Search results for: Automatic Speech Recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1474

Search results for: Automatic Speech Recognition

64 Public Service Ethics in Public Administration: An Empirical Investigation

Authors: Kalsoom Sumra

Abstract:

The increasing concern of public sector reforms brings new challenges to public service ethics in developing countries not only at central level but also at local level. This paper aims to identify perceptions on public service ethics of public officials and examines more generally the understanding of public servants in Pakistan towards public service ethics in local public organizations. The study uses an independently administered structured questionnaire to collect data to know the extent of the recognition of public service ethics in local organizations. A total of 150 completed questionnaires are analyzed received from public servants working at the local level in Pakistan. The analysis explores how traditional, social patterns and cultural ethics can provide us with a rounded picture of the main antecedents, moderators of public service ethics in Pakistan. Moreover, the findings of this study contribute in association of public service ethics which are crucial in ongoing political and administrative culture of Pakistan, the most crucial core for public organizational ethical climate. This study also has numerous implications for local public administration and it highlights the importance of expanding research agenda on public service ethics in developing settings with challenging institutional contexts with imperfect training and operating environments. This study may well be particularly important for practice of public service ethics in developing countries in public administration. To the best of author’s knowledge, this study is the first of its kind to provide an initial step in practical implications to emphasize relevant public service ethics in public administration in developing transparent and accountable organization.

Keywords: Public service ethics, accountability and transparency, public service reforms, public administration, organizational ethical climate.

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63 Destination Port Detection for Vessels: An Analytic Tool for Optimizing Port Authorities Resources

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages Automatic Identification System (AIS) messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring AIS messages. Our RRo method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measures to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Frechet Distance (DFD), Dynamic Time ´ Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an f-measure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: Spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization.

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62 Context Detection in Spreadsheets Based on Automatically Inferred Table Schema

Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

Abstract:

Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: Natural language processing, end user development; natural language interfaces, human computer interaction, data recognition, dialog systems, spreadsheet.

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61 A New High Speed Neural Model for Fast Character Recognition Using Cross Correlation and Matrix Decomposition

Authors: Hazem M. El-Bakry

Abstract:

Neural processors have shown good results for detecting a certain character in a given input matrix. In this paper, a new idead to speed up the operation of neural processors for character detection is presented. Such processors are designed based on cross correlation in the frequency domain between the input matrix and the weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single faster neural processor. Furthermore, faster character detection is obtained by using parallel processing techniques to test the resulting sub-images at the same time using the same number of faster neural networks. In contrast to using only faster neural processors, the speed up ratio is increased with the size of the input image when using faster neural processors and image decomposition. Moreover, the problem of local subimage normalization in the frequency domain is solved. The effect of image normalization on the speed up ratio of character detection is discussed. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.

Keywords: Fast Character Detection, Neural Processors, Cross Correlation, Image Normalization, Parallel Processing.

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60 Development of a Robot Assisted Centrifugal Casting Machine for Manufacturing Multi-Layer Journal Bearing and High-Tech Machine Components

Authors: Mohammad Syed Ali Molla, Mohammed Azim, Mohammad Esharuzzaman

Abstract:

Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision.

Keywords: Casting, cylinder liners, journal bearing, robot.

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59 A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotiv EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: Brain Computer Interface (BCI), Electroencephalogram (EEG), EEGLab, BCILab, Emotiv, Emotions, Interval features, Spectral features, Artificial Neural Network, Control applications.

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58 Authentication Protocol for Wireless Sensor Networks

Authors: Sunil Gupta, Harsh Kumar Verma, AL Sangal

Abstract:

Wireless sensor networks can be used to measure and monitor many challenging problems and typically involve in monitoring, tracking and controlling areas such as battlefield monitoring, object tracking, habitat monitoring and home sentry systems. However, wireless sensor networks pose unique security challenges including forgery of sensor data, eavesdropping, denial of service attacks, and the physical compromise of sensor nodes. Node in a sensor networks may be vanished due to power exhaustion or malicious attacks. To expand the life span of the sensor network, a new node deployment is needed. In military scenarios, intruder may directly organize malicious nodes or manipulate existing nodes to set up malicious new nodes through many kinds of attacks. To avoid malicious nodes from joining the sensor network, a security is required in the design of sensor network protocols. In this paper, we proposed a security framework to provide a complete security solution against the known attacks in wireless sensor networks. Our framework accomplishes node authentication for new nodes with recognition of a malicious node. When deployed as a framework, a high degree of security is reachable compared with the conventional sensor network security solutions. A proposed framework can protect against most of the notorious attacks in sensor networks, and attain better computation and communication performance. This is different from conventional authentication methods based on the node identity. It includes identity of nodes and the node security time stamp into the authentication procedure. Hence security protocols not only see the identity of each node but also distinguish between new nodes and old nodes.

Keywords: Authentication, Key management, Wireless Sensornetwork, Elliptic curve cryptography (ECC).

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57 Food for Thought: Preparing the Brain to Eat New Foods through “Messy” Play

Authors: L. Bernabeo, T. Loftus

Abstract:

Many children often experience phases of picky eating, food aversions and/or avoidance. For families with children who have special needs, these experiences are often exacerbated, which can lead to feelings that negatively impact a caregiver’s relationship with their child. Within the scope of speech language pathology practice, knowledge of both emotional and feeding development is key. This paper will explore the significance of “messy play” within typical feeding development, and the challenges that may arise if a child does not have the opportunity to engage in this type of exploratory play. This paper will consider several contributing factors that can result in a “picky eater.” Further, research has shown that individuals with special needs, including autism, possess a neurological makeup that differs from that of a typical individual. Because autism is a disorder of relating and communicating due to differences in the limbic system, an individual with special needs may respond to a typical feeding experience as if it is a traumatic event. As a result, broadening one’s dietary repertoire may seem to be an insurmountable challenge. This paper suggests that introducing new foods through exploratory play can help broaden and strengthen diets, as well as improve the feeding experience, of individuals with autism. The DIRFloortimeⓇ methodology stresses the importance of following a child's lead. Within this developmental model, there is a special focus on a person’s individual differences, including the unique way they process the world around them, as well as the significance of therapy occurring within the context of a strong and motivating relationship. Using this child-centered approach, we can support our children in expanding their diets, while simultaneously building upon their cognitive and creative development through playful and respectful interactions that include exposure to foods that differ in color, texture, and smell. Further, this paper explores the importance of exploration, self-feeding and messy play on brain development, both in the context of typically developing individuals and those with disordered development.

Keywords: Autism, development, exploration, feeding, play.

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56 Automated Textile Defect Recognition System Using Computer Vision and Artificial Neural Networks

Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

Abstract:

Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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55 Generative Adversarial Network Based Fingerprint Anti-Spoofing Limitations

Authors: Yehjune Heo

Abstract:

Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: Anti-spoofing, CNN, fingerprint recognition, GAN.

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54 Noninvasive Disease Diagnosis through Breath Analysis Using DNA-Functionalized SWNT Sensor Array

Authors: Wenjun Zhang, Yunqing Du, Ming L. Wang

Abstract:

Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancements in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless, and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-functionalized single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Seven DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, and diabetes. Our test results indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, and repeatability; and different molecules can be distinguished through pattern recognition enabled by this sensor array. Furthermore, the experimental sensing results are consistent with the Molecular Dynamics simulated ssDNAmolecular target interaction rankings. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or biomolecular detection for the noninvasive diagnostics of diseases and personal health monitoring.

Keywords: Breath analysis, DNA-SWNT sensor array, diagnosis, noninvasive.

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53 Image-Based UAV Vertical Distance and Velocity Estimation Algorithm during the Vertical Landing Phase Using Low-Resolution Images

Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

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The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement. On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: Automatic landing, multirotor, nonlinear control, parameters estimation, optical flow.

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52 Automated Video Surveillance System for Detection of Suspicious Activities during Academic Offline Examination

Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

Abstract:

This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: Impersonation, image registration, incrimination, object detection, threshold evaluation.

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51 Mobile Augmented Reality for Collaboration in Operation

Authors: Chong-Yang Qiao

Abstract:

Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: Mobile augmented reality, remote collaboration, user experience, cognitive model.

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50 Hierarchies Based On the Number of Cooperating Systems of Finite Automata on Four-Dimensional Input Tapes

Authors: Makoto Sakamoto, Yasuo Uchida, Makoto Nagatomo, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

Abstract:

In theoretical computer science, the Turing machine has played a number of important roles in understanding and exploiting basic concepts and mechanisms in computing and information processing [20]. It is a simple mathematical model of computers [9]. After that, M.Blum and C.Hewitt first proposed two-dimensional automata as a computational model of two-dimensional pattern processing, and investigated their pattern recognition abilities in 1967 [7]. Since then, a lot of researchers in this field have been investigating many properties about automata on a two- or three-dimensional tape. On the other hand, the question of whether processing fourdimensional digital patterns is much more difficult than two- or threedimensional ones is of great interest from the theoretical and practical standpoints. Thus, the study of four-dimensional automata as a computasional model of four-dimensional pattern processing has been meaningful [8]-[19],[21]. This paper introduces a cooperating system of four-dimensional finite automata as one model of four-dimensional automata. A cooperating system of four-dimensional finite automata consists of a finite number of four-dimensional finite automata and a four-dimensional input tape where these finite automata work independently (in parallel). Those finite automata whose input heads scan the same cell of the input tape can communicate with each other, that is, every finite automaton is allowed to know the internal states of other finite automata on the same cell it is scanning at the moment. In this paper, we mainly investigate some accepting powers of a cooperating system of eight- or seven-way four-dimensional finite automata. The seven-way four-dimensional finite automaton is an eight-way four-dimensional finite automaton whose input head can move east, west, south, north, up, down, or in the fu-ture, but not in the past on a four-dimensional input tape.

Keywords: computational complexity, cooperating system, finite automaton, four-dimension, hierarchy, multihead.

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49 Effect of Organizational Competitive Climate on Organizational Prosocial Behavior: Workplace Envy as a Mediator

Authors: Armaghan Eslami, Nasrin Arshadi

Abstract:

Scarce resources are the inseparable part of organization life. This fact that only small number of the employees can have these resources such as promotion, raise, and recognition can cause competition among employees, which create competitive climate. As well as any other competition, small number wins the reward, and a great number loses, one of the possible emotional reactions to this loss is negative emotions like malicious envy. In this case, the envious person may try to harm the envied person by reducing the prosocial behavior. Prosocial behavior is a behavior that aimed to benefit others. The main propose of this action is to maintain and increase well-being and well-fare of others. Therefore, one of the easiest ways for harming envied one is to suppress prosocial behavior. Prosocial behavior has positive and important implication for organizational efficiency. Our results supported our model and suggested that competitive climate has a significant effect on increasing workplace envy and on the other hand envy has significant negative impact on prosocial behavior. Our result also indicated that envy is the mediator in the relation between competitive climate and prosocial behavior. Organizational competitive climate can cause employees respond envy with negative emotion and hostile and damaging behavior toward envied person. Competition can lead employees to look out for proof of their self-worthiness; and, furthermore, they measure their self-worth, value and respect by the superiority that they gain in competitions. As a result, loss in competitions can harm employee’s self-definition and they try to protect themselves by devaluating envied other and being ‘less friendly’ to them. Some employees may find it inappropriate to engage in the harming behavior, but they may believe there is nothing against withholding the prosocial behavior.

Keywords: Competitive climate, mediator, prosocial behavior, workplace envy.

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48 Development of a Tilt-Rotor Aircraft Model Using System Identification Technique

Authors: Antonio Vitale, Nicola Genito, Giovanni Cuciniello, Ferdinando Montemari

Abstract:

The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: Flapping Dynamics, Flight Dynamics, System Identification, Tilt-Rotor Modeling and Simulation.

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47 The Direct and Indirect Effects of the Achievement Motivation on Nurturing Intellectual Giftedness

Authors: Al-Shabatat, M. Ahmad, Abbas, M., Ismail, H. Nizam

Abstract:

Achievement motivation is believed to promote giftedness attracting people to invest in many programs to adopt gifted students providing them with challenging activities. Intellectual giftedness is founded on the fluid intelligence and extends to more specific abilities through the growth and inputs from the achievement motivation. Acknowledging the roles played by the motivation in the development of giftedness leads to an effective nurturing of gifted individuals. However, no study has investigated the direct and indirect effects of the achievement motivation and fluid intelligence on intellectual giftedness. Thus, this study investigated the contribution of motivation factors to giftedness development by conducting tests of fluid intelligence using Cattell Culture Fair Test (CCFT) and analytical abilities using culture reduced test items covering problem solving, pattern recognition, audio-logic, audio-matrices, and artificial language, and self report questionnaire for the motivational factors. A number of 180 highscoring students were selected using CCFT from a leading university in Malaysia. Structural equation modeling was employed using Amos V.16 to determine the direct and indirect effects of achievement motivation factors (self confidence, success, perseverance, competition, autonomy, responsibility, ambition, and locus of control) on the intellectual giftedness. The findings showed that the hypothesized model fitted the data, supporting the model postulates and showed significant and strong direct and indirect effects of the motivation and fluid intelligence on the intellectual giftedness.

Keywords: Achievement motivation, Intellectual Giftedness, Fluid Intelligence, Analytical Giftedness, CCFT, Structural EquationModeling.

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46 Time-Cost-Quality Trade-off Software by using Simplified Genetic Algorithm for Typical Repetitive Construction Projects

Authors: Refaat H. Abd El Razek, Ahmed M. Diab, Sherif M. Hafez, Remon F. Aziz

Abstract:

Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.

Keywords: Project management, typical (repetitive) large scale projects, line of balance, multi-objective optimization, genetic algorithms, time-cost-quality trade-offs.

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45 Education and Assessment of Civil Employees in e-Government: The Case of a Moodle Based Platform

Authors: Stamatios A. Theocharis, George A. Tsihrintzis

Abstract:

One of the most important factors for the success of e-government is training and preparing the workforce of the public sector. As changes and innovation in the public sector progress at a very slow pace and more slowly than in the private sector, issues related to human resources require special care. This is because the workforce will eventually seize the opportunities of the technological solutions used in e-Government. Thus, the central administration should provide employees with continuous and focused training not only on new technologies but also on a wide range of subjects and also improve interdepartmental interaction.

To achieve all this, new methods and training tools need to be implemented in addition to assessment of the employees. In this spirit, we propose the development of an educational platform with user personalization features. We propose the development of this platform using Moodle as the basic tool. Incorporating a personalization mechanism is very important since different employees have different backgrounds, education levels, computer skills, or different capability to develop further. Key features of the proposed platform include, besides typical e-learning tools, communities organized in order to exchange experiences and knowledge, groups of users based on certain criteria, automatic evaluation of users and potential self-education and self-assessment. In its fully developed form, this platform can be part of a more comprehensive knowledge management system for the public sector.

Keywords: e-Government, civil employees education, education technologies.

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44 Early Depression Detection for Young Adults with a Psychiatric and AI Interdisciplinary Multimodal Framework

Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

Abstract:

During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: Artificial intelligence, depression detection, facial emotion recognition, natural language processing, mental disorder.

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43 Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores, Valentin Soloiu

Abstract:

This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

Keywords: Biosensors, electromyography, Artificial Neural Network, Arduino, drone flight control, machine learning.

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42 Disparities versus Similarities: WHO GPPQCL and ISO/IEC 17025:2017 International Standards for Quality Management Systems in Pharmaceutical Laboratories

Authors: M. A. Okezue, K. L. Clase, S. R. Byrn, P. Shivanand

Abstract:

Medicines regulatory authorities expect pharmaceutical companies and contract research organizations to seek ways to certify that their laboratory control measurements are reliable. Establishing and maintaining laboratory quality standards are essential in ensuring the accuracy of test results. ‘ISO/IEC 17025:2017’ and ‘WHO Good Practices for Pharmaceutical Quality Control Laboratories (GPPQCL)’ are two quality standards commonly employed in developing laboratory quality systems. A review was conducted on the two standards to elaborate on areas on convergence and divergence. The goal was to understand how differences in each standard's requirements may influence laboratories' choices as to which document is easier to adopt for quality systems. A qualitative review method compared similar items in the two standards while mapping out areas where there were specific differences in the requirements of the two documents. The review also provided a detailed description of the clauses and parts covering management and technical requirements in these laboratory standards. The review showed that both documents share requirements for over ten critical areas covering objectives, infrastructure, management systems, and laboratory processes. There were, however, differences in standard expectations where GPPQCL emphasizes system procedures for planning and future budgets that will ensure continuity. Conversely, ISO 17025 was more focused on the risk management approach to establish laboratory quality systems. Elements in the two documents form common standard requirements to assure the validity of laboratory test results that promote mutual recognition. The ISO standard currently has more global patronage than GPPQCL.

Keywords: ISO/IEC 17025:2017, laboratory standards, quality control, WHO GPPQCL

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41 Evaluation of Market Limitations in the Case of Ecosystem Services

Authors: Giani Gradinaru

Abstract:

Biodiversity crisis is one of the many crises that started at the turn of the millennia. Concrete form of expression is still disputed, but there is a relatively high consensus regarding the high rate of degradation and the urgent need for action. The strategy of action outlines a strong economic component, together with the recognition of market mechanisms as the most effective policies to protect biodiversity. In this context, biodiversity and ecosystem services are natural assets that play a key role in economic strategies and technological development to promote development and prosperity. Developing and strengthening policies for transition to an economy based on efficient use of resources is the way forward. To emphasize the co-viability specific to the connection economyecosystem services, scientific approach aimed on one hand how to implement policies for nature conservation and on the other hand, the concepts underlying the economic expression of ecosystem services- value, in the context of current technology. Following the analysis of business opportunities associated with changes in ecosystem services was concluded that development of market mechanisms for nature conservation is a trend that is increasingly stronger individualized within recent years. Although there are still many controversial issues that have already given rise to an obvious bias, international organizations and national governments have initiated and implemented in cooperation or independently such mechanisms. Consequently, they created the conditions for convergence between private interests and social interests of nature conservation, so there are opportunities for ongoing business development which leads, among other things, the positive effects on biodiversity. Finally, points out that markets fail to quantify the value of most ecosystem services. Existing price signals reflect at best, only a proportion of the total amount corresponding provision of food, water or fuel.

Keywords: ecosystem services, economic evaluation, nature conservation

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40 Multi-Scale Gabor Feature Based Eye Localization

Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Dusik Oh, Jaemin Kim, Seongwon Cho

Abstract:

Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported so far still need to be improved about precision and computational time for successful applications. In this paper, we propose an eye location method based on multi-scale Gabor feature vectors, which is more robust with respect to initial points. The eye localization based on Gabor feature vectors first needs to constructs an Eye Model Bunch for each eye (left or right eye) which consists of n Gabor jets and average eye coordinates of each eyes obtained from n model face images, and then tries to localize eyes in an incoming face image by utilizing the fact that the true eye coordinates is most likely to be very close to the position where the Gabor jet will have the best Gabor jet similarity matching with a Gabor jet in the Eye Model Bunch. Similar ideas have been already proposed in such as EBGM (Elastic Bunch Graph Matching). However, the method used in EBGM is known to be not robust with respect to initial values and may need extensive search range for achieving the required performance, but extensive search ranges will cause much more computational burden. In this paper, we propose a multi-scale approach with a little increased computational burden where one first tries to localize eyes based on Gabor feature vectors in a coarse face image obtained from down sampling of the original face image, and then localize eyes based on Gabor feature vectors in the original resolution face image by using the eye coordinates localized in the coarse scaled image as initial points. Several experiments and comparisons with other eye localization methods reported in the other papers show the efficiency of our proposed method.

Keywords: Eye Localization, Gabor features, Multi-scale, Gabor wavelets.

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39 Development of a Feedback Control System for a Lab-Scale Biomass Combustion System Using Programmable Logic Controller

Authors: Samuel O. Alamu, Seong W. Lee, Blaise Kalmia, Marc J. Louise Caballes, Xuejun Qian

Abstract:

The application of combustion technologies for thermal conversion of biomass and solid wastes to energy has been a major solution to the effective handling of wastes over a long period of time. Lab-scale biomass combustion systems have been observed to be economically viable and socially acceptable, but major concerns are the environmental impacts of the process and deviation of temperature distribution within the combustion chamber. Both high and low combustion chamber temperature may affect the overall combustion efficiency and gaseous emissions. Therefore, there is an urgent need to develop a control system which measures the deviations of chamber temperature from set target values, sends these deviations (which generates disturbances in the system) in the form of feedback signal (as input), and control operating conditions for correcting the errors. In this research study, major components of the feedback control system were determined, assembled, and tested. In addition, control algorithms were developed to actuate operating conditions (e.g., air velocity, fuel feeding rate) using ladder logic functions embedded in the Programmable Logic Controller (PLC). The developed control algorithm having chamber temperature as a feedback signal is integrated into the lab-scale swirling fluidized bed combustor (SFBC) to investigate the temperature distribution at different heights of the combustion chamber based on various operating conditions. The air blower rates and the fuel feeding rates obtained from automatic control operations were correlated with manual inputs. There was no observable difference in the correlated results, thus indicating that the written PLC program functions were adequate in designing the experimental study of the lab-scale SFBC. The experimental results were analyzed to study the effect of air velocity operating at 222-273 ft/min and fuel feeding rate of 60-90 rpm on the chamber temperature. The developed temperature-based feedback control system was shown to be adequate in controlling the airflow and the fuel feeding rate for the overall biomass combustion process as it helps to minimize the steady-state error.

Keywords: Air flow, biomass combustion, feedback control system, fuel feeding, ladder logic, programmable logic controller, temperature.

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38 Suicide Conceptualization in Adolescents through Semantic Networks

Authors: K. P. Valdés García, E. I. Rodríguez Fonseca, L. G. Juárez Cantú

Abstract:

Suicide is a global, multidimensional and dynamic problem of mental health, which requires a constant study for its understanding and prevention. When research of this phenomenon is done, it is necessary to consider the different characteristics it may have because of the individual and sociocultural variables, the importance of this consideration is related to the generation of effective treatments and interventions. Adolescents are a vulnerable population due to the characteristics of the development stage. The investigation was carried out with the objective of identifying and describing the conceptualization of adolescents of suicide, and in this process, we find possible differences between men and women. The study was carried out in Saltillo, Coahuila, Mexico. The sample was composed of 418 volunteer students aged between 11 and 18 years. The ethical aspects of the research were reviewed and considered in all the processes of the investigation with the participants, their parents and the schools to which they belonged, psychological attention was offered to the participants and preventive workshops were carried in the educational institutions. Natural semantic networks were the instrument used, since this hybrid method allows to find and analyze the social concept of a phenomenon; in this case, the word suicide was used as an evocative stimulus and participants were asked to evoke at least five words and a maximum 10 that they thought were related to suicide, and then hierarchize them according to the closeness with the construct. The subsequent analysis was carried with Excel, yielding the semantic weights, affective loads and the distances between each of the semantic fields established according to the words reported by the subjects. The results showed similarities in the conceptualization of suicide in adolescents, men and women. Seven semantic fields were generated; the words were related in the discourse analysis: 1) death, 2) possible triggering factors, 3) associated moods, 4) methods used to carry it out, 5) psychological symptomatology that could affect, 6) words associated with a rejection of suicide, and finally, 7) specific objects to carry it out. One of the necessary aspects to consider in the investigations of complex issues such as suicide is to have a diversity of instruments and techniques that adjust to the characteristics of the population and that allow to understand the phenomena from the social constructs and not only theoretical. The constant study of suicide is a pressing need, the loss of a life from emotional difficulties that can be solved through psychiatry and psychological methods requires governments and professionals to pay attention and work with the risk population.

Keywords: Adolescents, semantic networks, speech analysis, suicide.

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37 Sperm Whale Signal Analysis: Comparison using the Auto Regressive model and the Daubechies 15 Wavelets Transform

Authors: Olivier Adam, Maciej Lopatka, Christophe Laplanche, Jean-François Motsch

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This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.

Keywords: Autoregressive model, Daubechies Wavelet, Fourier Transform, marine mammals, signal processing, spectrogram, sperm whale, Wavelet Transform.

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36 Industrial Development, Environment And Occupational Problems: The Case Of Iran

Authors: Ghaffari, H., Changi Ashtiani, A., Younessi, A.

Abstract:

There are three distinct stages in the evolution of economic thought, namely: 1. in the first stage, the major concern was to accelerate economic growth with increased availability of material goods, especially in developing economies with very low living standards, because poverty eradication meant faster economic growth. 2. in the second stage, economists made distinction between growth and development. Development was seen as going beyond economic growth, and bringing certain changes in the structure of the economy with more equitable distribution of the benefits of growth, with the growth coming automatic and sustained. 3. the third stage is now reached. Our concern is now with “sustainable development", that is, development not only for the present but also of the future. Thus the focus changed from “sustained growth" to “sustained development". Sustained development brings to the fore the long term relationship between the ecology and economic development. Since the creation of UNEP in 1972 it has worked for development without destruction for environmentally sound and sustained development. It was realised that the environment cannot be viewed in a vaccum, it is not separate from development, nor is it competing. It suggested for the integration of the environment with development whereby ecological factors enter development planning, socio-economic policies, cost-benefit analysis, trade, technology transfer, waste management, educational and other specific areas. Industrialisation has contributed to the growth of economy of several countries. It has improved the standards of living of its people and provided benefits to the society. It has also created in the process great environmental problems like climate change, forest destruction and denudation, soil erosion and desertification etc. On the other hand, industry has provided jobs and improved the prospects of wealth for the industrialists. The working class communities had to simply put up with the high levels of pollution in order to keep up their jobs and also to save their income. There are many roots of the environmental problem. They may be political, economic, cultural and technological conditions of the modern society. The experts concede that industrial growth lies somewhere close to the heart of the matter. Therefore, the objective of this paper is not to document all roots of an environmental crisis but rather to discuss the effects of industrial growth and development. We have come to the conclusion that although public intervention is often unnecessary to ensure that perfectly competitive markets will function in society-s best interests, such intervention is necessary when firms or consumers pollute.

Keywords: Development, Environment, Industrial Development, Iran, Occupational problems, Pollution.

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35 Lightweight and Seamless Distributed Scheme for the Smart Home

Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

Abstract:

Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: Authentication, key-session, security, wireless sensors.

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