Search results for: task messages

Authors: Poojitha Vemula

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Understanding how we use image manipulation to communicate through an audience’s perceptions and conceive visual intelligence. With the use of many software and high-end skills, designers have developed a third eye to combine two different visuals and create the desired image by using photoshop and other software skills. The purpose of visual intelligence is to convey a message to the targeted audience. For instance, the images of models are retouched on their skin to make it more convincing and draw attention from the audience. There are many ways of manipulating an image, such as double exposure, retouching photography inks or paint airbrushing and piecing photos together, or enhancing the brightness and contrast. To understand visual intelligence, a questionnaire survey as well as research was conducted on how image manipulation is used by both the audience and the designers. This depends on the message that needs to be conveyed by the brands. For instance, Fair & Lovely, a brightening cream for ladies use a lot of retouching and effects to show the dramatic change the cream takes effect on dark or dusky faces. Thus the designer’s role is to use their third eye to incorporate the message into visuals. The research and questionnaire survey concludes the perceptions and manipulations used in visual communication. However this is all to make an effortless communication between the designer and the audience by using the skills of the designer and the features provided by the software. The objective of visual intelligence is to covet the message of the brands that advertise their products or services by using visuals through softwares. Conveying a message through visual intelligence requires an audiences perceptions and understanding from the visuals created by the artists or designers. Visual intelligence determines how we use our technical skills to retouch and manipulate an image for a better understanding to convey the message to the targeted audience. This also bridges the communication between the brand and the audience.

Keywords: graphic design, visual communication, convey messages, photoshop, image manipulation

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Authors: C. Malça, N. Alves, A. Mateus

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This work was one of the tasks of the Manufacturing2Client project, whose objective was to develop a frontal deflector to be commercialized in the automotive industry, using new project and manufacturing methods. In this task, in particular, it was proposed to develop the ability to predict computationally the aerodynamic influence of flow in vehicles, in an effort to reduce fuel consumption in vehicles from class 3 to 8. With this aim, two deflector models were developed and their aerodynamic performance analyzed. The aerodynamic study was done using the Computational Fluid Dynamics (CFD) software Ansys CFX and allowed the calculation of the drag coefficient caused by the vehicle motion for the different configurations considered. Moreover, the reduction of diesel consumption and carbon dioxide (CO2) emissions associated with the optimized deflector geometry could be assessed.

Keywords: erodynamic analysis, CFD, CO2 emissions, drag coefficient, frontal deflector, fuel consumption

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Authors: Monica Hoeldtke Pietruchinski, Andrey Ricardo Pimentel

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The teaching of computer programming for beginners has been presented to the community as a not simple or trivial task. Several methodologies and research tools have been developed; however, the problem still remains. This paper aims to present multi-agent system architecture to be incorporated to the educational collaborative game software for teaching programming that monitors, evaluates and encourages collaboration by the participants. A literature review has been made on the concepts of Collaborative Learning, Multi-agents systems, collaborative games and techniques to teach programming using these concepts simultaneously.

Keywords: architecture of multi-agent systems, collaborative evaluation, collaboration assessment, gamifying educational software

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Authors: Huayuan Lu, Chunfang Yang, Ma Zhu, Baojun Qi, Yaqiong Qiao, Jiangqian Xu

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Image geolocalization has great application prospects in fields such as autonomous driving and virtual/augmented reality. In practical application scenarios, the size of the image to be located is not fixed; it is impractical to train different networks for all possible sizes. When its size does not match the size of the input of the descriptor extraction model, existing image geolocalization methods usually directly scale or crop the image in some common ways. This will result in the loss of some information important to the geolocalization task, thus affecting the performance of the image geolocalization method. For example, excessive down-sampling can lead to blurred building contour, and inappropriate cropping can lead to the loss of key semantic elements, resulting in incorrect geolocation results. To address this problem, this paper designs a learnable image resizer and proposes an arbitrary-sized image geolocation method. (1) The designed learnable image resizer employs the self-attention mechanism to enhance the geometric features of the resized image. Firstly, it applies bilinear interpolation to the input image and its feature maps to obtain the initial resized image and the resized feature maps. Then, SKNet (selective kernel net) is used to approximate the best receptive field, thus keeping the geometric shapes as the original image. And SENet (squeeze and extraction net) is used to automatically select the feature maps with strong contour information, enhancing the geometric features. Finally, the enhanced geometric features are fused with the initial resized image, to obtain the final resized images. (2) The proposed image geolocalization method embeds the above image resizer as a fronting layer of the descriptor extraction network. It not only enables the network to be compatible with arbitrary-sized input images but also enhances the geometric features that are crucial to the image geolocalization task. Moreover, the triplet attention mechanism is added after the first convolutional layer of the backbone network to optimize the utilization of geometric elements extracted by the first convolutional layer. Finally, the local features extracted by the backbone network are aggregated to form image descriptors for image geolocalization. The proposed method was evaluated on several mainstream datasets, such as Pittsburgh30K, Tokyo24/7, and Places365. The results show that the proposed method has excellent size compatibility and compares favorably to recently mainstream geolocalization methods.

Keywords: image geolocalization, self-attention mechanism, image resizer, geometric feature

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Authors: Yadavalli Venkata Sridhar

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Finalization of Substation sizing and location is an important task to be carried out by electrical designers in an oil field. Practical issues influence the selection of size and location of the source substations that feed multiple production facilities are listed. Importance of selection of appropriately rated short circuit level for 11KV switchboards and constraints pertaining to availability of manufacturers are highlighted. Without being lost in the research of absolute optimum solution, under time constraints, the importance of practical approach is brought out. Focus on identifying near optimum solutions by process of elimination of unfeasible substation locations with the support of cost figures, is emphasized through a case study.

Keywords: substation, size, location, oil field

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Authors: András Rövid, Takeshi Hashimoto

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The paper focuses on the problem of the point correspondence matching in stereo images. The proposed matching algorithm is based on the combination of simpler methods such as normalized sum of squared differences (NSSD) and a more complex phase correlation based approach, by considering the noise and other factors, as well. The speed of NSSD and the preciseness of the phase correlation together yield an efficient approach to find the best candidate point with sub-pixel accuracy in stereo image pairs. The task of the NSSD in this case is to approach the candidate pixel roughly. Afterwards the location of the candidate is refined by an enhanced phase correlation based method which in contrast to the NSSD has to run only once for each selected pixel.

Keywords: stereo matching, sub-pixel accuracy, phase correlation, SVD, NSSD

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Authors: Wassim Jerbi, Abderrahmen Guermazi, Hafedh Trabelsi

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The optimum use of coverage in wireless sensor networks (WSNs) is very important. LEACH protocol called Low Energy Adaptive Clustering Hierarchy, presents a hierarchical clustering algorithm for wireless sensor networks. LEACH is a protocol that allows the formation of distributed cluster. In each cluster, LEACH randomly selects some sensor nodes called cluster heads (CHs). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node joins a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus, several sensor nodes cannot reach any CH. to solve this problem. We created an O-LEACH Orphan nodes protocol, its role is to reduce the sensor nodes which do not belong the cluster. The cluster member called Gateway receives messages from neighboring orphan nodes. The gateway informs CH having the neighboring nodes that not belong to any group. However, Gateway called (CH') attaches the orphaned nodes to the cluster and then collected the data. O-Leach enables the formation of a new method of cluster, leads to a long life and minimal energy consumption. Orphan nodes possess enough energy and seeks to be covered by the network. The principal novel contribution of the proposed work is O-LEACH protocol which provides coverage of the whole network with a minimum number of orphaned nodes and has a very high connectivity rates.As a result, the WSN application receives data from the entire network including orphan nodes. The proper functioning of the Application requires, therefore, management of intelligent resources present within each the network sensor. The simulation results show that O-LEACH performs better than LEACH in terms of coverage, connectivity rate, energy and scalability.

Keywords: WSNs; routing; LEACH; O-LEACH; Orphan nodes; sub-cluster; gateway; CH’

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Authors: Froogh Shooshtaryzadeh, Pramod Pandey

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The present study investigates place and manner harmony in typically developing (TD) children and children with phonological disorder (PD) who are acquiring Farsi as their first language. Five TD and five PD children are examined regarding their place and manner harmony patterns. Data is collected through a Picture-Naming Task using 132 pictures of different items designed to elicit the production of 132 different words. The examination of the data has indicated some similarities and differences in harmony patterns in PD and TD children. Moreover, the results of this study on the place and manner harmony have illustrated some differences with the results of the preceding studies on languages other than Farsi. The results of this study are discussed and compared with results from other studies. Optimality Theory is employed to explain some of the findings of this study.

Keywords: place harmony, manner harmony, phonological development, Farsi

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Authors: Mustafa Ekici

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Natural convection is a basic process which is important in a wide variety of practical applications. In essence, a heated fluid expands and rises from buoyancy due to decreased density. Numerous papers have been written on natural or mixed convection in vertical ducts heated on the side. These equations have been proved to be valuable tools for the modelling of many phenomena such as fluid dynamics. Finding solutions to such equations or system of equations are in general not an easy task. We propose a method, which is called differential transform method, of solving a non-linear equations and compare the results with some of the other techniques. Illustrative examples shows that the results are in good agreement.

Keywords: differential transform method, momentum, energy equation, boundry value problem

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Authors: Saadia Drissi

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The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

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Authors: Kabil Boukhari

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In the context of information retrieval, the selection of the most relevant words is a very important step. In fact, the text cleaning allows keeping only the most representative words for a better use. In this paper, we propose a library for the purpose text preprocessing within an implemented application to facilitate this task. This study has two purposes. The first, is to present the related work of the various steps involved in text preprocessing, presenting the segmentation, stemming and lemmatization algorithms that could be efficient in the rest of study. The second, is to implement a developed tool for text preprocessing in French and English. This library accepts unstructured text as input and provides the preprocessed text as output, based on a set of rules and on a base of stop words for both languages. The proposed library has been made on different corpora and gave an interesting result.

Keywords: text preprocessing, segmentation, knowledge extraction, normalization, text generation, information retrieval

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Authors: Gwendy Darras, Mattias Desmet

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Previous research showed that psychological distress has a negative impact on the disease course of viral infections. For COVID-19, the same association was observed in small samples of specific segments of the population (e.g. health care workers). The present study presents a more refined analysis of this association, measuring a broader spectrum of psychological distress in a large sample (n=3084) of the general Flemish population. Several types of psychological distress (state, trait and health anxiety, depression, intra-, and interpersonal stress) are registered throughout three periods: one year before the contamination, one week before the contamination, and during the contamination. In doing so, validated scales such as DASS-21, IIP-32, and FCV-19S are used. Furthermore, the course of COVID-19 is registered in several ways: number of symptoms, number of days sick leave due to COVID-19, and number of days the symptoms have lasted. Also, different control variables such as vaccination status, medical and psychological history are taken into account. Statistical analysis shows that all types of psychological distress are positively correlated with the severity of the COVID-19 disease course. Anxiety during the contamination shows the strongest correlation, but psychological distress one year before the onset of COVID-19 was still significantly associated with the worsening of the disease course. As the assessment of the latter type of distress happened before the onset of the COVID-19 disease course, retrospective bias resulting in artificial associations between self-reported stress and COVID-19 severity is unlikely to have impacted the observations. In view of possible future pandemics, it is important to focus on general stress and anxiety reduction in the general population as soon as possible. It is also advisable to minimize the use of stress-inducing messages to encourage the population to adhere to the measures issued during a pandemic.

Keywords: anxiety, COVID-19, depression, psychoneuroimmunology, psychological distress, stress

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Shazia Anwer

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This paper has discussed the unusual form of resistance in theatre against censorship board in Pakistan. The atypical approach of dramaturgy created massive space for performers and audiences to integrate and communicate. The social and religious absolutes creates suffocation in Pakistani society, strict control over all Fine and Performing Art has made art political, contemporary dramatics has started an amalgamated theatre to avoid censorship. Contemporary Punjabi theatre techniques are directly dependent on human cognition. The idea of indirect thought processing is not unique but dependent on spectators. The paper has provided an account of these techniques and their specific use for conveying specific messages across the audiences. For the Dramaturge of today, theatre space is an expression representing a linguistic formulation that includes qualities of experimental and non-traditional use of classical theatrical space in the context of fulfilling the concept of open theatre. Paper has explained the transformation of the theatrical experience into an event where the actor and the audience are co-existing and co-experiencing the dramatical experience. The denial of the existence of the 4th -Wall made two-way communication possible. This paper has elaborated that the previously marginalized genres such as naach, jugat, miras, are extensively included to counter the censorship board. Figurativeness, visual elements, allegory, scenic imagery are basic support system for contemporary Punjabi theatre. The body of the actor is used as a source for non-verbal communication, and for an escape from traditional theatrical space which by every means has every element that could be controlled and reprimanded by the controlling authority.

Keywords: communication, Punjabi theatre, figurativeness, censorship

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad, Nurfadhlina Mohammad Sharef

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Sarcasm is a common phenomenon in social media which is a nuanced form of language for stating the opposite of what is implied. Due to the intentional ambiguity, analysis of sarcasm is a difficult task not only for a machine but even for a human. Although sarcasm detection has an important effect on sentiment, it is usually ignored in social media analysis because sarcasm analysis is too complicated. While there is a few systems exist which can detect sarcasm, almost no work has been carried out on a study and the review of the existing work in this area. This survey presents a nearly full image of sarcasm detection techniques and the related fields with brief details. The main contributions of this paper include the illustration of the recent trend of research in the sarcasm analysis and we highlight the gaps and propose a new framework that can be explored.

Keywords: sarcasm detection, sentiment analysis, social media, sarcasm analysis

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Authors: Misha Teimouri

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Our world has been transformed by the use of the internet and the constant flow of information. While this transmission has its benefits, it has also added significant challenges to family relations, primarily in the field of parenting and children's digital lives. Screens, speed, and connectedness are the words that characterize the lives of today's digital generation; it's as if the entire world is in their pockets at all times. Parents attempt to regulate and control their children's internet use in the hopes of maximizing the advantages and minimizing the disadvantages of their children's internet use; however, given that children spend more time online, particularly ever since the pandemic, children's cyber-aggression has become an issue for them. Children may externalize their behavior online, bully others, send anger/hatred/resist messages, share violent and bloody content, and engage in sexting. These types of online aggression make parenting more difficult, especially for digital immigrant parents compared to digital native parents. In response to these challenges, this study investigated the level of cyber aggression among children, as well as the effects of digi-parenting (active, monitoring, restrictive, and warm and supportive) on children's cyber-aggression (sexual, verbal, visual) as victims or aggressors. The study also determined whether there were any differences in parenting styles between digital natives (DN) and digital immigrants. In accordance with the study, boys and older children are more likely to engage in cyber aggression as aggressors, whereas girls and younger children are more likely to engage as victims. Warmth and supportive digiparenting have a greater impact on children's cyber-aggression (sexual, verbal, and visual) as victims or aggressors. This study also found that, when compared to DI parents, DN parents are more successful at digi-parenting and reducing their children's exposure to cyber-aggression.

Keywords: digi-parenting, cyber-aggression, digital natives, digital immigrants, children's cyber-aggression (sexual, verbal, visual)

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Authors: Ayelet Hersch, Corrine Serfaty, Sigal Portnoy

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Stroke survivors commonly report persistent fatigue and sleep disruptions during rehabilitation and post-recovery. While limited research has explored the impact of stroke on a patient's chronotype, there is a gap in understanding the differences in cognitive performance based on treatment timing. Study objectives: (a) To characterize the sleep chronotype in sub-acute post-stroke individuals. (b) Explore cognitive task performance differences during preferred and non-preferred hours. (c) Examine the relationships between sleep quality and cognitive performance. For this intra-subject study, twenty participants (mean age 60.2±8.6) post-first stroke (6-12 weeks post stroke) underwent assessments at preferred and non-preferred chronotypic times. The assessment included demographic surveys, the Munich Chronotype Questionnaire, Montreal Cognitive Assessment (MoCA), Rivermead Behavioral Memory Test (RBMT), a fatigue questionnaire, and 4-5 days of actigraphy (wrist-worn wGT3X-BT, ActiGraph) to record sleep characteristics. Four sleep quality indices were extracted from actigraphy wristwatch recordings: The average of total sleep time per day (minutes), the average number of awakenings during the sleep period per day, the efficiency of sleep (total hours of sleep per day divided by hours spent in bed per day, averaged across the days and presented as percentage), and the Wake after Sleep Onset (WASO) index, indicating the average number of minutes elapsed from the onset of sleep to the first awakening. Stroke survivors exhibited an earlier sleep chronotype post-injury compared to pre-injury. Enhanced attention, as indicated by higher RBMT scores, occurred during preferred hours. Specifically, 30% of the study participants demonstrated an elevation in their final scores during their preferred hours, transitioning from the category of "mild memory impairment" to "normal memory." However, no significant differences emerged in executive functions, attention tasks, and MoCA scores between preferred and non-preferred hours. The Wake After Sleep Onset (WASO) index correlated with MoCA/RBMT scores during preferred hours (r=0.53/0.51, p=0.021/0.027, respectively). The number of awakenings correlated with MoCA letter task performance during non-preferred hours (r=0.45, p=0.044). Enhanced attention during preferred hours suggests a potential relationship between chronotype and cognitive performance, highlighting the importance of personalized rehabilitation strategies in stroke care. Further exploration of these relationships could contribute to optimizing the timing of cognitive interventions for stroke survivors.

Keywords: sleep chronotype, chronobiology, circadian rhythm, rehabilitation timing

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Authors: Shahpar Yilmaz, Yasir Nadeem, Syed A. Mehdi

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Searching for a record in a dataset is always a frequent task for any data structure-related application. Hence, a fast and efficient algorithm for the approach has its importance in yielding the quickest results and enhancing the overall productivity of the company. Interpolation search is one such technique used to search through a sorted set of elements. This paper proposes a new algorithm, an advancement over interpolation search for the application of search over a sorted array. Pattern Recognition Search or PR Search (PRS), like interpolation search, is a pattern-based divide and conquer algorithm whose objective is to reduce the sample size in order to quicken the process and it does so by treating the array as a perfect arithmetic progression series and thereby deducing the key element’s position. We look to highlight some of the key drawbacks of interpolation search, which are accounted for in the Pattern Recognition Search.

Keywords: array, complexity, index, sorting, space, time

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Authors: Daniel Vargas-Herrera, Ivette Caldelas, Fernando Brambila-Paz, Rodrigo Montufar-Chaveznava

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In this paper, we present a virtual reality application for neurorehabilitation. This application was developed using the Unity SDK integrating the Oculus Rift and Leap Motion devices. Essentially, it consists of three stages according to the kind of rehabilitation to carry on: ocular rehabilitation, head/neck rehabilitation, and eye-hand coordination. We build three scenes for each task; for ocular and head/neck rehabilitation, there are different objects moving in the field of view and extended field of view of the user according to some patterns relative to the therapy. In the third stage the user must try to touch with the hand some objects guided by its view. We report the primer results of the use of the application with healthy people.

Keywords: virtual reality, interactive technologies, video games, neurorehabilitation

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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

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

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Authors: Olupemi E. Oludare

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This paper discusses the thematic structure of Yoruba popular music of Southwest Nigeria. It examines the use of themes and variations in early and contemporary Juju music. The work is an outcome of a research developed by the author in his doctoral studies at the University of Lagos, Nigeria, with the aim of analyzing the thematic and motivic developments in Yoruba popular genres. Observations, interviews, live recordings and CDs were used as methods for eliciting information. Field recordings and CDs of selected musical samples were also transcribed and notated. The research established the prevalent use of string of themes by Juju musicians as a compositional technique in moving from one musical section to another, as they communicate the verbal messages in their song. These themes consisting of the popular ‘call and response’ form found in most African music, analogous to the western ‘subject and answer’ style of the fugue or sonata form, although without the tonic–dominant relations. Due to the short and repetitive form of African melodies and rhythms, a theme is restated as a variation, where its rhythmic and melodic motifs are stylistically developed and repeated, but still retaining its recognizable core musical structure. The findings of this study showed that Juju musicians generally often employ a thematic plan where new themes are used to arrange the songs into sections, and each theme is developed into variations in order to further expand the music, eliminate monotony, and create musical aesthetics, serving as hallmark of its musical identity. The study established the musical and extra-musical attributes of the genre, while recommending further research towards analyzing the various compositional techniques employed in African popular genres.

Keywords: compositional techniques, popular music, theme and variation, thematic development

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Authors: Jorge Duarte de Sá

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The project presented in this investigation is part of the multidisciplinary field of Architecture and explores an experience in media architecture, integrated in Arts, Science and Technology. The objective of this work is to create a visual experience comprehending Architecture, Media and Art. It is intended to specifically explore the sacred spaces that are losing social, cultural or religious dynamics and insert new Media technologies to create a new generate momentum, testing tools, techniques and methods of implementation. Given an architectural project methodology, it seems essential that 'the location' should be the starting point for the development of this technological apparatus: the church of Santa Clara in Santarém, Portugal emerged as an experimental space for apparatus, presenting itself as both temple and museum. We also aim to address the concept of rehabilitation through media technologies, directed at interventions that may have an impact on energizing spaces. The idea is emphasized on the rehabilitation of spaces that, one way or another, may gain new dynamics after a media intervention. Thus, we intend to affect the play with a sensitive and spiritual character which endemically, sacred spaces have, by exploring a sensitive aspect of the subject and drawing up new ideas for meditation and spiritual reflection. The work is designed primarily as a visual experience that encompasses the space, the object and the subject. It is a media project supported by a dual structure with two transparent screens operating in a holographic screen which will be projecting two images that complement the translucent overlay film, thus making the merger of two projections. The digitally created content reacts to the presence of observers through infrared cameras, placed strategically. The object revives the memory of the altarpiece as an architectural surface, promoting the expansion of messages through the media technologies.

Keywords: architecture, media, sacred, technology

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

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

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

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Authors: Shuo Liu

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

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

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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

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

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

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Authors: Lin Cheng, Zijiang Yang

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

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

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Authors: Prakash Singh

Abstract:

Employees who are satisfied at their place of work rate their leaders’ intrapersonal competencies as being high. They also believe that a leader’s intrapersonal competencies influence their sense of job satisfaction. Employees who indicate that they are unhappy at their place of work rate their leaders’ intrapersonal competencies as being low. They also believe that a leader’s intrapersonal intelligence influence their feeling of job satisfaction. The leader’s appropriate intrapersonal competencies are crucial to the creation of a motivated and satisfied employee team. In this study, the quantitative research method was used to determine the employees’ perceptions of their leaders’ intrapersonal competencies and their influence on their job satisfaction; the six competencies being self-awareness, self-confidence, self-expression, self-control, adaptability, and optimism. All the competencies of leaders identified in this quantitative study can therefore be described as intervening variables that influence an employee’s sense of job satisfaction. The number of responses that indicate that each of the intrapersonal competencies of a leader that will have an influence on an employee’s sense of job satisfaction, ranges from 93% (a leader’s sense of self-awareness) to 99% (a leader’s ability to be adaptable). As the responses are significantly similar, it can be stated that the respondents indicate that all the intrapersonal competencies of a leader can influence an employee’s sense of job satisfaction. The findings of this study strongly suggest that in order to be satisfied at work, employees prefer to be led by leaders who are confident in their leadership roles; who send out clear, unambiguous messages; who maintain self-control; who are adaptable and flexible;, who face the future with optimism and who support the establishment of a collegial working environment. Evidently, the findings corroborate the hypothesis that employees believe that the intrapersonal competencies of leaders have a positive influence on the employees’ sense of job satisfaction. This study’s findings, therefore, confirm that the key to the leaders’ self-knowledge is access to their own feelings and the ability to discriminate among them and draw upon them to guide behaviour in their organisations. This exploratory study makes a contribution to the emerging research being accomplished on leaders’ intrapersonal intelligence with more research still needing to be attempted to determine to what extent these competencies of leaders can reshape the organizational climate and culture.

Keywords: emotional intelligence, employees’ job satisfaction, leaders’ intrapersonal competencies, leaders’ self-knowledge

Procedia PDF Downloads 265

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

Abstract:

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

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

Procedia PDF Downloads 113