Search results for: task analysis

Authors: Yan Yan, Erhong Sun, Lin Peng, Xuchun Ye

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Aims: The present study aimed to explore Intensive Care Unit (ICU) nurses’ mental workload (MWL) and associated factors with it in performing human-machine tasks. Background: A wide range of emerging technologies have penetrated widely in the field of health care, and ICU nurses are facing a dramatic increase in nursing human-machine tasks. However, there is still a paucity of literature reporting on the general MWL of ICU nurses performing human-machine tasks and the associated influencing factors. Methods: A cross-sectional survey was employed. The data was collected from January to February 2021 from 9 tertiary hospitals in 6 provinces (Shanghai, Gansu, Guangdong, Liaoning, Shandong, and Hubei). Two-stage sampling was used to recruit eligible ICU nurses (n=427). The data were collected with an electronic questionnaire comprising sociodemographic characteristics and the measures of MWL, self-efficacy, system usability, and task difficulty. The univariate analysis, two-way analysis of variance (ANOVA), and a linear mixed model were used for data analysis. Results: Overall, the mental workload of ICU nurses in performing human-machine tasks was medium (score 52.04 on a 0-100 scale). Among the typical nursing human-machine tasks selected, the MWL of ICU nurses in completing first aid and life support tasks (‘Using a defibrillator to defibrillate’ and ‘Use of ventilator’) was significantly higher than others (p < .001). And ICU nurses’ MWL in performing human-machine tasks was also associated with age (p = .001), professional title (p = .002), years of working in ICU (p < .001), willingness to study emerging technology actively (p = .006), task difficulty (p < .001), and system usability (p < .001). Conclusion: The MWL of ICU nurses is at a moderate level in the context of a rapid increase in nursing human-machine tasks. However, there are significant differences in MWL when performing different types of human-machine tasks, and MWL can be influenced by a combination of factors. Nursing managers need to develop intervention strategies in multiple ways. Implications for practice: Multidimensional approaches are required to perform human-machine tasks better, including enhancing nurses' willingness to learn emerging technologies actively, developing training strategies that vary with tasks, and identifying obstacles in the process of human-machine system interaction.

Keywords: mental workload, nurse, ICU, human-machine, tasks, cross-sectional study, linear mixed model, China

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Ahmad Abu-Akel, Emilie De Montpellier, Sophie Von Bentivegni, Lyn Luechinger, Alessandro Ishii, Christine Mohr

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Convergent and divergent thinking are two main components of creativity that have been viewed as complementary. While divergent thinking refers to the fluency and flexibility of generating new ideas, convergent thinking refers to the ability to systematically apply rules and knowledge to arrive at the optimal solution or idea. These creativity components have been shown to be susceptible to variation in subclinical expressions of autistic and schizotypal traits within the general population. Research, albeit inconclusively, mainly linked positive schizotypal traits with divergent thinking and autistic traits with convergent thinking. However, cumulative evidence suggests that these trait dimensions can co-occur in the same individual more than would be expected by chance and that their concurrent effect can be diametric and even interactive. The current study aimed at investigating the concurrent effect of these trait dimensions on tasks assessing convergent and divergent thinking abilities. We predicted that individuals with high positive schizotypal traits alone would perform particularly well on the divergent thinking task, whilst those with high autistic traits alone would perform particularly well on the convergent thinking task. Crucially, we also predicted that individuals who are high on both autistic and positive schizotypal traits would perform particularly well on both the divergent and convergent thinking tasks. This was investigated in a non-clinical sample of 142 individuals (Males = 45%; Mean age = 21.45, SD = 2.30), sufficient to minimally observe an effect size f² ≥ .10. Divergent thinking was evaluated using the Alternative Uses Task, and convergent thinking with the Anagrams Task. Autistic and schizotypal traits were respectively assessed with the Autism Quotient Questionnaire (AQ) and the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE). Regression analyses revealed that the positive association of autistic traits with convergent thinking scores was qualified with an interaction with positive schizotypal traits. Specifically, positive schizotypal traits were negatively associated with convergent thinking scores when AQ scores were relatively low, but this trend was reversed when AQ scores were high. Conversely, the positive effect of AQ scores on convergent thinking progressively increased with increasing positive schizotypal traits. The results of divergent thinking task are currently being analyzed and will be reported at the conference. The association of elevated autistic and positive schizotypal traits with convergent thinking may represent a unique profile of creative thinkers who are able to simultaneously draw on trait-specific advantages conferred by autistic and positively schizotypal traits such as local and global processing. This suggests that main-effect models can tell an incomplete story regarding the effect of autistic and positive schizotypal traits on creativity-related processes. Future creativity research should consider their interaction and the benefits conferred by their co-presence.

Keywords: autism, schizotypy, convergent thinking, divergent thinking, comorbidity

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Authors: D. Dorota

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This paper presents a method to generate and schedule task in the architecture of embedded systems based on the simulated annealing. This method takes into account the attribute of divisibility of tasks. A proposal represents the process in the form of trees. Despite the fact that the architecture of Network-on-Chip (NoC) is an interesting alternative to a bus architecture based on multi-processors systems, it requires a lot of work that ensures the optimization of communication. This paper proposes an effective approach to generate dedicated NoC topology solving communication problems. Network NoC is generated taking into account the energy consumption and resource issues. Ultimately generated is minimal, dedicated NoC topology. The proposed solution is assumed to be a simple router design and the minimum number of lines.

Keywords: Network-on-Chip, NoC-based embedded systems, scheduling task in embedded systems, simulated annealing

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Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana

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It is evident that there has been progress in the development and innovation of tools, techniques and methods in the development of software. Even so, there are few methodologies that include the human factor from the point of view of motivation, emotions and impact on the work environment; aspects that, when mishandled or not taken into consideration, increase the iterations in the requirements elicitation phase. This generates a broad number of changes in the characteristics of the system during its developmental process and an overinvestment of resources to obtain a final product that, often, does not live up to the expectations and needs of the client. The human factors such as emotions or personality traits are naturally associated with the process of developing software. However, most of these jobs are oriented towards the analysis of the final users of the software and do not take into consideration the emotions and motivations of the members of the development team. Given that in the industry, the strategies to select the requirements engineers and/or the analysts do not take said factors into account, it is important to identify and describe the characteristics or personality traits in order to elicit requirements effectively. This research describes the main personality traits associated with the requirements elicitation tasks through the analysis of the existing literature on the topic and a compilation of our experiences as software development project managers in the academic and productive sectors; allowing for the characterisation of a suitable profile for this job. Moreover, a psychometric test is used as an information gathering technique, and it is applied to the personnel of some local companies in the software development sector. Such information has become an important asset in order to make a comparative analysis between the degree of effectiveness in the way their software development teams are formed and the proposed profile. The results show that of the software development companies studied: 53.58% have selected the personnel for the task of requirements elicitation adequately, 37.71% possess some of the characteristics to perform the task, and 10.71% are inadequate. From the previous information, it is possible to conclude that 46.42% of the requirements engineers selected by the companies could perform other roles more adequately; a change which could improve the performance and competitiveness of the work team and, indirectly, the quality of the product developed. Likewise, the research allowed for the validation of the pertinence and usefulness of the psychometric instrument as well as the accuracy of the characteristics for the profile of requirements engineer proposed as a reference.

Keywords: emotions, human attitudes, personality traits, psychometric tests, requirements engineering

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Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Yu-Chu Yeh, WeiChin Hsu, Chih-Yen Chang

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Substitution, combination, modification, putting to other uses, elimination, and rearrangement (SCAMPER) has been regarded as an effective technique that provides a structured way to help people to produce creative ideas and solutions. Although some neuroscience studies regarding creativity training have been conducted, no study has focused on SCAMPER. This study therefore aimed at examining whether the learning of SCAMPER through video tutorials would result in alternations of neural activation. Thirty college students were randomly assigned to the experimental group or the control group. The experimental group was requested to watch SCAMPER videos, whereas the control group was asked to watch natural-scene videos which were regarded as neutral stimulating materials. Each participant was brain scanned in a Functional magnetic resonance imaging (fMRI) machine while undertaking a creativity test before and after watching the videos. Furthermore, a two-way ANOVA was used to analyze the interaction between groups (the experimental group; the control group) and tasks (C task; M task; X task). The results revealed that the left precuneus significantly activated in the interaction of groups and tasks, as well as in the main effect of group. Furthermore, compared with the control group, the experimental group had greater activation in the default mode network (left precuneus and left inferior parietal cortex) and the motor network (left postcentral gyrus and left supplementary area). The findings suggest that the SCAMPER training may facilitate creativity through the stimulation of the default mode network and the motor network.

Keywords: creativity, default mode network, neural activation, SCAMPER

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Authors: Adnan Ahmad, Yusri Kamin, Asnol Dahar Minghat, Mohd. Khir Nordin, Dayana Farzeha, Ahmad Nabil

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The purpose of this study is to identify the teaching method practices of the practical work subject in Vocational Secondary School. This study examined the practice of Vocational Teaching Method in Automotive Practical Work. The quantitative method used the sets of the questionnaire. 283 students and 63 teachers involved from ten VSS involved in this research. Research finding showed in conducting the introduction session teachers prefer used the demonstration method and questioning technique. While in deliver the content of practical task, teachers applied group monitoring and problem-solving approach. To conclude the task of automotive practical work, teachers choose re-explain and report writing to make sure students really understand all the process of teaching. VTM-APW also involved the competency-based concept to embed in the model. Derived from factors investigated, research produced the combination of elements in teaching skills and vocational skills which could be used as the best teaching method in automotive practical work for school level. As conclusion this study has concluded that the VTM-APW model is able to apply in teaching to make an improvement with current practices in Vocational Secondary School. Hence, teachers are suggested to use this method to enhance student's knowledge in Automotive and teachers will deliver skills to the current and future workforce relevant with the required competency skilled in workplace.

Keywords: vocational teaching method, practical task, teacher preferences, student preferences

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

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In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: agriculture, human factors, product design, soil moisture control

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Authors: Małgorzata Osowiecka

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Negative emotions are rather seen as creativity inhibitor. On the other hand, it is worth noting that negative emotions may be good for our functioning. Negative emotions enhance cognitive resources and improve evaluative processes. Moreover maintaining a negative emotional state allow for cognitive reinterpretation of the emotional stimuli, what is good for our creativity, especially cognitive flexibility. Writing a diary or writing about difficult emotional experiences in general can be the way to not only improve psychical health, but also – enhance creative behaviors. Thanks to translating difficult emotions to the verbal level and giving them ‘a name’ or ‘a label’, we can get easier access to both emotional content of an experience and to the semantic content, without the need of speaking out loud. Expressive writing improves academic results and the efficiency of working memory. The classical method of writing about emotions consists in a long-term process of describing negative experiences. Present research demonstrate the efficiency of this process over a shorter period of time - one writing session, on school children sample. Participants performed writing task. Writing task had two different topics: emotions connected with their negative emotions (expressive writing) and content not connected with negative emotional state (writing about one’s typical day). Creativity was measured by Guilford’s Alternative Uses Task. Results have shown that writing about negative emotions results in the higher level of divergent thinking in all three parameters: fluency, flexibility and originality. After the writing task mood of expressive writing participants remained negative more than the mood of the controls. Taking an expressive action after a difficult emotional experience can support functioning, which can be observed in enhancement of divergent thinking. Writing about emotions connected with negative experience makes one more creative, than writing about something unrelated with difficult emotional moments. Research has shown that young people should not demonize negative emotions. Sometimes, properly applied, negative emotions can be the basis of creation. Preparation was supported by a The Young Scientist University grant titled ‘Dynamics of emotions in the creative process’ from The Polish Ministry of Science and Higher Education.

Keywords: creativity, divergent thinking, emotions, expressive writing

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Authors: L. Freeborn

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Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

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Authors: Anthony Mpiani

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Recent media and NGO reports suggest that human rights violations have been a salient characteristic of the government Joint Task Force (JTF) in the war on Boko Haram. However, there has been relatively scant scholarly engagement with the forms of abuses committed by the JTF against civilians and why such human rights violations occur. The focus of this paper is to analyse the various human rights violations committed by JTF in the war against Boko Haram. Employing a historical approach, it argues that the JTF's human rights violations is shaped by the philosophy of colonial policing in Nigeria. Consequently, the failure of successive post-colonial governments to ideologically transform policing is accountable for the human rights abuses being witnessed in Nigeria today. A philosophical transformation in Nigeria's security forces especially the police and military is a prerequisite for ending human rights abuses in the fight against Boko Haram.

Keywords: colonialism, policing, joint task force, counterinsurgency, Boko Haram, human rights violations

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Authors: Thomas E. Portegys

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An animal behavior problem is presented in the form of a nest-building task that involves two cooperating virtual birds, a male and female. The female builds a nest into which she lays an egg. The male's job is to forage in a forest for food for both himself and the female. In addition, the male must fetch stones from a nearby desert for the female to use as nesting material. The task is completed when the nest is built, and an egg is laid in it. A goal-seeking neural network and a recurrent neural network were trained and tested with little success. The goal-seeking network was then enhanced with “place cells”, allowing the birds to spatially navigate the world, building the nest while keeping themselves fed. Place cells are neurons in the hippocampus that map space.

Keywords: artificial animal intelligence, artificial life, goal-seeking neural network, nest-building, place cells, spatial navigation

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Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

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Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: Renukswamy Chikkamath, Vishvapalsinhji Ramsinh Parmar, Christoph Hewel, Markus Endres

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Given a patent document, identifying distinct semantic annotations is an interesting research aspect. Text annotation helps the patent practitioners such as examiners and patent attorneys to quickly identify the key arguments of any invention, successively providing a timely marking of a patent text. In the process of manual patent analysis, to attain better readability, recognising the semantic information by marking paragraphs is in practice. This semantic annotation process is laborious and time-consuming. To alleviate such a problem, we proposed a dataset to train machine learning algorithms to automate the highlighting process. The contributions of this work are: i) we developed a multi-class dataset of size 150k samples by traversing USPTO patents over a decade, ii) articulated statistics and distributions of data using imperative exploratory data analysis, iii) baseline Machine Learning models are developed to utilize the dataset to address patent paragraph highlighting task, and iv) future path to extend this work using Deep Learning and domain-specific pre-trained language models to develop a tool to highlight is provided. This work assists patent practitioners in highlighting semantic information automatically and aids in creating a sustainable and efficient patent analysis using the aptitude of machine learning.

Keywords: machine learning, patents, patent sentiment analysis, patent information retrieval

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

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Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

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Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

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Authors: Milorad Pavlovic, Sebastiano Trevisani, Antonella Cecchi

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In this paper, a procedure for the evaluation of seismic behavior of slender masonry structures (towers, bell towers, chimneys, minarets, etc.) is presented. The presented procedure is based on a full three-dimensional modal analyses and frequency measurements. As well-known, masonry is a composite material formed by bricks, or stone blocks, and mortar arranged more or less regularly and adopted for many centuries as structural material. Dynamic actions may represent the major risk of collapse of brickworks, and despite the progress achieved so far in science and mechanics; the assessment of their seismic performance remains a challenging task. Then, reliable physical and numerical models are worthy of recommendation. In this paper, attention is paid to the historical bell tower of the Basilica of Santa Maria Gloriosa dei Frari - usually called Frari - one of the greatest churches in Venice, Italy.

Keywords: bell tower, FEM, masonry, modal analysis, non-destructive testing

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Authors: Carlos Gonzalez-Flores, Ernesto Liñan-García

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A simple and robust approach for developing secure software. A Four Phase methodology consists in developing the non-secure software in phase one, and for the next three phases, one phase for each of the secure developing types (i.e. self-protected software, secure code transformation, and the secure shield). Our methodology requires first the determination and understanding of the type of security level needed for the software. The methodology proposes the use of several teams to accomplish this task. One Software Engineering Developing Team, a Compiler Team, a Specification and Requirements Testing Team, and for each of the secure software developing types: three teams of Secure Software Developing, three teams of Code Breakers, and three teams of Intrusion Analysis. These teams will interact among each other and make decisions to provide a secure software code protected against a required level of intruder.

Keywords: secure software, four phases methodology, software engineering, code breakers, intrusion analysis

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Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

Abstract:

Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score

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Authors: Sahar Sohrabi

Abstract:

The emergence of Cloud data centers has revolutionized the IT industry. Private Clouds in specific provide Cloud services for certain group of customers/businesses. In a real-time private Cloud each task that is given to the system has a deadline that desirably should not be violated. Scheduling tasks in a real-time private CLoud determine the way available resources in the system are shared among incoming tasks. The aim of the scheduling policy is to optimize the system outcome which for a real-time private Cloud can include: energy consumption, deadline violation, execution time and the number of host switches. Different scheduling policies can be used for scheduling. Each lead to a sub-optimal outcome in a certain settings of the system. A Bayesian Scheduling strategy is proposed for scheduling to further improve the system outcome. The Bayesian strategy showed to outperform all selected policies. It also has the flexibility in dealing with complex pattern of incoming task and has the ability to adapt.

Keywords: cloud computing, scheduling, real-time private cloud, bayesian

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Authors: Zsolt Szilvágyi, Jakub Panuska, Orsolya Kegyes-Brassai, Ákos Wolf, Péter Tildy, Richard P. Ray

Abstract:

Near-surface loose sediments and local ground conditions in general have a major influence on seismic response of structures. It is a difficult task to model ground behavior in seismic soil-structure-foundation interaction problems, fully account for them in seismic design of structures, or even properly consider them in seismic hazard assessment. In this study, we focused on applying seismic soil investigation methods, used for determining soil stiffness and damping properties, to response analysis used in seismic design. A site in Budapest, Hungary was investigated using Multichannel Analysis of Surface Waves, Seismic Cone Penetration Tests, Bender Elements, Resonant Column and Torsional Shear tests. Our aim was to compare the results of the different test methods and use the resulting soil properties for 1D ground response analysis. Often in practice, there are little-to no data available on dynamic soil properties and estimated parameters are used for design. Therefore, a comparison is made between results based on estimated parameters and those based on detailed investigations. Ground response results are also compared to Eurocode 8 design spectra.

Keywords: MASW, resonant column test, SCPT, site response analysis, torsional shear test

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Prajakta Patil, Yash Huzurbazar, Abhijeet Shinde

Abstract:

Aim: To develop a treatment protocol for the management of tinnitus through multi-modality brain stimulation. Methodology: Present study included 33 adults with unilateral (31 subjects) and bilateral (2 subjects) chronic tinnitus with and/or without hearing loss independent of their etiology. The Treatment protocol included 5 consecutive sessions with follow-up of 6 months. Each session was divided into 3 parts: • Pre-treatment: a) Informed consent b) Pitch and loudness matching. • Treatment: Bimanual paper pen task with tinnitus masking for 30 minutes. • Post-treatment: a) Pitch and loudness matching b) Directive counseling and obtaining feedback. Paper-pen task is to be performed bimanually that included carrying out two different writing activities in different context. The level of difficulty of the activities was increased in successive sessions. Narrowband noise of a frequency same as that of tinnitus was presented at 10 dBSL of tinnitus for 30 minutes simultaneously in the ear with tinnitus. Result: The perception of tinnitus was no longer present in 4 subjects while in remaining subjects it reduced to an intensity that its perception no longer troubled them without causing residual facilitation. In all subjects, the intensity of tinnitus decreased by an extent of 45 dB at an average. However, in few subjects, the intensity of tinnitus also decreased by more than 45 dB. The approach resulted in statistically significant reductions in Tinnitus Functional Index and Tinnitus Handicap Inventory scores. The results correlate with pre and post treatment score of Tinnitus Handicap Inventory that dropped from 90% to 0%. Discussion: Brain mapping(qEEG) Studies report that there is multiple parallel overlapping of neural subnetworks in the non-auditory areas of the brain which exhibits abnormal, constant and spontaneous neural activity involved in the perception of tinnitus with each subnetwork and area reflecting a specific aspect of tinnitus percept. The paper pen task and directive counseling are designed and delivered respectively in a way that is assumed to induce normal, rhythmically constant and premeditated neural activity and mask the abnormal, constant and spontaneous neural activity in the above-mentioned subnetworks and the specific non-auditory area. Counseling was focused on breaking the vicious cycle causing and maintaining the presence of tinnitus. Diverting auditory attention alone is insufficient to reduce the perception of tinnitus. Conscious awareness of tinnitus can be suppressed when individuals engage in cognitively demanding tasks of non-auditory nature as the paper pen task used in the present study. To carry out this task selective, divided, sustained, simultaneous and split attention act cumulatively. Bimanual paper pen task represents a top-down activity which underlies brain’s ability to selectively attend to the bimanual written activity as a relevant stimulus and to ignore tinnitus that is the irrelevant stimuli in the present study. Conclusion: The study suggests that this novel treatment approach is cost effective, time saving and efficient to vanish the tinnitus or to reduce the intensity of tinnitus to a negligible level and thereby eliminating the negative reactions towards tinnitus.

Keywords: multi-modality brain stimulation, neural subnetworks, non-auditory areas, paper-pen task, top-down activity

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Authors: Bjørn Salskov, Nicolaj Bang, Charlotte Falko

Abstract:

Future labour markets demand employees that can carry out a non-linear task which is still not possible for computers. This means that employees must have well-developed soft-skills to perform at high levels in such a work environment. One of these soft-skills is presenting a message effectively. To be able to present a message effectively, one needs to practice this. To practice effectively, the trainee needs feedback on the current performance. Here VR environments can be used as a practice tool because it gives the trainee a sense of presence and reality. VR environments are becoming a cost-effective training method since it does not demand the presence of an expert to provide this feedback. The research article analysed in this study suggests that VR environment can be used and are able to provide the necessary feedback to the trainee which in turn will help the trainee become better at the task. The research analysed in this review does, however, show that there is a need for a study with larger sample size and a study which runs over a longer period.

Keywords: training, presentation, presentation skills, VR training, VR as a training tool, VR and presentation

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