that an individual’s first motivated contact toward another has strong predictive capabilities for future behavior. This contact can lead to habit formation and specific favoritism towards individuals where contact has been established. This has important implications for understanding how group conflict occurs, and how intra-group individual bias can develop.

Keywords: categorization, group dynamics, initial contact, minimal social networks, momentary contact

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Authors: Inyene Nathaniel Nkanta

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The present economic situation in Nigeria, with an increase in inflation rate due to the fall of crude oil prices and post covid-19 crisis, has increased the level of poverty and suffering in Nigeria, particularly the women. Against that backdrop, this research project is initiated to explore ways to empower women through entrepreneurship education and training to ameliorate the poverty level amongst women in Nigeria. A qualitative approach to data collection will be applied in this study and to test the assertions of this research project empirically, this research adopts a case study research method as this will enable me to obtain and probe ways women can be empowered through semi-structured interviews and focus groups. The result of this research project will provide an original perspective on human capital development, most importantly, the need for entrepreneurial education and entrepreneurial literature and practice.

Keywords: women, Nigeria, entrepreneurship education, Economic development, human capital

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Authors: A. Delimitsou, C. Gouedard, E. Konstanta, A. Koletis, S. Patera, E. Manou, K. Spaho, S. Murray

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Background: There remains a lack of International Standard Control Reference materials for Next Generation Sequencing-based approaches or device calibration. We have designed and validated dsDNA biomimetic reference materials for targeted such approaches incorporating proprietary motifs (patent pending) for device/test calibration. They enable internal single-sample calibration, alleviating sample comparisons to pooled historical population-based data assembly or statistical modelling approaches. We have validated such an approach for BRCA Copy Number Variation analytics using iQRS™-CNVSUITE versus Mixed Ligation-dependent Probe Amplification. Methods: Standard BRCA Copy Number Variation analysis was compared between mixed ligation-dependent probe amplification and next generation sequencing using a cohort of 198 breast/ovarian cancer patients. Next generation sequencing based copy number variation analysis of samples spiked with iQRS™ dsDNA biomimetics were analysed using proprietary CNVSUITE software. Mixed ligation-dependent probe amplification analyses were performed on an ABI-3130 Sequencer and analysed with Coffalyser software. Results: Concordance of BRCA – copy number variation events for mixed ligation-dependent probe amplification and CNVSUITE indicated an overall sensitivity of 99.88% and specificity of 100% for iQRS™-CNVSUITE. The negative predictive value of iQRS-CNVSUITE™ for BRCA was 100%, allowing for accurate exclusion of any event. The positive predictive value was 99.88%, with no discrepancy between mixed ligation-dependent probe amplification and iQRS™-CNVSUITE. For device calibration purposes, precision was 100%, spiking of patient DNA demonstrated linearity to 1% (±2.5%) and range from 100 copies. Traditional training was supplemented by predefining the calibrator to sample cut-off (lock-down) for amplicon gain or loss based upon a relative ratio threshold, following training of iQRS™-CNVSUITE using spiked iQRS™ calibrator and control mocks. BRCA copy number variation analysis using iQRS™-CNVSUITE™ was successfully validated and ISO15189 accredited and now enters CE-IVD performance evaluation. Conclusions: The inclusion of a reference control competitor (iQRS™ dsDNA mimetic) to next generation sequencing-based sequencing offers a more robust sample-independent approach for the assessment of copy number variation events compared to mixed ligation-dependent probe amplification. The approach simplifies data analyses, improves independent sample data analyses, and allows for direct comparison to an internal reference control for sample-specific quantification. Our iQRS™ biomimetic reference materials allow for single sample copy number variation analytics and further decentralisation of diagnostics to single patient sample assessment.

Keywords: validation, diagnostics, oncology, copy number variation, reference material, calibration

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Padma Sree Potru

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Abstract: A co-relational descriptive study was conducted to assess the impact of cancer event on self, on family, coping strategies of cancer clients and quality of life among them in G.G.H., Guntur, Andhra Pradesh, India. Aim: The aim of the study was to investigate the impact of cancer events on self, on family, coping of clients and quality of life among cancer patients. Methods: 50 cancer patients were selected through random sampling technique. The data were obtained by using impact of events scale, impact on family scale, coping health inventory and WHOQOL-BREF scale. Results: The results revealed that majority (32%) of them were in the age group of 36-45 years, 72% were females, 44% were having the income of Rs. 5001-10000/- per month, 40% were working for daily wage, and 15% were newly diagnosed of cancer. Among 50 cancer patients, 65% had extreme impact of events, 61% shows extreme impact on family, 46% possess minimal coping strategies and 68% had poor quality of life. This study focuses on that there is a strong positive correlation between quality of life and coping behavior r=0.603 and also between impact of event and impact on family r=0.610, but a negative correlation existed between quality of life and impact of events r= -0.201. ANOVA test reveals that there is a significant difference between subscales of impact on family and coping behavior with f values = 3.893, 3.957 respectively. Chi-square highlights that there is a significant association between impact of events with age, occupation and impact on family with duration of illness. Conclusion: Even though cancer is a dreadful disease still there are many emerging treatment modalities and innovative procedures which are focusing on improving the standards of life among cancer clients. But all this can happen only when the clients accepts the reality, increase their willpower and confidence, desire to live, focusing on coping mechanisms and good ongoing support from the family members.

Keywords: impact of event, impact on family, coping, quality of event

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: Nighat Ayub, Masood Ahmad

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In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

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Authors: Frodouard Minani

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Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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Authors: Yi-Jiun Chou, Ying-Hsuan Li, Yi-Jung Liu, Hsin-Yu Chiang, Hsuan-Ching Wang

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Background: Patients received therapeutic hypothermia (TH) after resuscitation from cardiac arrest are more dependent on continue and intensive nursing care. It involves many difficult steps, especially achieving target body temperature. To our best knowledge, there is no consensus or recommended standards on nursing practice of TH. Aim: The aim of this study is to increase the completion rate of nursing care at therapeutic hypothermia. Methods: We took five measures: (1) Amendment of nursing standards of therapeutic hypothermia; (2) Amendment of TH checklist items to nursing records; (3) Establishment of monitor procedure; (4) Design each period of TH care reminder cards; (5) Providing in-service training sections of TH for ICU nursing staff. Outcomes: The completion rate of nursing care at therapeutic hypothermia increased from 78.1% to 89.3%. Conclusion: The project team not only increased the completion rate but also improved patient safety and quality of care.

Keywords: therapeutic hypothermia, nursing, critical care, quality of care

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Authors: Shih Meng-Chi, Nai-Chia Chao

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The study constructed an arts integrative curriculum for early childhood educators and kindergarten teachers to the exciting possibilities of the use of the art integration method. The art integrative curriculum applied art integration that combines and integrates various elements of music, observation, sound, art, instruments, and creation. The program consists of college courses that combine the use of technology with children’s literature, multimedia, music, dance, and drama presentation. This educational program is being used in kindergartens during the pre-service kindergarten teacher training. The study found that arts integrated curriculum was benefit for connecting across domains, multi-sensory experiences, teaching skills, implementation and creation on children art education. The art Integrating instruction helped to provide students with an understanding of the whole framework and improve the teaching quality.

Keywords: art integration, teaching quality assurance, early childhood education, arts integrated curriculum

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Authors: Pallavi Malhotra

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This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Mohamed Zellagui, Heba Ahmed Hassan

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This paper proposes a new approach for the calculation of short-circuit parameters in the presence of Pulse Width Modulated based Series Compensator (PWMSC). PWMSC is a newly Flexible Alternating Current Transmission System (FACTS) device that can modulate the impedance of a transmission line through applying a variation to the duty cycle (D) of a train of pulses with fixed frequency. This results in an improvement of the system performance as it provides virtual compensation of distribution line impedance by injecting controllable apparent reactance in series with the distribution line. This controllable reactance can operate in both capacitive and inductive modes and this makes PWMSC highly effective in controlling the power flow and increasing system stability in the system. The purpose of this work is to study the impact of fault resistance (RF) which varies between 0 to 30 Ω on the fault current calculations in case of a ground fault and a fixed fault location. The case study is for a medium voltage (MV) Algerian distribution line which is compensated by PWMSC in the 30 kV Algerian distribution power network. The analysis is based on symmetrical components method which involves the calculations of symmetrical components of currents and voltages, without and with PWMSC in both cases of maximum and minimum duty cycle value for capacitive and inductive modes. The paper presents simulation results which are verified by the theoretical analysis.

Keywords: pulse width modulated series compensator (pwmsc), duty cycle, distribution line, short-circuit calculations, ground fault, symmetrical components method

Procedia PDF Downloads 483