Search results for: assistant robot

Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Abdulmajeed Almansour

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Learning a foreign language with the assistant of technological tools has become an interest of learners and educators. Increased use of smartphones among undergraduate students has made them popular for not only social communication but also for entertainment and educational purposes. Smartphones have provided remarkable advantages in language learning process. Learning vocabulary is an important part of learning a language. The use of smartphone applications for English vocabulary learning provides an opportunity for learners to improve vocabulary knowledge beyond the classroom wall anytime anywhere. Recently, various smartphone applications were created specifically for vocabulary learning. This paper aims to explore the use of smartphone application Memrise designed for vocabulary learning to enhance academic vocabulary among undergraduate students. It examines whether the use of a Memrise smartphone application designed course enhances the academic vocabulary learning among ESL learners. The research paradigm used in this paper followed a mixed research model combining quantitative and qualitative research. The study included two hundred undergraduate students randomly assigned to the experimental and controlled group during the first academic year at the Faculty of English Language, Imam University. The research instruments included an attitudinal questionnaire and an English vocabulary pre-test administered to students at the beginning of the semester whereas post-test and semi-structured interviews administered at the end of the semester. The findings of the attitudinal questionnaire revealed a positive attitude towards using smartphones in learning vocabulary. The post-test scores showed a significant difference in the experimental group performance. The results from the semi-structure interviews showed that there were positive attitudes towards Memrise smartphone application. The students found the application enjoyable, convenient and efficient learning tool. From the study, the use of the Memrise application is seen to have long-term and motivational benefits to students. For this reason, there is a need for further research to identify the long-term optimal effects of learning a language using smartphone applications.

Keywords: second language vocabulary learning, academic vocabulary, mobile learning technologies, smartphone applications

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Authors: Adawati Suhaili, Kamisah Osman, Mohd Effendi, Ewan Mohd Matore

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The global education reform has prompted Malaysia to transform the education system in Malaysia through the Malaysian Education Blueprint (MEB) 2013-2025. This transformation is aimed to achieve the top one-third rank in international assessment. The low achievement of student scientific literacy in TIMMS (Trends in International Mathematics and Science Study ) and PISA (Programme for International Student Assessment) has caused concern to the Ministry Of Education (MOE) despite various reform efforts. Therefore, an alternative action by enhancing the role of the Head of Science Panels (HoSPs) as a key change agent in catalyzing the improvement of student performance should be considered. Highlights of previous studies have shown that subject leadership is able to enhance teacher teaching quality in order to increase student learning. To lead the Science department and guide Science teachers more effectively, HoSPs need to strengthen their leadership skills. However, the issue of weaknesses in the leadership competencies of HoSPs in Malaysia has caused them to lack confidence and ability in leading the Science Department. The main objective of this study is to explore the factors that contribute to the problems faced by HoSPs at Sarawak in their leadership roles. This study used a qualitative design framework and using a semi-structured interview method for data collection. There were six informants involved in the interview consisting of lecturers, Senior Administrative Assistant Teacher and HoSPs. The findings of the study had been identified four main factors that contribute to problems in the leadership competencies of HoSPs in Sarawak, namely leadership practices, leadership structure, academic subjects and school change. The results are significant to the MOE in strengthening the leadership competencies of HoSPs in a more focus for improving the achievement of scientific literacy of students in Malaysia. This study can help improve the Hosps' leadership competencies in Malaysia.

Keywords: issues, problems, Malaysia education blueprint, leadership competencies, head of science panels

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Authors: Hala Zaghloul, Taymoor Nazmy

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One of the great challenges of the 21st century is to build a robot that can perceive and act within its environment and communicate with people, while also exhibiting the cognitive capabilities that lead to performance like that of people. The Pulse Coupled Neural Network, PCNN, is a relative new ANN model that derived from a neural mammal model with a great potential in the area of image processing as well as target recognition, feature extraction, speech recognition, combinatorial optimization, compressed encoding. PCNN has unique feature among other types of neural network, which make it a candid to be an important approach for perceiving in cognitive systems. This work show and emphasis on the potentials of PCNN to perform different tasks related to image processing. The main drawback or the obstacle that prevent the direct implementation of such technique, is the need to find away to control the PCNN parameters toward perform a specific task. This paper will evaluate the performance of PCNN standard model for processing images with different properties, and select the important parameters that give a significant result, also, the approaches towards find a way for the adaptation of the PCNN parameters to perform a specific task.

Keywords: cognitive system, image processing, segmentation, PCNN kernels

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Authors: Alaa El-Din Rezk

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In Egypt, management of crops still away from what is being used today by utilizing the advances of mechanical design capabilities, sensing and electronics technology. These technologies have been introduced in many places and recorm, for Straight Path, Curved Path, Sine Wave ded high accuracy in different field operations. So, an autonomous robotic platform based on machine vision has been developed and constructed to be implemented in Egyptian conditions as self-propelled mobile vehicle for carrying tools for inter/intra-row crop management based on different control modules. The experiments were carried out at plant protection research institute (PPRI) during 2014-2015 to optimize the accuracy of agricultural robotic platform control using machine vision in term of the autonomous navigation and performance of the robot’s guidance system. Results showed that the robotic platform' guidance system with machine vision was able to adequately distinguish the path and resisted image noise and did better than human operators for getting less lateral offset error. The average error of autonomous was 2.75, 19.33, 21.22, 34.18, and 16.69 mm. while the human operator was 32.70, 4.85, 7.85, 38.35 and 14.75 mm Path, Offset Discontinuity and Angle Discontinuity respectively.

Keywords: autonomous robotic, Hough transform, image processing, machine vision

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Authors: Jennifer Fane, Mike Gray, Melissa Sager

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Children with diagnosed or suspected learning disabilities frequently experience significant skill gaps in foundational learning areas such as reading, writing, and math. Remedial one-to-one instruction is a highly effective means of supporting children with learning differences in building these foundational skills and closing the learning gap between them and their same-age peers. However, due to the learning challenges children with learning disabilities face, and ensuing challenges with self-confidence, many children with learning differences struggle with motivation and self-regulation within remedial one-to-one learning environments - despite the benefits of these sessions. Socially Assistive Robots (SARs) are an innovative educational technology tool that has been trialled in a range of educational settings to support diverse learning needs. Yet, little is known about the impact of SARs on the learning of children with learning differences in a one-to-one remedial instructional setting. This study sought to explore the impact of SARs on the engagement of children (n=9) with learning differences attending one-to-one remedial instruction sessions at a non-profit remedial education provider. The study used a mixed-methods design to explore learner engagement during learning tasks both with and without the use of a SAR to investigate how the use of SARs impacts student learning. The study took place over five weeks, with each session within the study followed the same procedure with the SAR acting as a teaching assistant when in use. Data from the study included analysis of time-sample video segments of the instructional sessions, instructor recorded information about the student’s progress towards their session learning goal and student self-reported mood and energy levels before and after the session. Analysis of the findings indicates that the use of SARs resulted in fewer instances of off-task behaviour and less need for instructor re-direction during learning tasks, allowing students to work in more sustained ways towards their learning goals. This initial research indicates that the use of SARs does have a material and measurable impact on learner engagement for children with learning differences and that further exploration of the impact of SARs during one-to-one remedial instruction is warranted.

Keywords: engagement, learning differences, learning disabilities, instruction, social robotics.

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Authors: Zahid Hussain

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Provincial Disaster Management Authority (PDMA) Punjab was established under NDM Act 2010 and now working under Senior Member Board of Revenue, deals with the whole spectrum of disasters including preparedness, mitigation, early warning, response, relief, rescue, recovery and rehabilitation. The District Disaster Management Authorities (DDMA) are acting as implementing arms of PDMA in the districts to respond any disaster. DDMAs' role is very important in disaster mitigation, response and recovery as they are the first responder and closest tier to the community. Keeping in view the significant role of DDMAs, technical and human resource capacity are need to be checked. For calculating the technical efficiencies of District Disaster Management Authority (DDMA) in Punjab, three inputs like number of labour, the number of transportation and number of equipment, two outputs like relief assistance and the number of rescue and 25 districts as decision making unit have been selected. For this purpose, 8 years secondary data from 2005 to 2012 has been used. Data Envelopment Analysis technique has been applied. DEA estimates the relative efficiency of peer entities or entities performing the similar tasks. The findings show that all decision making unit (DMU) (districts) are inefficient on techonological and scale efficiency scale while technically efficient on pure and total factor productivity efficiency scale. All DMU are found technically inefficient only in the year 2006. Labour and equipment were not efficiently used in the year 2005, 2007, 2008, 2009 and 2012. Furthermore, only three years 2006, 2010 and 2011 show that districts could not efficiently use transportation in a disaster situation. This study suggests that all districts should curtail labour, transportation and equipment to be efficient. Similarly, overall all districts are not required to achieve number of rescue and relief assistant, these should be reduced.

Keywords: DEA, DMU, PDMA, DDMA

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Anita Chhatwal

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Purpose: The purpose of this paper is to evaluate and investigate the scope of usage of Academic Social Networking Websites (ASNs) by the Science faculty members across universities of North India, viz. Panjab University, Punjabi University and University of Delhi, Delhi. Design/Methodology/Approach: The present study is based upon the primary data collected from 81 science faculty participants from three universities of North India. Questionnaire method was used as an instrument for survey. The study is descriptive and research-based to investigate the popular ASNs amongst the participants from three sample universities and the purpose for which they use them along with the problems they encounter while using ASNs. Findings: The findings of the study revealed that majority of the participants were using ASNs for their academic needs. It was observed that majority of the participants (78%) used ASNs to access scientific papers, while 73.8% of the participants used them to share their research publications. ResearchGate (60.5%) and Google Scholar (59.7%) were the top two most preferred and widely used ASNs by the participants. The critical analysis of the data shows that laptops (86.3%) emerged as major tools for accessing ASNs. Shortage of computers was found to be the chief obstacle in accessing ASNs by the participants. Results of the study demonstrate that 56.3% of participants suggested conduct of seminars and training as the most effective method to increase the awareness of ASNs. Research Limitations/Implications: The study in hand absorbed the 81 faculty (Assistant Professors) members from 15 Science teaching departments across three sample universities of North India. The findings of this study will help the Government of India to regulate and simultaneously make effort to develop and enhance ASNs usage among faculty, researchers, and students. The present study will add to the existing library and information science literature and will be advantageous for all the information professionals as well. Originality/Value: This study is original survey based on primary data investigate the usage of ASNs by the academia. This study will be useful for research scholars, academicians and students all over the world.

Keywords: academic social networks, awareness and usage, North India, scholarly communication, web 2.0

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Rossukhon Makaramani, Supanan Sittilerd, Wipada Prasarnsaph

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The study aimed to 1) examine management status of a Program in Education at the Faculty of Education, Suan Sunandha Rajabhat University (SSRU); 2) determine main components, indicators and criteria for constructing quality assessment framework; 3) assess quality of a SSRU Program in Education; and 4) provide recommendations to promote academic excellence. The program to be assessed was Bachelor of Education Program in Education (5 years), Revised Version 2009. Population and samples were stakeholders involving implementation of this program during an academic year 2012. Results were: 1) Management status of the Program in Education showed that the Faculty of Education depicted good level (4.20) in the third cycle of external quality assessment by the Office for National Education Standards and Quality Assessment (ONESQA). There were 1,192 students enrolling in the program, divided into 5 major fields of study. There were 50 faculty members, 37 holding master’s degrees and 13 holding doctorate degrees. Their academic position consisted of 35 lecturers, 10 assistant professors, and 5 associate professors. For program management, there was a committee of 5 members for the program and also a committee of 4 or 5 members for each major field of study. Among the faculty members, 41 persons taught in this program. The ratio between faculty and student was 1:26. The result of 2013 internal quality assessment indicated that system and mechanism of the program development and management was at fair level. However, the overall result yielded good level either by criteria of the Office of Higher Education Commission (4.29) or the NESQA (4.37); 2) Framework for assessing the quality of the program consisted of 4 dimensions and 15 indicators; 3) Assessment of the program yielded Good level of quality (4.04); 4) Recommendations to promote academic excellence included management and development of the program focusing on teacher reform toward highly recognized profession; cultivation of values, moral, ethics, and spirits of being a teacher; construction of specialized programs; development of faculty potentials; enhancement of the demonstration school’s readiness level; and provision of dormitories for learning.

Keywords: quality assessment, education program, Suan Sunandha Rajabhat University, academic excellence

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Authors: Naser Alajmi, Ali Alobaidly, Mubarak Alhajri, Salem Salamah, Muhammad Alsubaie

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Iterative Learning Control (ILC) known to be a controlling tool to overcome periodic disturbances for repetitive systems. This technique is required to let the error signal tends to zero as the number of operation increases. The learning process that lies within this context is strongly dependent on the initial input which if selected properly tends to let the learning process be more effective compared to the case where a system starts from blind. ILC uses previous recorded execution data to update the following execution/trial input such that a reference trajectory is followed to a high accuracy. Error convergence in ILC is generally highly dependent on the input applied to a plant for trial $1$, thus a good choice of initial starting input signal would make learning faster and as a consequence the error tends to zero faster as well. In the work presented within, an upper limit based on the Singular Values Principle (SV) is derived for the initial input signal applied at trial $1$ such that the system follow the reference in less number of trials without responding aggressively or exceeding the working envelope where a system is required to move within in a robot arm, for example. Simulation results presented illustrate the theory introduced within this paper.

Keywords: initial input, iterative learning control, maximum input, singular values

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Authors: Musa Alghamdi

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Although Saudi students’ motivation to learn English language as a foreign language in Saudi Arabia have been investigated by a number of studies; these have appeared almost completely as using the quantitative research paradigm. There is a significant lack of research that explores the Saudi students’ motivation using qualitative methods. It was essential, as an investigator, to be immersed in the community to understand the individuals under study via their actions and words, their thoughts, views and beliefs, and how those individuals credited to activities. Thus, the study aims to explore the Saudi students’ motivation to learn English language as a foreign language in Saudi Arabia employing qualitative methodology via applying ethnography. The study will be carried out in Saudi Arabia. Ethnography qualitative approach will be used in the current study by employing formal and informal interview instruments. Gardner’s motivation theory is used as frameworks for this study to aid the understanding of the research findings. The author, an English language lecturer, will undertake participant observations for 4 months. He will work as teaching-assistant (on an unpaid basis) with EFL lecturers in different discipline department at a Saudi university where students study English language as a minor course. The researcher will start with informal ethnographical interview with students during his existence with the informants in their natural context. Then the researcher will utilize the semi-structural interview. The informal interview will be with 14-16 students, then, he will carry out semi-structural interview with the same informants to go deep in their natural context to find out to what extent the Saudi university students are motivated to learn English as a foreign language. As well as, to find out the reasons that played roles in that. The findings of this study will add new knowledge about what factors motivate universities’ Saudi students to learn English language in Saudi Arabia. Very few chances have given to students to express themselves and to speak about their feelings in a more comfortable way in order to gain a clear image of those factors. The working author as an EFL teacher and lecturer will provide him secure access into EFL teaching and learning setting. It will help him attain richer insights into the nature EFL context in universities what will provide him with richer insights into the reasons behind the weakness of EFL level among Saudi students.

Keywords: motivation, ethnography, Saudi, language

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Authors: Atef A. Ata, Sohair F. Rezeka, Ahmed El-Shenawy, Mohammed Diab

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Image processing in today’s world grabs massive attentions as it leads to possibilities of broaden application in many fields of high technology. The real challenge is how to improve existing sorting system applications which consists of two integrated stations of processing and handling with a new image processing feature. Existing color sorting techniques use a set of inductive, capacitive, and optical sensors to differentiate object color. This research presents a mechatronics color sorting system solution with the application of image processing. A 5-DOF robot arm is designed and developed with pick and place operation to be main part of the color sorting system. Image processing procedure senses the circular objects in an image captured in real time by a webcam attached at the end-effector then extracts color and position information out of it. This information is passed as a sequence of sorting commands to the manipulator that has pick-and-place mechanism. Performance analysis proves that this color based object sorting system works very accurate under ideal condition in term of adequate illumination, circular objects shape and color. The circular objects tested for sorting are red, green and blue. For non-ideal condition, such as unspecified color the accuracy reduces to 80%.

Keywords: robotics manipulator, 5-DOF manipulator, image processing, color sorting, pick-and-place

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Authors: Andreas Kornmaaler Hansen, Carlos Gomez Cubero, Elizabeth Jochum

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The use of the arts in therapy and rehabilitation is well established, and there is growing recognition of the value of the arts for improving health and well-being across diverse populations. Combining arts with socially assistive robots is a relatively under-explored research area. This paper presents the results of a feasibility study conducted within an existing arts and health program to scope the possibility of combining visual arts with socially assistive robots to promote mental health and well-being. Using a participatory research design with participant-led perspectives, we present the results of our feasibility study with a collaborative drawing robot among an adult population with mild to severe mental illness. We identify key methodological challenges and advantages of working with participatory and human-centered approaches. Based on the results of three pilot workshops with participants and lay health workers, we outline suggestions for authentic engagement with real stakeholders toward the development of socially assistive robots in community health contexts. Working closely with a patient population at all levels of the research process is key for developing tools and interventions that center patient experience and priorities while minimizing the risks of alienating patients and communities.

Keywords: arts and health, visual art, health promotion, mental health, collaborative robots, creativity, socially assistive robots

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Authors: Thinh Huu Nguyen, Shahab Sharfaei, Jindřich Soukup

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In the pursuit of reducing production costs, offshoring has been a major trend throughout global value chains for many decades. However, with the rise of advanced technologies, new opportunities to automate their production are changing the motivation of multinational firms to go offshore. Instead, many firms are working to relocate their offshored activities from developing economies back to their home countries. This phenomenon, known as reshoring, has recently garnered much attention as it becomes clear that automation in advanced countries might have major implications not only on their own economies but also through international trade on the economy of low-income countries, including their labor market outcomes and their comparative advantages. Thus, while using robots to substitute human labor may lower the relative costs of producing at home, it has the potential to decrease employment and demand for exports from developing economies through reshoring. In this paper, we investigate the recent literature to provide a further understanding of the relationships between robotization and the reshoring of production. Moreover, we analyze the impact of robot adoption on international trade in both developed and emerging markets. Finally, we identify the research gaps and provide avenues for future research in international economics. This study is a part of the project funded by the Internal Grant Agency (IGA) of the Faculty of Business Administration, Prague University of Economics and Business.

Keywords: automation, robotization, reshoring, international trade

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Bahareh Yousefian, Laurel Smith Stvan

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Linguistic structures have two facades: form and meaning. These structures could have either literal meaning or figurative meaning (although it could also depend on the context in which that structure appears). The literal meaning is understandable more easily, but for the figurative meaning, a word or concept is understood from a different word or concept. In linguistic structures with a figurative meaning, it’s more difficult to relate their forms to the meanings than structures with literal meaning. In these cases, the relationship between form and figurative meaning could be studied from different perspectives. Various linguists have been curious about what happens in someone’s mind to understand figurative meaning through the forms; they have used different perspectives and theories to explain this process. It has been studied through cognitive linguistics as well, in which mind and mental activities are really important. In this viewpoint, meaning (in other words, conceptualization) is considered a mental process. In this descriptive-analytic study, 20 Persian compound nouns with figurative meanings have been collected from the Persian-language Moeen Encyclopedic Dictionary and other sources. Examples include [“Sofreh Xaneh”] (traditional restaurant) and [“Dast Yar”] (Assistant). These were studied in a cognitive semantics framework using “Conceptual Blending Theory” which hasn’t been tested on Persian compound nouns before. It was noted that “Conceptual Blending Theory” could lead to the process of understanding the figurative meanings of Persian compound nouns. Many cognitive linguists believe that “Conceptual Blending” is not only a linguistic theory but it’s also a basic human cognitive ability that plays important roles in thought, imagination, and even everyday life as well (though unconsciously). The ability to use mental spaces and conceptual blending (which is exclusive to humankind) is such a basic but unconscious ability that we are unaware of its existence and importance. What differentiates Conceptual Blending Theory from other ways of understanding figurative meaning, are arising new semantic aspects (emergent structure) that lead to a more comprehensive and precise meaning. In this study, it was found that Conceptual Blending Theory could explain reaching the figurative meanings of Persian compound nouns from their forms, such as [talkative for compound word of “Bolbol + Zabani” (nightingale + tongue)] and [wage for compound word of “Dast + Ranj” (hand + suffering)].

Keywords: cognitive linguistics, conceptual blending, figurative meaning, Persian compound nouns

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Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

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Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

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Authors: Mallikarjunachari G., Venkata Ravi M.

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The objective of this research work is to evaluate the mechanical properties such as elastic modulus and critical rupture load of tomato fruits. Determination of mechanical properties of tomato fruits is essential in various material handling applications, especially as related to robot harvesting, packaging, and transportation. However, extracting meaningful mechanical properties of tomato fruits are extremely challenging due to its layered structure, i.e., the combination of exocarp, mesocarp, and locular gel tissues. Apart from this layered structure, other physical parameters such as diameter, sphericity, locule number, and, the surface to volume ratio also influence the mechanical properties. In this research work, tomato fruits are cultivated in two different ways, namely organic and inorganic farming. Static compression tests are performed to extract the mechanical properties of tomato fruits. Finite element simulations are done to complement the experimental results. It is observed that the effective modulus decreases as the compression depth increase from 0.5 mm to 10 mm and also a critical load of fracture decreases as the locule number increases from 3 to 5. Significant differences in mechanical properties are observed between organically and inorganically cultivated tomato fruits. The current study significantly helps in the design of material handling systems to avoid damage of tomato fruits.

Keywords: elastic modulus, critical load of fracture, locule number, finite element analysis

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Poonam Mishra, Shiv Kumar Sharma, Sanjeev Swami

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Purpose: The Purpose of this paper is to investigate the relationship of percieved organizational politics with three levels of antecedents (i.e., organizational level, work environment level and individual level)and its consequents simultaneously. The study addresses antecedents and consequents of percieved political behavior in the higher education sector of India with specific reference to a central university. Design/ Methodology/ Approach: A conceptual framework and hypotheses were first developed on the basis of review of previous studies on organizational politics. A questionnaire was then developed carrying 66 items related to 8-constructs and demographic characteristics of respondents. Jundegemental sampling was used to select respondents. Primary data is collected through structured questionnaire from 45 faculty members of a central university. The sample constitutes Professors, Associate Professors and Assistant Professors from various departments of the University. To test hypotheses data was analyzed statistically using partial least square-structural equations modeling (PLS-SEM). Findings: Results indicated a strong support for OP’s relationship with three of the four proposed antecedents that are, workforce diversity, relationship conflict and need for power with relationship conflict having the strongest impact. No significant relationship was found between role conflict and perception of organizational politics. The three consequences that is, intention to turnover, job anxiety, and organizational commitment are significantly impacted by perception of organizational politics. Practical Implications– This study will be helpful in motivating future research for improving the quality of higher education in India by reducing the level of antecedents that adds to the level of perception of organizational politics, ultimately resulting in unfavorable outcomes. Originality/value: Although a large number of studies on atecedents and consequents of percieved organizational politics have been reported, little attention has been paid to test all the separate but interdependent relationships simultaneously; in this paper organizational politics will be simultaneously treated as a dependent variable and same will be treated as independent variable in subsequent relationships.

Keywords: organizational politics, workforce diversity, relationship conflict, role conflict, need for power, intention to turnover, job anxiety, organizational commitment

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: adaptive algorithm, fuzzy systems, membership functions, observer

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Authors: Martin Leroux, Sylvain Brisebois

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Eating a meal is among the Activities of Daily Living, but it takes a lot of time and effort for people with physical or functional limitations. Dedicated technologies are cumbersome and not portable, while general-purpose assistive robots such as wheelchair-based manipulators are too hard to control for elaborate continuous motion like eating. Eating with such devices has not previously been automated, since there existed no description of a feeding motion for uncontrolled environments. In this paper, we introduce a feeding mode for assistive manipulators, including a mathematical description of trajectories for motions that are difficult to perform manually such as gathering and scooping food at a defined/desired pace. We implement these trajectories in a sequence of movements for a semi-automated feeding mode which can be controlled with a very simple 3-button interface, allowing the user to have control over the feeding pace. Finally, we demonstrate the feeding mode with a JACO robotic arm and compare the eating speed, measured in bites per minute of three eating methods: a healthy person eating unaided, a person with upper limb limitations or disability using JACO with manual control, and a person with limitations using JACO with the feeding mode. We found that the feeding mode allows eating about 5 bites per minute, which should be sufficient to eat a meal under 30min.

Keywords: assistive robotics, automated feeding, elderly care, trajectory design, human-robot interaction

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Authors: Zhou Congling

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The integration of private tutoring has emerged as an indispensable facet in the acquisition of language proficiency beyond formal educational settings. Notably, there has been a discernible surge in the demand for private English tutoring, specifically geared towards the preparation for internationally recognized gatekeeping examinations, such as IELTS, TOEFL, GMAT, and GRE. This trajectory has engendered an escalating need for English Language Teaching Assistants (ELTAs) operating within the realm of Private Tutoring Schools (PTSs). The objective of this study is to unravel the intricate process by which these ELTAs formulate their professional identities in the nascent stages of their careers as English educators, as well as to delineate their perceptions regarding their professional trajectories. The construct of language teacher identity is inherently multifaceted, shaped by an amalgamation of individual, societal, and cultural determinants, exerting a profound influence on how language educators navigate their professional responsibilities. This investigation seeks to scrutinize the experiential and influential factors that mold the identities of ELTAs in PTSs, particularly post the culmination of their language-oriented academic programs. Employing a qualitative narrative inquiry approach, this study aims to delve into the nuanced understanding of how ELTAs conceptualize their professional identities and envision their future roles. The research methodology involves purposeful sampling and the conduct of in-depth, semi-structured interviews with ten participants. Data analysis will be conducted utilizing Barkhuizen’s Short Story Analysis, a method designed to explore a three-dimensional narrative space, elucidating the intricate interplay of personal experiences and societal contexts in shaping the identities of ELTAs. The anticipated outcomes of this study are poised to contribute substantively to a holistic comprehension of ELTA identity formation, holding practical implications for diverse stakeholders within the private tutoring sector. This research endeavors to furnish insights into strategies for the retention of ELTAs and the enhancement of overall service quality within PTSs.

Keywords: China, English language teacher, narrative inquiry, private tutoring school, teacher identity

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Authors: Indu Chandran, Shubham Sharma, Rohan Mehta, Vipin Kizheppatt

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Unmanned aerial vehicles are increasingly being explored as the most promising solution to disaster monitoring, assessment, and recovery. Current relief operations heavily rely on intelligent robot swarms to capture the damage caused, provide timely rescue, and create road maps for the victims. To perform these time-critical missions, efficient path planning that ensures quick coverage of the area is vital. This study aims to develop a technically balanced approach to provide maximum coverage of the affected area in a minimum time using the optimal number of UAVs. A coverage trajectory is designed through area decomposition and task assignment. To perform efficient and autonomous coverage mission, solution to a TSP-based optimization problem using meta-heuristic approaches is designed to allocate waypoints to the UAVs of different flight capacities. The study exploits multi-agent simulations like PX4-SITL and QGroundcontrol through the ROS framework and visualizes the dynamics of UAV deployment to different search paths in a 3D Gazebo environment. Through detailed theoretical analysis and simulation tests, we illustrate the optimality and efficiency of the proposed methodologies.

Keywords: area coverage, coverage path planning, heuristic algorithm, mission monitoring, optimization, task assignment, unmanned aerial vehicles

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

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The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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