Search results for: Collaborative sensors

Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: Emotion identification, emotion models, gesture recognition, user perception.

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Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol.

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Authors: Eu Tteum Ha, Kwang Ryel Ryu

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As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

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Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: Accelerometer, activity recognition, directional cosine matrix filter, gyroscope, Kalman filter, magnetometer.

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Authors: Sheikh I. Azid, Bibhya Sharma

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A low cost Short Message System (SMS) based Home security system equipped with motion, smoke, temperature, humidity and light sensors has been studied and tested. The sensors are controlled by a microprocessor PIC 18F4520 through the SMS having password protection code for the secure operation. The user is able to switch light and the appliances and get instant feedback. Also in cases of emergencies such as fire or robbery the system will send alert message to occupant and relevant civil authorities. The operation of the home security has been tested on Vodafone- Fiji network and Digicel Fiji Network for emergency and feedback responses for 25 samples. The experiment showed that it takes about 8-10s for the security system to respond in case of emergency. It takes about 18-22s for the occupant to switch and monitor lights and appliances and then get feedback depending upon the network traffic.

Keywords: Smart Home, SMS, Sensors, Microprocessor.

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Authors: Vincent Lau Chun Fai, Yang Doo Lee, Kyongsoo Lee, Keun-Soo Lee, Shin-Kyung, Byeong-Kwon Ju

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Chemical detection is still a continuous challenge when it comes to designing single-walled carbon nanotube (SWCNT) sensors with high selectivity, especially in complex chemical environments. A perfect example of such an environment would be in thermally oxidized soybean oil. At elevated temperatures, oil oxidizes through a series of chemical reactions which results in the formation of monoacylglycerols, diacylglycerols, oxidized triacylglycerols, dimers, trimers, polymers, free fatty acids, ketones, aldehydes, alcohols, esters, and other minor products. In order to detect the rancidity of oxidized soybean oil, carbon nanotube chemiresistor sensors have been coated with polyethylenimine (PEI) to enhance the sensitivity and selectivity. PEI functionalized SWCNTs are known to have a high selectivity towards strong electron withdrawing molecules. The sensors were very responsive to different oil oxidation levels and furthermore, displayed a rapid recovery in ambient air without the need of heating or UV exposure.

Keywords: Carbon nanotubes, polyethylenimine, sensor, oxidized oil

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Authors: Kiwon Rhee, Kyung-Jin You, Hyun-Chool Shin

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This paper proposes a method of remotely controlling robots with arm gestures using surface electromyography (EMG) and accelerometer sensors attached to the operator’s wrists. The EMG and accelerometer sensors receive signals from the arm gestures of the operator and infer the corresponding movements to execute the command to control the robot. The movements of the robot include moving forward and backward and turning left and right. The accuracy is over 99% and movements can be controlled in real time.

Keywords: EMG, accelerometer, K-nn, entropy.

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Authors: Monika Jain, Shikhar Puri, Shivali Unishree

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This paper presents the ‘Eye Ball Motion Controlled Wheelchair using IR Sensors’ for the elderly and differently abled people. In this eye tracking based technology, three Proximity Infrared (IR) sensor modules are mounted on an eye frame to trace the movement of the iris. Since, IR sensors detect only white objects; a unique sequence of digital bits is generated corresponding to each eye movement. These signals are then processed via a micro controller IC (PIC18F452) to control the motors of the wheelchair. The potential and efficiency of previously developed rehabilitation systems that use head motion, chin control, sip-n-puff control, voice recognition, and EEG signals variedly have also been explored in detail. They were found to be inconvenient as they served either limited usability or non-affordability. After multiple regression analyses, the proposed design was developed as a cost-effective, flexible and stream-lined alternative for people who have trouble adopting conventional assistive technologies.

Keywords: Eye tracking technology, Intelligent wheelchair, IR module, rehabilitation technology.

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Authors: Ye. B. Utepov, A. S. Tulebekova, A. B. Kazkeyev

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Maturity sensors are used to determine concrete strength by the non-destructive method. The method of placement of the maturity sensors determines their number required for a certain frame of a monolithic building. This paper proposes a cheap prototype of an embedded wireless sensor for monitoring concrete structures, as well as an alternative strategy for placing sensors based on the transitional boundaries of the temperature distribution of concrete curing, which were determined by building a heat map of the temperature distribution, where unknown values are calculated by the method of inverse distance weighing. The developed prototype can simultaneously measure temperature and relative humidity over a smartphone-controlled time interval. It implements a maturity method to assess the in-situ strength of concrete, which is considered an alternative to the traditional shock impulse and compression testing method used in Kazakhstan. The prototype was tested in laboratory and field conditions. The tests were aimed at studying the effect of internal and external temperature and relative humidity on concrete's strength gain. Based on an experimentally poured concrete slab with randomly integrated maturity sensors, it the transition boundaries form elliptical forms were determined. Temperature distribution over the largest diameter of the ellipses was plotted, resulting in correct and inverted parabolas. As a result, the distance between the closest opposite crossing points of the parabolas is accepted as the maximum permissible step for setting the maturity sensors. The proposed placement strategy can be applied to sensors that measure various continuous phenomena such as relative humidity. Prototype testing has also revealed Bluetooth inconvenience due to weak signal and inability to access multiple prototypes simultaneously. For this reason, further prototype upgrades are planned in the future work.

Keywords: Heat map, placement strategy, temperature and relative humidity, wireless embedded sensor.

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Authors: D. Satish Kumar, N. Nagarajan

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Coverage conservation and extend the network lifetime are the primary issues in wireless sensor networks. Due to the large variety of applications, coverage is focus to a wide range of interpretations. The applications necessitate that each point in the area is observed by only one sensor while other applications may require that each point is enclosed by at least sensors (n>1) to achieve fault tolerance. Sensor scheduling activities in existing Transparent and non- Transparent relay modes (T-NT) Mobile Multi-Hop relay networks fails to guarantee area coverage with minimal energy consumption and fault tolerance. To overcome these issues, Cluster based Energy Competent n- coverage scheme called (CEC n-coverage scheme) to ensure the full coverage of a monitored area while saving energy. CEC n-coverage scheme uses a novel sensor scheduling scheme based on the n-density and the remaining energy of each sensor to determine the state of all the deployed sensors to be either active or sleep as well as the state durations. Hence, it is attractive to trigger a minimum number of sensors that are able to ensure coverage area and turn off some redundant sensors to save energy and therefore extend network lifetime. In addition, decisive a smallest amount of active sensors based on the degree coverage required and its level. A variety of numerical parameters are computed using ns2 simulator on existing (T-NT) Mobile Multi-Hop relay networks and CEC n-coverage scheme. Simulation results showed that CEC n-coverage scheme in wireless sensor network provides better performance in terms of the energy efficiency, 6.61% reduced fault tolerant in terms of seconds and the percentage of active sensors to guarantee the area coverage compared to exiting algorithm.

Keywords: Wireless Sensor network, Mobile Multi-Hop relay networks, n-coverage, Cluster based Energy Competent, Transparent and non- Transparent relay modes, Fault Tolerant, sensor scheduling.

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Authors: G. Büyüközkan , O. Feyzioglu, Z. Vardaloglu

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Collaborative planning, forecasting and replenishment (CPFR) coordinates the various supply chain management activities including production and purchase planning, demand forecasting and inventory replenishment between supply chain trading partners. This study proposes a systematic way of analyzing CPFR supporting factors using fuzzy cognitive map (FCM) approach. FCMs have proven particularly useful for solving problems in which a number of decision variables and uncontrollable variables are causally interrelated. Hence the FCMs of CPFR are created to show the relationships between the factors that influence on effective implementation of CPFR in the supply chain.

Keywords: Collaborative planning, forecasting and replenishment, fuzzy cognitive map, information sharing, decision synchronization, incentive alignment.

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Authors: Jieh-Shian Young, Chan Wei Hsu

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This paper mainly studies the analyses of parameters in the intersection collision avoidance (ICA) system based on the radar sensors. The parameters include the positioning errors, the repeat period of the radar sensor, the conditions of potential collisions of two cross-path vehicles, etc. The analyses of the parameters can provide the requirements, limitations, or specifications of this ICA system. In these analyses, the positioning errors will be increased as the measured vehicle approach the intersection. In addition, it is not necessary to implement the radar sensor in higher position since the positioning sensitivities become serious as the height of the radar sensor increases. A concept of the safety buffer distances for front and rear of the measured vehicle is also proposed. The conditions for potential collisions of two cross-path vehicles are also presented to facilitate the computation algorithm.

Keywords: Intersection Collision Avoidance (ICA), Positioning Errors, Radar Sensors, Sensitivity of Positioning.

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Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong

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This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.

Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.

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Authors: Radwa Mabrook

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Virtual Reality (VR) content creation is a complex and an expensive process, which requires multi-disciplinary teams of content creators. Grant schemes from technology companies help media organisations to explore the VR potential in journalism and factual storytelling. Media organisations try to do as much as they can in-house, but they may outsource due to time constraints and skill availability. Journalists, game developers, sound designers and creative artists work together and bring in new cultures of work. This study explores the collaborative experimental nature of VR content creation, through tracing every actor involved in the process and examining their perceptions of the VR work. The study builds on Actor Network Theory (ANT), which decomposes phenomena into their basic elements and traces the interrelations among them. Therefore, the researcher conducted 22 semi-structured interviews with VR content creators between November 2017 and April 2018. Purposive and snowball sampling techniques allowed the researcher to recruit fact-based VR content creators from production studios and media organisations, as well as freelancers. Interviews lasted up to three hours, and they were a mix of Skype calls and in-person interviews. Participants consented for their interviews to be recorded, and for their names to be revealed in the study. The researcher coded interviews’ transcripts in Nvivo software, looking for key themes that correspond with the research questions. The study revealed that VR content creators must be adaptive to change, open to learn and comfortable with mistakes. The VR content creation process is very iterative because VR has no established work flow or visual grammar. Multi-disciplinary VR team members often speak different languages making it hard to communicate. However, adaptive content creators perceive VR work as a fun experience and an opportunity to learn. The traditional sense of competition and the strive for information exclusivity are now replaced by a strong drive for knowledge sharing. VR content creators are open to share their methods of work and their experiences. They target to build a collaborative network that aims to harness VR technology for journalism and factual storytelling. Indeed, VR is instilling collaborative and experimental cultures in journalism.

Keywords: Collaborative culture, content creation, experimental culture, virtual reality.

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Authors: Byung-kyoo Jung, Weui-bong Jeong

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In most cases, it is considerably difficult to directly measure structural vibration with a lot of sensors because of complex geometry, time and equipment cost. For this reason, this paper deals with the problem of locating sensors on a plate model by four advanced sensor placement optimization (S.P.O) techniques. It also suggests the evaluation index representing the characteristic of orthogonal between each of natural modes. The index value provides the assistance to selecting of proper S.P.O technique and optimal positions for monitoring of dynamic systems without the experiment.

Keywords: Genetic algorithm, Modal assurance criterion, Sensor placement optimization.

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Authors: Wenlong Feng, Zhenchun Du, Jianguo Yang

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To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detection is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15μm/10m and the accuracy of the machine tool is significant improved.

Keywords: Thermal expansion error of grating scale, error compensation, machine tools, integral method.

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Authors: Leong Lee, Jennifer Leopold, Julia Albath, Alton Coalter

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As more people from non-technical backgrounds are becoming directly involved with large-scale ontology development, the focal point of ontology research has shifted from the more theoretical ontology issues to problems associated with the actual use of ontologies in real-world, large-scale collaborative applications. Recently the National Science Foundation funded a large collaborative ontology development project for which a new formal ontology model, the Ontology Abstract Machine (OAM), was developed to satisfy some unique functional and data representation requirements. This paper introduces the OAM model and the related algorithms that enable maintenance of an ontology that supports node-based user access. The successful software implementation of the OAM model and its subsequent acceptance by a large research community proves its validity and its real-world application value.

Keywords: Ontology, Abstract Machine, Ontology Editor, WebbasedOntology Management System.

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Authors: Tae Kyung Kim, Hee Suk Seo

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Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.

Keywords: Fuzzy, Sensor Networks, Trust.

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Authors: Mabel Ortiz, Claudio Díaz

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This paper explores Chilean pre-service teachers' perceptions about the provision of corrective feedback in a wiki environment during the collaborative writing of an argumentative essay. After conducting a semi-structured interview on 22 participants, the data were processed through the content analysis technique. The results show that students have positive perceptions about corrective feedback, provided through a wiki virtual environment, which in turn facilitates feedback provision and impacts language learning effectively. Some of the positive perceptions about virtual feedback refer to permanent access, efficiency, simultaneous revision and immediacy. It would then be advisable to integrate wiki-based feedback as a methodology for the language classroom and collaborative writing tasks.

Keywords: Argumentative essay, focused corrective feedback, perception, wiki environment.

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps.

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Authors: Seung You Na, Daejung Shin, Jin Young Kim, Bae-Ho Lee, Ji-Sung Lee

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There has been a growing interest in the field of bio-mimetic robots that resemble the shape of an insect or an aquatic animal, among many others. One bio-mimetic robot serves the purpose of exploring pipelines, spotting any troubled areas or malfunctions and reporting its data. Moreover, the robot is able to prepare for and react to any abnormal routes in the pipeline. In order to move effectively inside a pipeline, the robot-s movement will resemble that of a lizard. When situated in massive pipelines with complex routes, the robot places fixed sensors in several important spots in order to complete its monitoring. This monitoring task is to prevent a major system failure by preemptively recognizing any minor or partial malfunctions. Areas uncovered by fixed sensors are usually impossible to provide real-time observation and examination, and thus are dependant on periodical offline monitoring. This paper provides the Monitoring System that is able to monitor the entire area of pipelines–with and without fixed sensors–by using the bio-mimetic robot.

Keywords: Bio-mimetic robots, Plant pipes monitoring, Mobileand active monitoring.

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Authors: Omnia F. Elkommos

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In the course of teaching stylistics to undergraduate students of the Department of English Language and Literature, Faculty of Arts and Humanities, the linguistic tool kit of theories comes in handy and useful for the better understanding of the different literary genres: Poetry, drama, and short stories. In the present paper, a model of teaching of stylistics is compiled and suggested. It is a collaborative group project technique for use in the undergraduate diverse specialisms (Literature, Linguistics and Translation tracks) class. Students initially are introduced to the different linguistic tools and theories suitable for each literary genre. The second step is to apply these linguistic tools to texts. Students are required to watch videos performing the poems or play, for example, and search the net for interpretations of the texts by other authorities. They should be using a template (prepared by the researcher) that has guided questions leading students along in their analysis. Finally, a practical analysis would be written up using the practical analysis essay template (also prepared by the researcher). As per collaborative learning, all the steps include activities that are student-centered addressing differentiation and considering their three different specialisms. In the process of selecting the proper tools, the actual application and analysis discussion, students are given tasks that request their collaboration. They also work in small groups and the groups collaborate in seminars and group discussions. At the end of the course/module, students present their work also collaboratively and reflect and comment on their learning experience. The module/course uses a drama play that lends itself to the task: ‘The Bond’ by Amy Lowell and Robert Frost. The project results in an interpretation of its theme, characterization and plot. The linguistic tools are drawn from pragmatics, and discourse analysis among others.

Keywords: Applied linguistic theories, collaborative learning, cooperative principle, discourse analysis, drama analysis, group project, online acting performance, pragmatics, speech act theory, stylistics, technology enhanced learning.

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Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. UAV techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. In this paper, a methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of RGB and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: Aerial thermography, data processing, drone, low-cost, point cloud.

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Authors: Yu-Kyung Kang, Suk-Hyung Hwang, Kyoung-Mo Yang

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The tagging data of (users, tags and resources) constitutes a folksonomy that is the user-driven and bottom-up approach to organizing and classifying information on the Web. Tagging data stored in the folksonomy include a lot of very useful information and knowledge. However, appropriate approach for analyzing tagging data and discovering hidden knowledge from them still remains one of the main problems on the folksonomy mining researches. In this paper, we have proposed a folksonomy data mining approach based on FCA for discovering hidden knowledge easily from folksonomy. Also we have demonstrated how our proposed approach can be applied in the collaborative tagging system through our experiment. Our proposed approach can be applied to some interesting areas such as social network analysis, semantic web mining and so on.

Keywords: Folksonomy data mining, formal concept analysis, collaborative tagging, conceptual knowledge discovery, classification.

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Authors: Bastian Hartmann, Christoph Schauer, Norbert Link

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This paper addresses the problem of recognizing and interpreting the behavior of human workers in industrial environments for the purpose of integrating humans in software controlled manufacturing environments. In this work we propose a generic concept in order to derive solutions for task-related manual production applications. Thus, we are able to use a versatile concept providing flexible components and being less restricted to a specific problem or application. We instantiate our concept in a spot welding scenario in which the behavior of a human worker is interpreted when performing a welding task with a hand welding gun. We acquire signals from inertial sensors, video cameras and triggers and recognize atomic actions by using pose data from a marker based video tracking system and movement data from inertial sensors. Recognized atomic actions are analyzed on a higher evaluation level by a finite state machine.

Keywords: activity recognition, task modeling, marker-based video-tracking, inertial sensors.

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Authors: Indiramma M., K. R. Anandakumar

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Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

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Authors: N.M Abdul Ghani, L.K. Haur, T.P.Yon, F Naim

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This project relates to a two-wheeled self balancing robot for transferring loads on different locations along a path. This robot specifically functions as a dual mode navigation to navigate efficiently along a desired path. First, as a plurality of distance sensors mounted at both sides of the body for collecting information on tilt angle of the body and second, as a plurality of speed sensors mounted at the bottom of the body for collecting information of the velocity of the body in relative to the ground. A microcontroller for processing information collected from the sensors and configured to set the path and to balance the body automatically while a processor operatively coupled to the microcontroller and configured to compute change of the tilt and velocity of the body. A direct current motor operatively coupled to the microcontroller for controlling the wheels and characterized in that a remote control is operatively coupled to the microcontroller to operate the robot in dual navigation modes.

Keywords: Two-Wheeled Balancing Robot, Dual Mode Navigation, Remote Control, Desired Path.

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Authors: Kyoung-Jae Kim, Hyunchul Ahn

Abstract:

This study proposes novel hybrid social network analysis and collaborative filtering approach to enhance the performance of recommender systems. The proposed model selects subgroups of users in Internet community through social network analysis (SNA), and then performs clustering analysis using the information about subgroups. Finally, it makes recommendations using cluster-indexing CF based on the clustering results. This study tries to use the cores in subgroups as an initial seed for a conventional clustering algorithm. This model chooses five cores which have the highest value of degree centrality from SNA, and then performs clustering analysis by using the cores as initial centroids (cluster centers). Then, the model amplifies the impact of friends in social network in the process of cluster-indexing CF.

Keywords: Social network analysis, Recommender systems, Collaborative filtering, Customer relationship management

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Authors: D. Sathan, A. Meetoo, R. K. Subramaniam

Abstract:

Context awareness is a capability whereby mobile computing devices can sense their physical environment and adapt their behavior accordingly. The term context-awareness, in ubiquitous computing, was introduced by Schilit in 1994 and has become one of the most exciting concepts in early 21st-century computing, fueled by recent developments in pervasive computing (i.e. mobile and ubiquitous computing). These include computing devices worn by users, embedded devices, smart appliances, sensors surrounding users and a variety of wireless networking technologies. Context-aware applications use context information to adapt interfaces, tailor the set of application-relevant data, increase the precision of information retrieval, discover services, make the user interaction implicit, or build smart environments. For example: A context aware mobile phone will know that the user is currently in a meeting room, and reject any unimportant calls. One of the major challenges in providing users with context-aware services lies in continuously monitoring their contexts based on numerous sensors connected to the context aware system through wireless communication. A number of context aware frameworks based on sensors have been proposed, but many of them have neglected the fact that monitoring with sensors imposes heavy workloads on ubiquitous devices with limited computing power and battery. In this paper, we present CALEEF, a lightweight and energy efficient context aware framework for resource limited ubiquitous devices.

Keywords: Context-Aware, Energy-Efficient, Lightweight, Ubiquitous Devices.

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Authors: Nicolay Zarutskiy, Roman Bulkin

Abstract:

The paper deals with the existing methods of force-torque sensor calibration with a number of components from one to six, analyzed their advantages and disadvantages, the necessity of introduction of a calibration method. Calibration method and its constructive realization are also described here. A calibration method allows performing automated force-torque sensor calibration both with selected components of the main vector of forces and moments and with complex loading. Thus, two main advantages of the proposed calibration method are achieved: the automation of the calibration process and universality.

Keywords: Automation, calibration, calibration device, calibration method, force-torque sensors.

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