Search results for: task management
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11011

Search results for: task management

10831 Methodology to Affirm Driver Engagement in Dynamic Driving Task (DDT) for a Level 2 Adas Feature

Authors: Praneeth Puvvula

Abstract:

Autonomy in has become increasingly common in modern automotive cars. There are 5 levels of autonomy as defined by SAE. This paper focuses on a SAE level 2 feature which, by definition, is able to control the vehicle longitudinally and laterally at the same time. The system keeps the vehicle centred with in the lane by detecting the lane boundaries while maintaining the vehicle speed. As with the features from SAE level 1 to level 3, the primary responsibility of dynamic driving task lies with the driver. This will need monitoring techniques to ensure the driver is always engaged even while the feature is active. This paper focuses on the these techniques, which would help the safe usage of the feature and provide appropriate warnings to the driver.

Keywords: autonomous driving, safety, adas, automotive technology

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10830 Comparative Study between Inertial Navigation System and GPS in Flight Management System Application

Authors: Othman Maklouf, Matouk Elamari, M. Rgeai, Fateh Alej

Abstract:

In modern avionics the main fundamental component is the flight management system (FMS). An FMS is a specialized computer system that automates a wide variety of in-flight tasks, reducing the workload on the flight crew to the point that modern civilian aircraft no longer carry flight engineers or navigators. The main function of the FMS is in-flight management of the flight plan using various sensors such as Global Positioning System (GPS) and Inertial Navigation System (INS) to determine the aircraft's position and guide the aircraft along the flight plan. GPS which is satellite based navigation system, and INS which generally consists of inertial sensors (accelerometers and gyroscopes). GPS is used to locate positions anywhere on earth, it consists of satellites, control stations, and receivers. GPS receivers take information transmitted from the satellites and uses triangulation to calculate a user’s exact location. The basic principle of an INS is based on the integration of accelerations observed by the accelerometers on board the moving platform, the system will accomplish this task through appropriate processing of the data obtained from the specific force and angular velocity measurements. Thus, an appropriately initialized inertial navigation system is capable of continuous determination of vehicle position, velocity and attitude without the use of the external information. The main objective of article is to introduce a comparative study between the two systems under different conditions and scenarios using MATLAB with SIMULINK software.

Keywords: flight management system, GPS, IMU, inertial navigation system

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10829 Threshold Quantum Distillation

Authors: Shashank Gupta, Carlos Cid, William John Munro

Abstract:

Quantum distillation is the task of concentrating quantum correlations present in N imperfect copies to M perfect copies (M < N) using free operations by involving all P the parties sharing the quantum correlation. We present a threshold quantum distillation task where the same objective is achieved but using lesser number of parties (K < P). In particular, we give an exact local filtering operations by the participating parties sharing high dimension multipartite entangled state to distill the perfect quantum correlation. Later, we bridge a connection between threshold quantum entanglement distillation and quantum steering distillation and show that threshold distillation might work in the scenario where general distillation protocol like DEJMPS does not work.

Keywords: quantum networks, quantum distillation, quantum key distribution, entanglement distillation

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10828 Implementation of Congestion Management Strategies on Arterial Roads: Case Study of Geelong

Authors: A. Das, L. Hitihamillage, S. Moridpour

Abstract:

Natural disasters are inevitable to the biodiversity. Disasters such as flood, tsunami and tornadoes could be brutal, harsh and devastating. In Australia, flooding is a major issue experienced by different parts of the country. In such crisis, delays in evacuation could decide the life and death of the people living in those regions. Congestion management could become a mammoth task if there are no steps taken before such situations. In the past to manage congestion in such circumstances, many strategies were utilised such as converting the road shoulders to extra lanes or changing the road geometry by adding more lanes. However, expansion of road to resolving congestion problems is not considered a viable option nowadays. The authorities avoid this option due to many reasons, such as lack of financial support and land space. They tend to focus their attention on optimising the current resources they possess and use traffic signals to overcome congestion problems. Traffic Signal Management strategy was considered a viable option, to alleviate congestion problems in the City of Geelong, Victoria. Arterial road with signalised intersections considered in this paper and the traffic data required for modelling collected from VicRoads. Traffic signalling software SIDRA used to model the roads, and the information gathered from VicRoads. In this paper, various signal parameters utilised to assess and improve the corridor performance to achieve the best possible Level of Services (LOS) for the arterial road.

Keywords: congestion, constraints, management, LOS

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10827 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

Abstract:

The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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10826 Power Control in Solar Battery Charging Station Using Fuzzy Decision Support System

Authors: Krishnan Manickavasagam, Manikandan Shanmugam

Abstract:

Clean and abundant renewable energy sources (RES) such as solar energy is seen as the best solution to replace conventional energy source. Unpredictable power generation is a major issue in the penetration of solar energy, as power generated is governed by the irradiance received. Controlling the power generated from solar PV (SPV) panels to battery and load is a challenging task. In this paper, power flow control from SPV to load and energy storage device (ESD) is controlled by a fuzzy decision support system (FDSS) on the availability of solar irradiation. The results show that FDSS implemented with the energy management system (EMS) is capable of managing power within the area, and if excess power is available, then shared with the neighboring area.

Keywords: renewable energy sources, fuzzy decision support system, solar photovoltaic, energy storage device, energy management system

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10825 The Effects of Three Levels of Contextual Inference among adult Athletes

Authors: Abdulaziz Almustafa

Abstract:

Considering the critical role permanence has on predictions related to the contextual interference effect on laboratory and field research, this study sought to determine whether the paradigm of the effect depends on the complexity of the skill during the acquisition and transfer phases. The purpose of the present study was to investigate the effects of contextual interference CI by extending previous laboratory and field research with adult athletes through the acquisition and transfer phases. Male (n=60) athletes age 18-22 years-old, were chosen randomly from Eastern Province Clubs. They were assigned to complete blocked, random, or serial practices. Analysis of variance with repeated measures MANOVA indicated that, the results did not support the notion of CI. There were no significant differences in acquisition phase between blocked, serial and random practice groups. During the transfer phase, there were no major differences between the practice groups. Apparently, due to the task complexity, participants were probably confused and not able to use the advantages of contextual interference. This is another contradictory result to contextual interference effects in acquisition and transfer phases in sport settings. One major factor that can influence the effect of contextual interference is task characteristics as the nature of level of difficulty in sport-related skill.

Keywords: contextual interference, acquisition, transfer, task difficulty

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10824 Risk Management Approach for Lean, Agile, Resilient and Green Supply Chain

Authors: Benmoussa Rachid, Deguio Roland, Dubois Sebastien, Rasovska Ivana

Abstract:

Implementation of LARG (Lean, Agile, Resilient, Green) practices in the supply chain management is a complex task mainly because ecological, economical and operational goals are usually in conflict. To implement these LARG practices successfully, companies’ need relevant decision making tools allowing processes performance control and improvement strategies visibility. To contribute to this issue, this work tries to answer the following research question: How to master performance and anticipate problems in supply chain LARG practices implementation? To answer this question, a risk management approach (RMA) is adopted. Indeed, the proposed RMA aims basically to assess the ability of a supply chain, guided by “Lean, Green and Achievement” performance goals, to face “agility and resilience risk” factors. To proof its relevance, a logistics academic case study based on simulation is used to illustrate all its stages. It shows particularly how to build the “LARG risk map” which is the main output of this approach.

Keywords: agile supply chain, lean supply chain, green supply chain, resilient supply chain, risk approach

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10823 Waste Management in Africa

Authors: Peter Ekene Egwu

Abstract:

Waste management is of critical importance in Africa for reasons related to public health, human dignity, climate resilience and environmental preservation. However, delivering waste management services requires adequate funding, which has generally been lacking in a context where the generation of waste is outpacing the development of waste management infrastructure in most cities. The sector represents a growing percentage of cities’ greenhouse gas (GHG) emissions, and some of the African cities profiled in this study are now designing waste management strategies with emission reduction in mind.

Keywords: management waste material, Africa, uses of new technology to manage waste, waste management

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10822 The Effects of Sleep Deprivation on Vigilance, Fatigue, and Performance during Simulated Train Driving

Authors: Clara Theresia, Hardianto Iridiastadi

Abstract:

Drowsiness is one of the main factors that contribute to the occurrence of accidents, particularly in the transportation sector. While the effects of sleep deprivation on cognitive functions have been reported, the exact relationships remain a critical issue. This study aimed at quantifying the effects of extreme sleep deprivation on vigilance, fatigue, and performance during simulated train driving. A total of 12 participants were asked to drive a train simulator continuously for 4 hours, either in a sleep deprived condition (2-hr of sleep) or normal (8-hr of sleep) condition. Dependent variables obtained during the task included Psychomotor Vigilance Task (PVT) parameters, degree of fatigue (assessed via Visual Analogue Scale/VAS) and sleepiness (reported using Karolinska Sleepiness Scale/KSS), and driving performance (the number of speed limit violations). Findings from this study demonstrated substantial decrements in vigilance in the sleep-deprived condition. This condition also resulted in 75% increase in speed violation and a two-fold increase in the degree of fatigue and sleepiness. Extreme sleep deprivation was clearly associated with substantially poorer response. The exact effects, however, were dependent upon the types of responses.

Keywords: cognitive function, psychomotor vigilance task, sleep deprivation, train simulator

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10821 Multi-Criteria Evolutionary Algorithm to Develop Efficient Schedules for Complex Maintenance Problems

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

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This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

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10820 Induced Affectivity and Impact on Creativity: Personal Growth and Perceived Adjustment when Narrating an Intense Emotional Experience

Authors: S. Da Costa, D. Páez, F. Sánchez

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We examine the causal role of positive affect on creativity, the association of creativity or innovation in the ideation phase with functional emotional regulation, successful adjustment to stress and dispositional emotional creativity, as well as the predictive role of creativity for positive emotions and social adjustment. The study examines the effects of modification of positive affect on creativity. Participants write three poems, narrate an infatuation episode, answer a scale of personal growth after this episode and perform a creativity task, answer a flow scale after creativity task and fill a dispositional emotional creativity scale. High and low positive effect was induced by asking subjects to write three poems about high and low positive connotation stimuli. In a neutral condition, tasks were performed without previous affect induction. Subjects on the condition of high positive affect report more positive and less negative emotions, more personal growth (effect size r = .24) and their last poem was rated as more original by judges (effect size r = .33). Mediational analysis showed that positive emotions explain the influence of the manipulation on personal growth - positive affect correlates r = .33 to personal growth. The emotional creativity scale correlated to creativity scores of the creative task (r = .14), to the creativity of the narration of the infatuation episode (r = .21). Emotional creativity was also associated, during performing the creativity task, with flow (r = .27) and with affect balance (r = .26). The mediational analysis showed that emotional creativity predicts flow through positive affect. Results suggest that innovation in the phase of ideation is associated with a positive affect balance and satisfactory performance, as well as dispositional emotional creativity is adaptive.

Keywords: affectivity, creativity, induction, innovation, psychological factors

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10819 Neurocognitive and Executive Function in Cocaine Addicted Females

Authors: Gwendolyn Royal-Smith

Abstract:

Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.

Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function

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10818 The Development of Congeneric Elicited Writing Tasks to Capture Language Decline in Alzheimer Patients

Authors: Lise Paesen, Marielle Leijten

Abstract:

People diagnosed with probable Alzheimer disease suffer from an impairment of their language capacities; a gradual impairment which affects both their spoken and written communication. Our study aims at characterising the language decline in DAT patients with the use of congeneric elicited writing tasks. Within these tasks, a descriptive text has to be written based upon images with which the participants are confronted. A randomised set of images allows us to present the participants with a different task on every encounter, thus allowing us to avoid a recognition effect in this iterative study. This method is a revision from previous studies, in which participants were presented with a larger picture depicting an entire scene. In order to create the randomised set of images, existing pictures were adapted following strict criteria (e.g. frequency, AoA, colour, ...). The resulting data set contained 50 images, belonging to several categories (vehicles, animals, humans, and objects). A pre-test was constructed to validate the created picture set; most images had been used before in spoken picture naming tasks. Hence the same reaction times ought to be triggered in the typed picture naming task. Once validated, the effectiveness of the descriptive tasks was assessed. First, the participants (n=60 students, n=40 healthy elderly) performed a typing task, which provided information about the typing speed of each individual. Secondly, two descriptive writing tasks were carried out, one simple and one complex. The simple task contains 4 images (1 animal, 2 objects, 1 vehicle) and only contains elements with high frequency, a young AoA (<6 years), and fast reaction times. Slow reaction times, a later AoA (≥ 6 years) and low frequency were criteria for the complex task. This task uses 6 images (2 animals, 1 human, 2 objects and 1 vehicle). The data were collected with the keystroke logging programme Inputlog. Keystroke logging tools log and time stamp keystroke activity to reconstruct and describe text production processes. The data were analysed using a selection of writing process and product variables, such as general writing process measures, detailed pause analysis, linguistic analysis, and text length. As a covariate, the intrapersonal interkey transition times from the typing task were taken into account. The pre-test indicated that the new images lead to similar or even faster reaction times compared to the original images. All the images were therefore used in the main study. The produced texts of the description tasks were significantly longer compared to previous studies, providing sufficient text and process data for analyses. Preliminary analysis shows that the amount of words produced differed significantly between the healthy elderly and the students, as did the mean length of production bursts, even though both groups needed the same time to produce their texts. However, the elderly took significantly more time to produce the complex task than the simple task. Nevertheless, the amount of words per minute remained comparable between simple and complex. The pauses within and before words varied, even when taking personal typing abilities (obtained by the typing task) into account.

Keywords: Alzheimer's disease, experimental design, language decline, writing process

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10817 Deep Reinforcement Learning for Advanced Pressure Management in Water Distribution Networks

Authors: Ahmed Negm, George Aggidis, Xiandong Ma

Abstract:

With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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10816 The Effect of Work Site Dangers on the Management of Construction Projects in Syria

Authors: Mohammed Aljoma, Eblal Zakzok

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Safety is a science that seeks to protect and avoid humans from risks in any field and prevent losses in properties and lives as much as possible. On the other hand, occupational safety goals aim to protect workers from risks which can occur during work execution. The main purpose of occupational safety is to ultimately protect people, properties and the environment by reducing accidents and injuries that may cause losses and damages. To achieve this goal, we must remove the direct and indirect reasons which cause accidents and injuries; some of the reasons of accidents are the unsafe cases and inept behavior or both of them. This research focuses on the manner of providing instant protection from the very first beginning to people, properties and the environment by: -Inserting safety demands in the planning and designing works by identifying risk levels in every task of the project, -Using a new risk managing system or modifying or changing a previously-used one.

Keywords: planning, scheduling, risk management, project duration, site safety

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10815 Managing Multiple Change Projects in Supply Chains: A Case Study of a Moroccan Multi-Technical Services Company

Authors: Abdelouahab Errida, Bouchra Lotfi, Elalami Semma

Abstract:

In this paper, we try to address the topic of multiple change management by adopting an engineered research methodology, conducted within a Moroccan company during its implementation of several change projects that aim at improving its supply chain management performance. Firstly, we present the key concepts related to our research, namely change management, multiproject management and supply chain management. Then, we try to assess how the change management and multi-project management are applied in this company. Finally, we try to propose an approach that will help managers in dealing with multiple change projects. This approach proposes to integrate change management, project management and multi-project management for managing change projects according to three organizational levels: executive level, project portfolio level and change project level.

Keywords: change management, multi-project management, project management, change portfolio, supply chain management,

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10814 The Influence of Collaboration on Individual Writing Quality: The Case of Iranian vs. Malaysian Freshers

Authors: Seyed Yasin Yazdi-Amirkhiz, Azirah Hashim

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This study purported to comparatively investigate the influence of collaborative writing on the quality of individual writing of four female Iranian and four female Malaysian students. The first semester students at a private university in Malaysia, who were homogeneous in terms of age, gender, study discipline, and language proficiency, were divided into two Iranian and two Malaysian dyads. The dyads performed collaborative writing tasks for 15 sessions; after three consecutive collaborative writing sessions, each participant was asked to individually attempt a writing task. Both collaborative and individual writing tasks comprised isomorphic graphic prompts (IELTS Academic Module task 1). Writing quality of the five individually-produced texts during the study was scored in terms of task achievement (TA), cohesion/coherence (C/C), grammatical range/accuracy (GR/A), and lexical resources (LR). The findings indicated a hierarchy of development in TA and C/C among all the students, while LR showed minor improvement only among three of Malaysian students, and GR/A barely exhibited any progress among all the participants. Intermittent progressions and regressions were also discerned in the trajectory of their writing development. The findings are discussed in the light of the socio-cultural and emergentist perspectives, the typology of tasks used as well as the role of the participants’ level of language proficiency.

Keywords: collaborative writing, writing quality, individual writing, collaboration

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10813 A Case Study Comparing the Effect of Computer Assisted Task-Based Language Teaching and Computer-Assisted Form Focused Language Instruction on Language Production of Students Learning Arabic as a Foreign Language

Authors: Hanan K. Hassanein

Abstract:

Task-based language teaching (TBLT) and focus on form instruction (FFI) methods were proven to improve quality and quantity of immediate language production. However, studies that compare between the effectiveness of the language production when using TBLT versus FFI are very little with results that are not consistent. Moreover, teaching Arabic using TBLT is a new field with few research that has investigated its application inside classrooms. Furthermore, to the best knowledge of the researcher, there are no prior studies that compared teaching Arabic as a foreign language in a classroom setting using computer-assisted task-based language teaching (CATBLT) with computer-assisted form focused language instruction (CAFFI). Accordingly, the focus of this presentation is to display CATBLT and CAFFI tools when teaching Arabic as a foreign language as well as demonstrate an experimental study that aims to identify whether or not CATBLT is a more effective instruction method. The effectiveness will be determined through comparing CATBLT and CAFFI in terms of accuracy, lexical complexity, and fluency of language produced by students. The participants of the study are 20 students enrolled in two intermediate-level Arabic as a foreign language classes. The experiment will take place over the course of 7 days. Based on a study conducted by Abdurrahman Arslanyilmaz for teaching Turkish as a second language, an in-house computer assisted tool for the TBLT and another one for FFI will be designed for the experiment. The experimental group will be instructed using the in-house CATBLT tool and the control group will be taught through the in-house CAFFI tool. The data that will be analyzed are the dialogues produced by students in both the experimental and control groups when completing a task or communicating in conversational activities. The dialogues of both groups will be analyzed to understand the effect of the type of instruction (CATBLT or CAFFI) on accuracy, lexical complexity, and fluency. Thus, the study aims to demonstrate whether or not there is an instruction method that positively affects the language produced by students learning Arabic as a foreign language more than the other.

Keywords: computer assisted language teaching, foreign language teaching, form-focused instruction, task based language teaching

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10812 Proactive Disk Defragmentation through User's File-Access Patterns

Authors: Gordon Wong

Abstract:

This paper shows how the task of disk defragmentation can be handled by modern operating systems in a transparent, automated, efficient, and confined way through user's file-access patterns. Since files tend to gradually fragment from time to time through file creation, deletion, growth, and shrinking, the problem gets even worse when a disk becomes so fragmented that file accesses cannot be made reasonably efficient without performing the operation of defragmentation for the "entire" disk, which is done manually by the user by launching the disk defragmentation utility program normally bundled with the operating system. In this paper, we argue that the disk defragmentation problem described can be solved without having to manually use the utility program to defragment the entire disk. The argument is based on the observation that system users tend to access certain files in a particular time interval like the way observed for programs exhibiting temporal locality of memory references during their execution. The task of disk defragmentation can be initiated and acted upon for those files contained in the current file-access locality detected and identified by the operating system. The paper also discusses how to use the locality of file references approach to quantitatively measure and determine the locality of user's file access patterns on which the task of disk defragmentation is based.

Keywords: operating systems, disk defragmentation, locality of file accesses, system performance

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10811 Cross-Cultural Study of Stroop Interference among Juvenile Delinquents

Authors: Tanusree Moitra, Garga Chatterjee, Diganta Mukherjee, Anjali Ghosh

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Stroop task is considered to be an important measure of selective attention. However, the color – word Stroop task cannot be administered to the illiterate population. Some of the participants in the present study are illiterate, therefore, object – color Stroop task was used among male juvenile delinquents of India and Bangladesh citizenship (IC & BC), housed in delinquent home in India. The purpose of the study is to test the hypothesis that over - selective attention is present among juvenile delinquents across both the countries. Eighty juvenile delinquents and matched control of 12 – 18 years (50 IC juvenile delinquents, 30 BC juvenile delinquents and 50 Indian control) were shown 24 familiar objects in both typical (e.g. a red apple) and atypical (e.g. a blue apple) color. Repeated – measure factorial ANOVA was used and it was found that all the three groups have taken longer response time in the atypical condition compared to the typical condition. However, contrary to the over - selective attention hypothesis, both groups of juvenile delinquents displayed higher Stroop interference in comparison to the matched control group. The findings of the study can be explained on the basis of anxiety score. IC and BC juvenile delinquents have high anxiety score compared to the control group which indicates that increased anxiety is correlated with the interference produced by the atypical color object stimuli when compared with the typical object stimuli. Funding acknowledgement: Authors acknowledge Department of Science and Technology, Government of India for financial support to the first author of the paper vide Reference no. SR/CSRI/PDF -01/2013 under Cognitive Science Research Initiative (CSRI) to carry out this work.

Keywords: Bangladesh, India, male juvenile delinquent, objects - color Stroop task

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10810 Kinematic Modelling and Task-Based Synthesis of a Passive Architecture for an Upper Limb Rehabilitation Exoskeleton

Authors: Sakshi Gupta, Anupam Agrawal, Ekta Singla

Abstract:

An exoskeleton design for rehabilitation purpose encounters many challenges, including ergonomically acceptable wearing technology, architectural design human-motion compatibility, actuation type, human-robot interaction, etc. In this paper, a passive architecture for upper limb exoskeleton is proposed for assisting in rehabilitation tasks. Kinematic modelling is detailed for task-based kinematic synthesis of the wearable exoskeleton for self-feeding tasks. The exoskeleton architecture possesses expansion and torsional springs which are able to store and redistribute energy over the human arm joints. The elastic characteristics of the springs have been optimized to minimize the mechanical work of the human arm joints. The concept of hybrid combination of a 4-bar parallelogram linkage and a serial linkage were chosen, where the 4-bar parallelogram linkage with expansion spring acts as a rigid structure which is used to provide the rotational degree-of-freedom (DOF) required for lowering and raising of the arm. The single linkage with torsional spring allows for the rotational DOF required for elbow movement. The focus of the paper is kinematic modelling, analysis and task-based synthesis framework for the proposed architecture, keeping in considerations the essential tasks of self-feeding and self-exercising during rehabilitation of partially healthy person. Rehabilitation of primary functional movements (activities of daily life, i.e., ADL) is routine activities that people tend to every day such as cleaning, dressing, feeding. We are focusing on the feeding process to make people independent in respect of the feeding tasks. The tasks are focused to post-surgery patients under rehabilitation with less than 40% weakness. The challenges addressed in work are ensuring to emulate the natural movement of the human arm. Human motion data is extracted through motion-sensors for targeted tasks of feeding and specific exercises. Task-based synthesis procedure framework will be discussed for the proposed architecture. The results include the simulation of the architectural concept for tracking the human-arm movements while displaying the kinematic and static study parameters for standard human weight. D-H parameters are used for kinematic modelling of the hybrid-mechanism, and the model is used while performing task-based optimal synthesis utilizing evolutionary algorithm.

Keywords: passive mechanism, task-based synthesis, emulating human-motion, exoskeleton

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10809 Effective Parameter Selection for Audio-Based Music Mood Classification for Christian Kokborok Song: A Regression-Based Approach

Authors: Sanchali Das, Swapan Debbarma

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Music mood classification is developing in both the areas of music information retrieval (MIR) and natural language processing (NLP). Some of the Indian languages like Hindi English etc. have considerable exposure in MIR. But research in mood classification in regional language is very less. In this paper, powerful audio based feature for Kokborok Christian song is identified and mood classification task has been performed. Kokborok is an Indo-Burman language especially spoken in the northeastern part of India and also some other countries like Bangladesh, Myanmar etc. For performing audio-based classification task, useful audio features are taken out by jMIR software. There are some standard audio parameters are there for the audio-based task but as known to all that every language has its unique characteristics. So here, the most significant features which are the best fit for the database of Kokborok song is analysed. The regression-based model is used to find out the independent parameters that act as a predictor and predicts the dependencies of parameters and shows how it will impact on overall classification result. For classification WEKA 3.5 is used, and selected parameters create a classification model. And another model is developed by using all the standard audio features that are used by most of the researcher. In this experiment, the essential parameters that are responsible for effective audio based mood classification and parameters that do not significantly change for each of the Christian Kokborok songs are analysed, and a comparison is also shown between the two above model.

Keywords: Christian Kokborok song, mood classification, music information retrieval, regression

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10808 Gender Recognition with Deep Belief Networks

Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

Abstract:

A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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10807 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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10806 Modeling Driving Distraction Considering Psychological-Physical Constraints

Authors: Yixin Zhu, Lishengsa Yue, Jian Sun, Lanyue Tang

Abstract:

Modeling driving distraction in microscopic traffic simulation is crucial for enhancing simulation accuracy. Current driving distraction models are mainly derived from physical motion constraints under distracted states, in which distraction-related error terms are added to existing microscopic driver models. However, the model accuracy is not very satisfying, due to a lack of modeling the cognitive mechanism underlying the distraction. This study models driving distraction based on the Queueing Network Human Processor model (QN-MHP). This study utilizes the queuing structure of the model to perform task invocation and switching for distracted operation and control of the vehicle under driver distraction. Based on the assumption of the QN-MHP model about the cognitive sub-network, server F is a structural bottleneck. The latter information must wait for the previous information to leave server F before it can be processed in server F. Therefore, the waiting time for task switching needs to be calculated. Since the QN-MHP model has different information processing paths for auditory information and visual information, this study divides driving distraction into two types: auditory distraction and visual distraction. For visual distraction, both the visual distraction task and the driving task need to go through the visual perception sub-network, and the stimuli of the two are asynchronous, which is called stimulus on asynchrony (SOA), so when calculating the waiting time for switching tasks, it is necessary to consider it. In the case of auditory distraction, the auditory distraction task and the driving task do not need to compete for the server resources of the perceptual sub-network, and their stimuli can be synchronized without considering the time difference in receiving the stimuli. According to the Theory of Planned Behavior for drivers (TPB), this study uses risk entropy as the decision criterion for driver task switching. A logistic regression model is used with risk entropy as the independent variable to determine whether the driver performs a distraction task, to explain the relationship between perceived risk and distraction. Furthermore, to model a driver’s perception characteristics, a neurophysiological model of visual distraction tasks is incorporated into the QN-MHP, and executes the classical Intelligent Driver Model. The proposed driving distraction model integrates the psychological cognitive process of a driver with the physical motion characteristics, resulting in both high accuracy and interpretability. This paper uses 773 segments of distracted car-following in Shanghai Naturalistic Driving Study data (SH-NDS) to classify the patterns of distracted behavior on different road facilities and obtains three types of distraction patterns: numbness, delay, and aggressiveness. The model was calibrated and verified by simulation. The results indicate that the model can effectively simulate the distracted car-following behavior of different patterns on various roadway facilities, and its performance is better than the traditional IDM model with distraction-related error terms. The proposed model overcomes the limitations of physical-constraints-based models in replicating dangerous driving behaviors, and internal characteristics of an individual. Moreover, the model is demonstrated to effectively generate more dangerous distracted driving scenarios, which can be used to construct high-value automated driving test scenarios.

Keywords: computational cognitive model, driving distraction, microscopic traffic simulation, psychological-physical constraints

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10805 Algorithms for Run-Time Task Mapping in NoC-Based Heterogeneous MPSoCs

Authors: M. K. Benhaoua, A. K. Singh, A. E. Benyamina, P. Boulet

Abstract:

Mapping parallelized tasks of applications onto these MPSoCs can be done either at design time (static) or at run-time (dynamic). Static mapping strategies find the best placement of tasks at design-time, and hence, these are not suitable for dynamic workload and seem incapable of runtime resource management. The number of tasks or applications executing in MPSoC platform can exceed the available resources, requiring efficient run-time mapping strategies to meet these constraints. This paper describes a new Spiral Dynamic Task Mapping heuristic for mapping applications onto NoC-based Heterogeneous MPSoC. This heuristic is based on packing strategy and routing Algorithm proposed also in this paper. Heuristic try to map the tasks of an application in a clustering region to reduce the communication overhead between the communicating tasks. The heuristic proposed in this paper attempts to map the tasks of an application that are most related to each other in a spiral manner and to find the best possible path load that minimizes the communication overhead. In this context, we have realized a simulation environment for experimental evaluations to map applications with varying number of tasks onto an 8x8 NoC-based Heterogeneous MPSoCs platform, we demonstrate that the new mapping heuristics with the new modified dijkstra routing algorithm proposed are capable of reducing the total execution time and energy consumption of applications when compared to state-of-the-art run-time mapping heuristics reported in the literature.

Keywords: multiprocessor system on chip, MPSoC, network on chip, NoC, heterogeneous architectures, run-time mapping heuristics, routing algorithm

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10804 The Neglected Elements of Implementing Strategic Succession Management in Public Organizations

Authors: François Chiocchio, Mahshid Gharibpour

Abstract:

Regardless of the extent to which succession management is implemented in the private sector, it is still overlooked in the public sector. Traditional succession management is evolving providing a better alignment between business strategies and HR strategies. Succession management brings sustainable effectiveness for succession programs through career path development, knowledge and skill transfer, job retention, as well as high-potential candidates’ empowerment for upcoming vacancies. By way of a systematic literature review, we bring into focus strategic succession management in public organizations and discuss best ways of implementation. 

Keywords: succession management, strategic succession management, public organization, succession management model

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10803 Digital Portfolio as Mediation to Enhance Willingness to Communicate in English

Authors: Saeko Toyoshima

Abstract:

This research will discuss if performance tasks with technology would enhance students' willingness to communicate. The present study investigated how Japanese learners of English would change their attitude to communication in their target language by experiencing a performance task, called 'digital portfolio', in the classroom, applying the concepts of action research. The study adapted questionnaires including four-Likert and open-end questions as mixed-methods research. There were 28 students in the class. Many of Japanese university students with low proficiency (A1 in Common European Framework of References in Language Learning and Teaching) have difficulty in communicating in English due to the low proficiency and the lack of practice in and outside of the classroom at secondary education. They should need to mediate between themselves in the world of L1 and L2 with completing a performance task for communication. This paper will introduce the practice of CALL class where A1 level students have made their 'digital portfolio' related to the topics of TED® (Technology, Entertainment, Design) Talk materials. The students had 'Portfolio Session' twice in one term, once in the middle, and once at the end of the course, where they introduced their portfolio to their classmates and international students in English. The present study asked the students to answer a questionnaire about willingness to communicate twice, once at the end of the first term and once at the end of the second term. The four-Likert questions were statistically analyzed with a t-test, and the answers to open-end questions were analyzed to clarify the difference between them. They showed that the students had a more positive attitude to communication in English and enhanced their willingness to communicate through the experiences of the task. It will be the implication of this paper that making and presenting portfolio as a performance task would lead them to construct themselves in English and enable them to communicate with the others enjoyably and autonomously.

Keywords: action research, digital portfoliio, computer-assisted language learning, ELT with CALL system, mixed methods research, Japanese English learners, willingness to communicate

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10802 Interaction Between Task Complexity and Collaborative Learning on Virtual Patient Design: The Effects on Students’ Performance, Cognitive Load, and Task Time

Authors: Fatemeh Jannesarvatan, Ghazaal Parastooei, Jimmy frerejan, Saedeh Mokhtari, Peter Van Rosmalen

Abstract:

Medical and dental education increasingly emphasizes the acquisition, integration, and coordination of complex knowledge, skills, and attitudes that can be applied in practical situations. Instructional design approaches have focused on using real-life tasks in order to facilitate complex learning in both real and simulated environments. The Four component instructional design (4C/ID) model has become a useful guideline for designing instructional materials that improve learning transfer, especially in health profession education. The objective of this study was to apply the 4C/ID model in the creation of virtual patients (VPs) that dental students can use to practice their clinical management and clinical reasoning skills. The study first explored the context and concept of complication factors and common errors for novices and how they can affect the design of a virtual patient program. The study then selected key dental information and considered the content needs of dental students. The design of virtual patients was based on the 4C/ID model's fundamental principles, which included: Designing learning tasks that reflect real patient scenarios and applying different levels of task complexity to challenge students to apply their knowledge and skills in different contexts. Creating varied learning materials that support students during the VP program and are closely integrated with the learning tasks and students' curricula. Cognitive feedback was provided at different levels of the program. Providing procedural information where students followed a step-by-step process from history taking to writing a comprehensive treatment plan. Four virtual patients were designed using the 4C/ID model's principles, and an experimental design was used to test the effectiveness of the principles in achieving the intended educational outcomes. The 4C/ID model provides an effective framework for designing engaging and successful virtual patients that support the transfer of knowledge and skills for dental students. However, there are some challenges and pitfalls that instructional designers should take into account when developing these educational tools.

Keywords: 4C/ID model, virtual patients, education, dental, instructional design

Procedia PDF Downloads 52