Search results for: computer assisted strategies

Authors: Chia-Ling Hsieh, Kankanit Potikit

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Metadiscourse refers to linguistic resources employed by writers to organize text and interact with readers. While metadiscourse has received considerable attention within the field of discourse analysis, few studies have explored the use of metadiscourse in email, one of the most popular forms of computer-mediated communication. Furthermore, the diversity of cross-linguistic research required to uncover the influence of cultural factors on metadiscourse use is lacking. The present study compares metadiscourse markers employed in Chinese and Thai-language request emails with the purpose of discovering cross-cultural similarities and differences that are meaningful and applicable to foreign language teaching. The analysis is based on a corpus of 200 request emails: 100 composed in Chinese and 100 in Thai, with half of the emails from each language data set addressed to professors and the other half addressed to classmates. Adopting Hyland’s model as an analytical framework, two primary categories of metadiscourse are identified. Textual metadiscourse helps to create text coherence, while interpersonal metadiscourse functions to convey authorial stance. Results of the study make clear that both Chinese and Thai-language emails use significantly more interpersonal markers than textual markers, indicating that email, as a unique communicative medium, is characterized by high degrees of concision and interactivity. Users of both languages further deploy similar patterns in writing emails to recipients of different social statuses. Compared with emails addressed to classmates, emails addressed to professors are notably longer and include more transition and engagement markers. Nevertheless, cultural factors do play a role. Emails composed in Thai, for example, include more textual markers than those in Chinese, as Thai favors formal expressions and detailed explanations, while in contrast, emails composed in Chinese employ more interpersonal markers than those in Thai, since Chinese tends to emphasize recipient involvement and attitudinal warmth. These findings thereby demonstrate the combined effects of email as a communicative medium, social status, and cultural values on metadiscourse usage. The study concludes by applying these findings to pedagogical suggestions for teaching email writing to Chinese and Thai language learners based on similarities and differences in metadiscourse strategy between the two languages.

Keywords: discourse analysis, email, metadiscourse, writing instruction

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Authors: Seval Kizildag, Ozge Can Aran

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The effective intervention of counselors’ in conflict between spouses may be effective in increasing the quality of marital relationship. At this point, it is necessary for counselors to consider their own value systems at first and then reflect this correctly to the counseling process. For this reason, it is primarily important to determine the needs of counselors. Starting from this point of view, in this study, it is aimed to reveal the perspective of counselor candidates about the universal values in marriage relation. The study group of the survey was formed by sampling, which is one of the prospective sampling methods. As a criterion being a candidate for counseling area and having knowledge of the concepts of the Marriage and Family Counseling course is based, because, that candidate students have a comprehensive knowledge of the field and that students have mastered the concepts of marriage and family counseling will strengthen the findings of this study. For this reason, 61 counselor candidates, 32 (52%) female and 29 (48%) male counselor candidates, who were about to graduate from a university in south-east Turkey and who took a Marriage and Family Counseling course, voluntarily participated in the study. The average age of counselor candidates’ is 23. At the same time, 70 % of the parents of these candidates brought about their marriage through arranged marriage, 13% through flirting, 8% by relative marriage, 7% through friend circles and 2% by custom. The data were collected through Demographic Information Form and a form titled ‘Universal Values Form in Marriage’ which consists of six questions prepared by researchers. After the data were transferred to the computer, necessary statistical evaluations were made on the data. The qualitative data analysis was used on the data which was obtained in the study. The universal values which include six basic values covering trustworthiness, respect, responsibility, fairness, caring, citizenship, determined under the name as ‘six pillar of character’ are used as base and frequency values of the data were calculated trough content analysis. According to the findings of the study, while the value which most students find the most important value in marriage relation is being reliable, the value which they find the least important is to have citizenship consciousness. Also in this study, it is found out that counselor candidates associate the value of being trustworthiness ‘loyalty’ with (33%) as the highest in terms of frequency, the value of being respect ‘No violence’ with (23%), the value of responsibility ‘in the context of gender roles and spouses doing their owns’ with (35%) the value of being fairness ‘impartiality’ with (25%), the value of being caring ‘ being helpful’ with (25%) and finally as to the value of citizenship ‘love of country’ with (14%) and’ respect for the laws ‘ with (14%). It is believed that these results of the study will contribute to the arrangements for the development of counseling skills for counselor candidates regarding value in marriage and family counseling curricula.

Keywords: caring, citizenship, counselor candidate, fairness, marriage relationship, respect, responsibility, trustworthiness, value system

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Authors: Ibtisam A. Abbas Al-Darkazly

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In this study, the mechanical properties of alginate hydrogel material for self-standing 3D scaffold architecture with proper shape fidelity are investigated. In-lab built 3D bio-printer extrusion-based technology is utilized to fabricate 3D alginate scaffold constructs. The pressure, needle speed and stage speed are varied using a computer-controlled system. The experimental result indicates that the concentration of alginate solution, calcium chloride (CaCl₂) cross-linking concentration and cross-linking ratios lead to the formation of alginate hydrogel with various gelation states. Besides, the gelling conditions, such as cross-linking reaction time and temperature also have a significant effect on the mechanical properties of alginate hydrogel. Various experimental tests such as the material gelation, the material spreading and the printability test for filament collapse as well as the swelling test were conducted to evaluate the fabricated 3D scaffold constructs. The result indicates that the fabricated 3D scaffold from composition of 3.5% wt alginate solution, that is prepared in DI water and 1% wt CaCl₂ solution with cross-linking ratios of 7:3 show good printability and sustain good shape fidelity for more than 20 days, compared to alginate hydrogel that is prepared in a phosphate buffered saline (PBS). The fabricated self-standing 3D scaffold constructs measured 30 mm × 30 mm and consisted of 4 layers (n = 4) show good pore geometry and clear grid structure after printing. In addition, the percentage change of swelling degree exhibits high swelling capability with respect to time. The swelling test shows that the geometry of 3D alginate-scaffold construct and of the macro-pore are rarely changed, which indicates the capability of holding the shape fidelity during the incubation period. This study demonstrated that the mechanical and physical properties of alginate hydrogel could be tuned for a 3D bio-printing extrusion-based system to fabricate self-standing 3D scaffold soft structures. This 3D bioengineered scaffold provides a natural microenvironment present in the extracellular matrix of the tissue, which could be seeded with the biological cells to generate the desired 3D live tissue model for in vitro and in vivo tissue engineering applications.

Keywords: biomaterial, calcium chloride, 3D bio-printing, extrusion, scaffold, sodium alginate, tissue engineering

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Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

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A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

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Authors: Dipo Dunsin, Mohamed C. Ghanem, Karim Ouazzane

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Digital investigators often have a hard time spotting evidence in digital information. It has become hard to determine which source of proof relates to a specific investigation. A growing concern is that the various processes, technology, and specific procedures used in the digital investigation are not keeping up with criminal developments. Therefore, criminals are taking advantage of these weaknesses to commit further crimes. In digital forensics investigations, artificial intelligence is invaluable in identifying crime. It has been observed that an algorithm based on artificial intelligence (AI) is highly effective in detecting risks, preventing criminal activity, and forecasting illegal activity. Providing objective data and conducting an assessment is the goal of digital forensics and digital investigation, which will assist in developing a plausible theory that can be presented as evidence in court. Researchers and other authorities have used the available data as evidence in court to convict a person. This research paper aims at developing a multiagent framework for digital investigations using specific intelligent software agents (ISA). The agents communicate to address particular tasks jointly and keep the same objectives in mind during each task. The rules and knowledge contained within each agent are dependent on the investigation type. A criminal investigation is classified quickly and efficiently using the case-based reasoning (CBR) technique. The MADIK is implemented using the Java Agent Development Framework and implemented using Eclipse, Postgres repository, and a rule engine for agent reasoning. The proposed framework was tested using the Lone Wolf image files and datasets. Experiments were conducted using various sets of ISA and VMs. There was a significant reduction in the time taken for the Hash Set Agent to execute. As a result of loading the agents, 5 percent of the time was lost, as the File Path Agent prescribed deleting 1,510, while the Timeline Agent found multiple executable files. In comparison, the integrity check carried out on the Lone Wolf image file using a digital forensic tool kit took approximately 48 minutes (2,880 ms), whereas the MADIK framework accomplished this in 16 minutes (960 ms). The framework is integrated with Python, allowing for further integration of other digital forensic tools, such as AccessData Forensic Toolkit (FTK), Wireshark, Volatility, and Scapy.

Keywords: artificial intelligence, computer science, criminal investigation, digital forensics

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Authors: Pin Xiu Chen, Shang Liang Chen

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A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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Authors: Michael Adebayo, Saheed Lawal

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The Comprehensive Geriatric Assessment (CGA) is the multidimensional tool used to assess elderly, frail patients either on admission to hospital care or at a community level in primary care. It is a tool designed with the aim of using a holistic approach to managing patients. A Cochrane review of CGA use in 2011 found that the likelihood of being alive and living in their own home rises by 30% post-discharge. RCTs have also discovered 10–15% reductions in readmission rates and reductions in institutionalization, and resource use and costs. Past audit cycles at King’s College Hospital, Denmark Hill had shown inconsistent evidence of CGA completion inpatient discharge summaries (less than 50%). Junior Doctors in the Health and Ageing (HAU) wards have struggled to sustain the efforts of past audit cycles due to the quick turnover in staff (four-month placements for trainees). This 7th cycle created a multi-faceted approach to solving this problem amongst staff and creating lasting change. Methods: 1. We adopted multidisciplinary team involvement to support Doctors. MDT staff e.g. Nurses, Physiotherapists, Occupational Therapists and Dieticians, were actively encouraged to fill in the CGA document. 2. We added a CGA Document Pro-forma to “Sunrise EPR” (Trust computer system). These CGAs were to automatically be included the discharge summary. 3. Prior to assessing uptake, we used a spot audit questionnaire to assess staff awareness/knowledge of what a CGA was. 4. We designed and placed posters highlighting domains of CGA and MDT roles suited to each domain on geriatric “Health and Ageing Wards” (HAU) in the hospital. 5. We performed an audit of % discharge summaries which include CGA and MDT role input. 6. We nominated ward champions on each ward from each multidisciplinary specialty to monitor and encourage colleagues to actively complete CGAs. 7. We initiated further education of ward staff on CGA's importance by discussion at board rounds and weekly multidisciplinary meetings. Outcomes: 1. The majority of respondents to our spot audit were aware of what a CGA was, but fewer had used the EPR document to complete one. 2. We found that CGAs were not being commenced for nearly 50% of patients discharged on HAU wards and the Frailty Assessment Unit.

Keywords: comprehensive geriatric assessment, CGA, multidisciplinary team, quality of life, mortality

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

Procedia PDF Downloads 340

Authors: Sharat Chandra, Zilong Wang, Ru-Rong Ji, Andrey Bortsov

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Chronic pain (CP) therapeutic approaches have limited efficacy. As a result, doctors are prescribing opioids for chronic pain, leading to opioid overuse, abuse, and addiction epidemic. Therefore, the development of effective and safe CP drugs remains an unmet medical need. Voltage-gated sodium (Nav) channels act as cardiovascular and neurological disorder’s molecular targets. Nav channels selective inhibitors are hard to design because there are nine closely-related isoforms (Nav1.1-1.9) that share the protein sequence segments. We are targeting the Nav1.7 found in the peripheral nervous system and engaged in the perception of pain. The objective of this project was to screen a 1.5 million compound library for identification of inhibitors for Nav1.7 with analgesic effect. In this study, we designed a protocol for identification of isoform-selective inhibitors of Nav1.7, by utilizing the prior information on isoform-selective antagonists. First, a similarity search was performed; then the identified hits were docked into a binding site on the fourth voltage-sensor domain (VSD4) of Nav1.7. We used the FTrees tool for similarity searching and library generation; the generated library was docked in the VSD4 domain binding site using FlexX and compounds were shortlisted using a FlexX score and SeeSAR hyde scoring. Finally, the top 25 compounds were tested with molecular dynamics simulation (MDS). We reduced our list to 9 compounds based on the MDS root mean square deviation plot and obtained them from a vendor for in vitro and in vivo validation. Whole-cell patch-clamp recordings in HEK-293 cells and dorsal root ganglion neurons were conducted. We used patch pipettes to record transient Na⁺ currents. One of the compounds reduced the peak sodium currents in Nav1.7-HEK-293 stable cell line in a dose-dependent manner, with IC50 values at 0.74 µM. In summary, our computer-aided analgesic discovery approach allowed us to develop pre-clinical analgesic candidate with significant reduction of time and cost.

Keywords: chronic pain, voltage-gated sodium channel, isoform-selective antagonist, similarity search, virtual screening, analgesics development

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Authors: Magali Mari, Misha Muller

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The present study’s objectives were to determine how diverse implicit stereotypes affect the processing of written information and linguistic inferential processes, such as presupposition accommodation. When reading a text, one constructs a representation of the described situation, which is then updated, according to new outputs and based on stereotypes inscribed within society. If the new output contradicts stereotypical expectations, the representation must be corrected, resulting in longer reading times. A similar process occurs in cases of linguistic inferential processes like presupposition accommodation. Presupposition accommodation is traditionally regarded as fast, automatic processing of background information (e.g., ‘Mary stopped eating meat’ is quickly processed as Mary used to eat meat). However, very few accounts have investigated if this process is likely to be influenced by domains of social cognition, such as implicit stereotypes. To study the effects of implicit stereotypes on presupposition accommodation, adults were recorded while they read sentences in French, combining two methods, an eye-tracking task and a classic self-paced reading task (where participants read sentence segments at their own pace by pressing a computer key). In one condition, presuppositions were activated with the French definite articles ‘le/la/les,’ whereas in the other condition, the French indefinite articles ‘un/une/des’ was used, triggering no presupposition. Using a definite article presupposes that the object has already been uttered and is thus part of background information, whereas using an indefinite article is understood as the introduction of new information. Two types of stereotypes were under examination in order to enlarge the scope of stereotypes traditionally analyzed. Study 1 investigated gender stereotypes linked to professional occupations to replicate previous findings. Study 2 focused on nationality-related stereotypes (e.g. ‘the French are seducers’ versus ‘the Japanese are seducers’) to determine if the effects of implicit stereotypes on reading are generalizable to other types of implicit stereotypes. The results show that reading is influenced by the two types of implicit stereotypes; in the two studies, the reading pace slowed down when a counter-stereotype was presented. However, presupposition accommodation did not affect participants’ processing of information. Altogether these results show that (a) implicit stereotypes affect the processing of written information, regardless of the type of stereotypes presented, and (b) that implicit stereotypes prevail over the superficial linguistic treatment of presuppositions, which suggests faster processing for treating social information compared to linguistic information.

Keywords: eye-tracking, implicit stereotypes, reading, social cognition

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Authors: V. I. Kozyavkin, L. F. Shestopalova, T. B. Voloshyn

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Introduction: Rehabilitation of children with Autism is the issue of the day in psychiatry and neurology. It is attributed to constantly increasing quantity of autistic children - Autistic Spectrum Disorders (ASD) Existing rehabilitation approaches in treatment of children with Autism improve their medico- social and social- psychological adjustment. Experience of treatment for different kinds of Autistic disorders in International Clinic of Rehabilitation (ICR) reveals the necessity of complex intensive approach for healing this malady and wider implementation of a Kozyavkin method for treatment of children with ASD. Methods: 19 children aged from 3 to 14 years were examined. They were diagnosed ‘Autism’ (F84.0) with comorbid neurological pathology (from pyramidal insufficiency to para- and tetraplegia). All patients underwent rehabilitation in ICR during two weeks, where INRS approach was used. INRS included methods like biomechanical correction of the spine, massage, physical therapy, joint mobilization, wax-paraffin applications. They were supplemented by art- therapy, ergotherapy, rhythmical group exercises, computer game therapy, team Olympic games and other methods for improvement of motivation and social integration of the child. Estimation of efficacy was conducted using parent’s questioning and done twice- on the onset of INRS rehabilitation course and two weeks afterward. For efficacy assessment of rehabilitation of autistic children in ICR standardized tool was used, namely Autism Treatment Evaluation Checklist (ATEC). This scale was selected because any rehabilitation approaches for the child with Autism can be assessed using it. Results: Before the onset of INRS treatment mean score according to ATEC scale was 64,75±9,23, it reveals occurrence in examined children severe communication, speech, socialization and behavioral impairments. After the end of the rehabilitation course, the mean score was 56,5±6,7, what indicates positive dynamics in comparison to the onset of rehabilitation. Generally, improvement of psychoemotional state occurred in 90% of cases. Most significant changes occurred in the scope of speech (16,5 before and 14,5 after the treatment), socialization (15.1 before and 12,5 after) and behavior (20,1 before and 17.4 after). Conclusion: As a result of INRS rehabilitation course reduction of autistic symptoms was noted. Particularly improvements in speech were observed (children began to spell out new syllables, words), there was some decrease in signs of destructiveness, quality of contact with the surrounding people improved, new skills of self-service appeared. The prospect of the study is further, according to evidence- based medicine standards, deeper examination of INRS and assessment of its usefulness in treatment for Autism and ASD.

Keywords: intensive neurophysiological rehabilitation system (INRS), international clinic od rehabilitation, ASD, rehabilitation

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Authors: Fikret Yalcinkaya, Hamza Unsal

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To understand how neurons work, it is required to combine experimental studies on neural science with numerical simulations of neuron models in a computer environment. In this regard, the simplicity and applicability of spiking neuron modeling functions have been of great interest in computational neuron science and numerical neuroscience in recent years. Spiking neuron models can be classified by exhibiting various neuronal behaviors, such as spiking and bursting. These classifications are important for researchers working on theoretical neuroscience. In this paper, three different spiking neuron models; Izhikevich, Adaptive Exponential Integrate Fire (AEIF) and Hindmarsh Rose (HR), which are based on first order differential equations, are discussed and compared. First, the physical meanings, derivatives, and differential equations of each model are provided and simulated in the Matlab environment. Then, by selecting appropriate parameters, the models were visually examined in the Matlab environment and it was aimed to demonstrate which model can simulate well-known biological neuron behaviours such as Tonic Spiking, Tonic Bursting, Mixed Mode Firing, Spike Frequency Adaptation, Resonator and Integrator. As a result, the Izhikevich model has been shown to perform Regular Spiking, Continuous Explosion, Intrinsically Bursting, Thalmo Cortical, Low-Threshold Spiking and Resonator. The Adaptive Exponential Integrate Fire model has been able to produce firing patterns such as Regular Ignition, Adaptive Ignition, Initially Explosive Ignition, Regular Explosive Ignition, Delayed Ignition, Delayed Regular Explosive Ignition, Temporary Ignition and Irregular Ignition. The Hindmarsh Rose model showed three different dynamic neuron behaviours; Spike, Burst and Chaotic. From these results, the Izhikevich cell model may be preferred due to its ability to reflect the true behavior of the nerve cell, the ability to produce different types of spikes, and the suitability for use in larger scale brain models. The most important reason for choosing the Adaptive Exponential Integrate Fire model is that it can create rich ignition patterns with fewer parameters. The chaotic behaviours of the Hindmarsh Rose neuron model, like some chaotic systems, is thought to be used in many scientific and engineering applications such as physics, secure communication and signal processing.

Keywords: Izhikevich, adaptive exponential integrate fire, Hindmarsh Rose, biological neuron behaviours, spiking neuron models

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Authors: Chiu-Yin Leung

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This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Eric Bates

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Higher education is recognised as being of critical importance in Ireland and has been linked as a vital factor to national well-being. Statistics show that Ireland has one of the highest rates of higher education participation in Europe. However, student retention and progression, especially in Institutes of Technology, is becoming an issue as rates on non-completion rise. Both within Ireland and across Europe student retention is seen as a key performance indicator for higher education and with these increasing rates the Irish higher education system needs to be flexible and adapt to the situation it now faces. The author is a Programme Chair on a Level 6 full time undergraduate programme and experience to date has shown that the first year undergraduate students take some time to identify themselves as a group within the setting of a higher education institute. Despite being part of a distinct class on a specific programme some individuals can feel isolated as he or she take the first step into higher education. Such feelings can contribute to students eventually dropping out. This paper reports on an ongoing initiative that aims to accelerate the bonding experience of a distinct group of first year undergraduates on a programme which has a high rate of non-completion. This research sought to engage the students in dynamic interactions with their peers to quickly evolve a group sense of coherence. Two separate modules – a Research Module and a Communications module - delivered by the researcher were linked across two semesters. Students were allocated into random groups and each group was given a topic to be researched. There were six topics – essentially the six sub-headings on the DIT Graduate Attribute Statement. The research took place in a computer lab and students also used the library. The output from this was a document that formed part of the submission for the Research Module. In the second semester the groups then had to make a presentation of their findings where each student spoke for a minimum amount of time. Presentation workshops formed part of that module and students were given the opportunity to practice their presentation skills. These presentations were video recorded to enable feedback to be given. Although this was a small scale study preliminary results found a strong sense of coherence among this particular cohort and feedback from the students was very positive. Other findings indicate that spreading the initiative across two semesters may have been an inhibitor. Future challenges include spreading such Initiatives College wide and indeed sector wide.

Keywords: first year experience, student retention, group work, presentation workshops

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Authors: Ardita Malaj, Ahmad R. Alsaber, Bedour Alboloushi, Anwaar Alkandari

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Organizations worldwide, particularly in Kuwait, are concerned with implementing a progressive workplace culture and fostering social innovation behaviours. The main aim of this research is to examine and establish a thorough comprehension of the relationship between an inventive organizational culture, employee intrapreneurial behaviour, authentic leadership, employee job satisfaction, and employee job commitment in the manufacturing sector of Kuwait, which is a developed economy. Literature reviews analyse the core concepts and their related areas by scrutinizing their definitions, dimensions, and importance to uncover any deficiencies in existing research. The examination of relevant research uncovered major gaps in understanding. This study examines the reliability and validity of a newly developed questionnaire designed to identify the appropriate applications for a large-scale investigation. A preliminary investigation was carried out, determining a sample size of 36 respondents selected randomly from a pool of 223 samples. SPSS was utilized to calculate the percentages of the demographic characteristics for the participants, assess the credibility of the measurements, evaluate the internal consistency, validate all agreements, and determine Pearson's correlation. The study's results indicated that the majority of participants were male (66.7%), aged between 35 and 44 (38.9%), and possessed a bachelor's degree (58.3%). Approximately 94.4% of the participants were employed full-time. 72.2% of the participants are employed in the electrical, computer, and ICT sector, whilst 8.3% work in the metal industry. Out of all the departments, the human resource department had the highest level of engagement, making up 13.9% of the total. Most participants (36.1%) possessed intermediate or advanced levels of experience, whilst 21% were classified as entry-level. Furthermore, 8.3% of individuals were categorized as first-level management, 22.2% were categorized as middle management, and 16.7% were categorized as executive or senior management. Around 19.4% of the participants have over a decade of professional experience. The Pearson's correlation coefficient for all 5 components varies between 0.4009 to 0.7183. The results indicate that all elements of the questionnaire were effectively verified, with a Cronbach alpha factor predominantly exceeding 0.6, which is the criterion commonly accepted by researchers. Therefore, the work on the larger scope of testing and analysis could continue.

Keywords: pilot study, ESIB, innovative organizational culture, Kuwait, validation

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Authors: M. Agostini, A. Sonato, G. Greco, M. Travagliati, G. Ruffato, E. Gazzola, D. Liuni, F. Romanato, M. Cecchini

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Since their first demonstration in the early 1980s, surface plasmon resonance (SPR) sensors have been widely recognized as useful tools for detecting chemical and biological species, and the interest of the scientific community toward this technology has known a rapid growth in the past two decades owing to their high sensitivity, label-free operation and possibility of real-time detection. Recent works have suggested that a turning point in SPR sensor research would be the combination of SPR strategies with other technologies in order to reduce human handling of samples, improve integration and plasmonic sensitivity. In this light, microfluidics has been attracting growing interest. By properly designing microfluidic biochips it is possible to miniaturize the analyte-sensitive areas with an overall reduction of the chip dimension, reduce the liquid reagents and sample volume, improve automation, and increase the number of experiments in a single biochip by multiplexing approaches. However, as the fluidic channel dimensions approach the micron scale, laminar flows become dominant owing to the low Reynolds numbers that typically characterize microfluidics. In these environments mixing times are usually dominated by diffusion, which can be prohibitively long and lead to long-lasting biochemistry experiments. An elegant method to overcome these issues is to actively perturb the liquid laminar flow by exploiting surface acoustic waves (SAWs). With this work, we demonstrate a new approach for SPR biosensing based on the combination of microfluidics, SAW-induced mixing and the real-time phase-interrogation grating-coupling SPR technology. On a single lithium niobate (LN) substrate the nanostructured SPR sensing areas, interdigital transducer (IDT) for SAW generation and polydimethylsiloxane (PDMS) microfluidic chambers were fabricated. SAWs, impinging on the microfluidic chamber, generate acoustic streaming inside the fluid, leading to chaotic advection and thus improved fluid mixing, whilst analytes binding detection is made via SPR method based on SPP excitation via gold metallic grating upon azimuthal orientation and phase interrogation. Our device has been fully characterized in order to separate for the very first time the unwanted SAW heating effect with respect to the fluid stirring inside the microchamber that affect the molecules binding dynamics. Avidin/biotin assay and thiol-polyethylene glycol (bPEG-SH) were exploited as model biological interaction and non-fouling layer respectively. Biosensing kinetics time reduction with SAW-enhanced mixing resulted in a ≈ 82% improvement for bPEG-SH adsorption onto gold and ≈ 24% for avidin/biotin binding—≈ 50% and 18% respectively compared to the heating only condition. These results demonstrate that our biochip can significantly reduce the duration of bioreactions that usually require long times (e.g., PEG-based sensing layer, low concentration analyte detection). The sensing architecture here proposed represents a new promising technology satisfying the major biosensing requirements: scalability and high throughput capabilities. The detection system size and biochip dimension could be further reduced and integrated; in addition, the possibility of reducing biological experiment duration via SAW-driven active mixing and developing multiplexing platforms for parallel real-time sensing could be easily combined. In general, the technology reported in this study can be straightforwardly adapted to a great number of biological system and sensing geometry.

Keywords: biosensor, microfluidics, surface acoustic wave, surface plasmon resonance

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Authors: Alok Madan, Ashok Gupta, Arshad K. Hashmi

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Non-linear dynamic time history analysis is considered as the most advanced and comprehensive analytical method for evaluating the seismic response and performance of multi-degree-of-freedom building structures under the influence of earthquake ground motions. However, effective and accurate application of the method requires the implementation of advanced hysteretic constitutive models of the various structural components including masonry infill panels. Sophisticated computational research tools that incorporate realistic hysteresis models for non-linear dynamic time-history analysis are not popular among the professional engineers as they are not only difficult to access but also complex and time-consuming to use. And, commercial computer programs for structural analysis and design that are acceptable to practicing engineers do not generally integrate advanced hysteretic models which can accurately simulate the hysteresis behavior of structural elements with a realistic representation of strength degradation, stiffness deterioration, energy dissipation and ‘pinching’ under cyclic load reversals in the inelastic range of behavior. In this scenario, push-over or non-linear static analysis methods have gained significant popularity, as they can be employed to assess the seismic performance of building structures while avoiding the complexities and difficulties associated with non-linear dynamic time-history analysis. “Push-over” or non-linear static analysis offers a practical and efficient alternative to non-linear dynamic time-history analysis for rationally evaluating the seismic demands. The present paper is based on the analytical investigation of the effect of distribution of masonry infill panels over the elevation of planar masonry infilled reinforced concrete (R/C) frames on the seismic demands using the capacity spectrum procedures implementing nonlinear static analysis (pushover analysis) in conjunction with the response spectrum concept. An important objective of the present study is to numerically evaluate the adequacy of the capacity spectrum method using pushover analysis for performance based design of masonry infilled R/C frames for near-field earthquake ground motions.

Keywords: nonlinear analysis, capacity spectrum method, response spectrum, seismic demand, near-field earthquakes

Procedia PDF Downloads 382

Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

Procedia PDF Downloads 58

Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: T. Schmitt, J. Rosin, C. Butenweg

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Seismic design of buried pipeline systems for energy and water supply is not only important for plant and operational safety, but in particular for the maintenance of supply infrastructure after an earthquake. Past earthquakes have shown the vulnerability of pipeline systems. After the Kobe earthquake in Japan in 1995 for instance, in some regions the water supply was interrupted for almost two months. The present paper shows special issues of the seismic wave impacts on buried pipelines, describes calculation methods, proposes approaches and gives calculation examples. Buried pipelines are exposed to different effects of seismic impacts. This paper regards the effects of transient displacement differences and resulting tensions within the pipeline due to the wave propagation of the earthquake. Other effects are permanent displacements due to fault rupture displacements at the surface, soil liquefaction, landslides and seismic soil compaction. The presented model can also be used to calculate fault rupture induced displacements. Based on a three-dimensional Finite Element Model parameter studies are performed to show the influence of several parameters such as incoming wave angle, wave velocity, soil depth and selected displacement time histories. In the computer model, the interaction between the pipeline and the surrounding soil is modeled with non-linear soil springs. A propagating wave is simulated affecting the pipeline punctually independently in time and space. The resulting stresses mainly are caused by displacement differences of neighboring pipeline segments and by soil-structure interaction. The calculation examples focus on pipeline bends as the most critical parts. Special attention is given to the calculation of long-distance heat pipeline systems. Here, in regular distances expansion bends are arranged to ensure movements of the pipeline due to high temperature. Such expansion bends are usually designed with small bending radii, which in the event of an earthquake lead to high bending stresses at the cross-section of the pipeline. Therefore, Karman's elasticity factors, as well as the stress intensity factors for curved pipe sections, must be taken into account. The seismic verification of the pipeline for wave propagation in the soil can be achieved by observing normative strain criteria. Finally, an interpretation of the results and recommendations are given taking into account the most critical parameters.

Keywords: buried pipeline, earthquake, seismic impact, transient displacement

Procedia PDF Downloads 164

Authors: M. J. Ponnambalam

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Physics Outreach in Jamaica has nearly tripled the number of students doing Introductory Calculus-based Physics at the University of the West Indies (UWI, Mona) within 5 years, and thus has shown the importance of Physics Teaching & Learning in Informal Settings. In 1899, the first president of the American Physical Society called Physics, “the science above all sciences.” Sure enough, exactly one hundred years later, Time magazine proclaims Albert Einstein, “Person of the Century.” Unfortunately, Physics seems to be losing that glow in this century. Many countries, big and small, are finding it difficult to attract bright young minds to pursue Physics. At UWI, Mona, the number of students in first year Physics dropped to an all-time low of 81 in 2006, from more than 200 in the nineteen eighties, spelling disaster for the Physics Department! The author of this paper launched an aggressive Physics Outreach that same year, aimed at conveying to the students and the general public the following messages: i) Physics is an exciting intellectual enterprise, full of fun and delight. ii) Physics is very helpful in understanding how things like TV, CD player, car, computer, X-ray, CT scan, MRI, etc. work. iii) The critical and analytical thinking developed in the study of Physics is of inestimable value in almost any field. iv) Physics is the core subject for Science and Technology, and hence of national development. Science Literacy is a ‘must’ for any nation in the 21st century. Hence, the Physics Outreach aims at reaching out to every person, through every possible means. The Outreach work is split into the following target groups: i) Universities, ii) High Schools iii) Middle Schools, iv) Primary Schools, v) General Public, and vi) Physics teachers in High Schools. The programmes, tools and best practices are adjusted to suit each target group. The feedback from each group is highly positive. e.g. In February 2014, the author conducted in 3 Primary Schools the Interactive Show on ‘Science Is Fun’ to stimulate 290 students’ interest in Science – with lively and interesting demonstrations and experiments in a highly interactive way, using dramatization, story-telling and dancing. The feedback: 47% found the Show ‘Exciting’ and 51% found it ‘Interesting’ – totaling an impressive 98%. When asked to describe the Show in their own words, the leading 4 responses were: ‘Fun’ (26%), ‘Interesting’ (20%), ‘Exciting’ (14%) and ‘Educational’ (10%) – confirming that ‘fun’ & ‘education’ can go together. The success of Physics Outreach in Jamaica verifies the following words of Chodos, Associate Executive Officer of the American Physical Society: “If we could get members to go to K-12 schools and levitate a magnet or something, we really think these efforts would bring great rewards.”

Keywords: physics education, physics popularization, UWI, Jamaica

Procedia PDF Downloads 374

Authors: F. Saccucci

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Gamification has now started to take root in the post-secondary classroom. Educators have learned much about gamification to date but there is still a great deal to learn. One definition of gamification is the ability to engage post-secondary students with games that are fun and correlate to class room curriculum. There is no shortage of literature illustrating the advantages of gamification in the class room. This study is an extension of similar thought as well as an extension of a previous study where in class testing proved with the used of paired T-test that gamification did significantly improve the students’ understanding of subject material. Gamification itself in the class room can range from high end computer simulated software to paper based games of which both have advantages and disadvantages. This analysis used a paper based game to highlight certain qualitative advantages of gamification. The paper based game in this analysis was inexpensive, required low preparation time for the faculty member and consumed approximately 20 minutes of class room time. Data for the study was collected through in class student feedback surveys and narrative from the faculty member moderating the game. Students were randomly selected into groups of four. Qualitative advantages identified in this analysis included: 1. Students had a chance to meet, connect and know other students. 2. Students enjoyed the gamification process given there was a sense of fun and competition. 3. The post assessment that followed the simulation game was not part of their grade calculation therefore it was an opportunity to participate in a low risk activity whereby students could subsequently self-assess their understanding of the subject material. 4. In the view of the student, content knowledge did increase after the gamification process. These qualitative advantages identified in this analysis contribute to the argument that there should be an attempt to use gamification in today’s post-secondary class room. The analysis also highlighted that eighty (80) percent of the respondents believe twenty minutes devoted to the gamification process was appropriate, however twenty (20) percentage of respondents believed that rather than scheduling a gamification process and its post quiz in the last week, a review for the final exam may have been more useful. An additional study to this hopes to determine if the scheduling of the gamification had any correlation to a percentage of the students not wanting to be engaged in the process. As well, the additional study hopes to determine at what incremental level of time invested in class room gamification produce no material incremental benefits to the student as well as determine if any correlation exist between respondents preferring not to have it at the end of the semester to students not believing the gamification process added to the increase of their curricular knowledge.

Keywords: gamification, inexpensive, non-quantitative advantages, post-secondary

Procedia PDF Downloads 187

Authors: Belbaly Nassim

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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

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Authors: Oluwaseun Ijiwade, Chris Davison, Kelvin Gregory

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In Australia, like other parts of the world, the debate on how to enhance teachers using assessment data to inform teaching and learning of English as an Additional Language (EAL, Australia) or English as a Foreign Language (EFL, United States) have occupied the centre of academic scholarship. Traditionally, this approach was conceptualised as ‘Formative Assessment’ and, in recent times, ‘Assessment for Learning (AfL)’. The central problem is that teacher-made tests are limited in providing data that can inform teaching and learning due to variability of classroom assessments, which are hindered by teachers’ characteristics and assessment literacy. To address this concern, scholars in language education and testing have proposed a uniformed large-scale computer-based assessment program to meet the needs of teachers and promote AfL in language education. In Australia, for instance, the Victoria state government commissioned a large-scale project called 'Tools to Enhance Assessment Literacy (TEAL) for Teachers of English as an additional language'. As part of the TEAL project, a tool called ‘Reading and Vocabulary assessment for English as an Additional Language (RVEAL)’, as a diagnostic language assessment (DLA), was developed by language experts at the University of New South Wales for teachers in Victorian schools to guide EAL pedagogy in the classroom. Therefore, this study aims to provide qualitative evidence for understanding beliefs about the diagnostic language assessment (DLA) among EAL teachers in primary and secondary schools in Victoria, Australia. To realize this goal, this study raises the following questions: (a) How do teachers use large-scale assessment data for diagnostic purposes? (b) What skills do language teachers think are necessary for using assessment data for instruction in the classroom? and (c) What factors, if any, contribute to teachers’ beliefs about diagnostic assessment in a large-scale assessment? Semi-structured interview method was used to collect data from at least 15 professional teachers who were selected through a purposeful sampling. The findings from the resulting data analysis (thematic analysis) provide an understanding of teachers’ beliefs about DLA in a classroom context and identify how these beliefs are crystallised in language teachers. The discussion shows how the findings can be used to inform professional development processes for language teachers as well as informing important factor of teacher cognition in the pedagogic processes of language assessment. This, hopefully, will help test developers and testing organisations to align the outcome of this study with their test development processes to design assessment that can enhance AfL in language education.

Keywords: beliefs, diagnostic language assessment, English as an additional language, teacher cognition

Procedia PDF Downloads 176

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

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The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

Procedia PDF Downloads 223

Authors: Samuel Faboyede, Obiamaka Nwobu, Samuel Fakile, Dickson Mukoro

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In the present dynamic business environment of corporate governance and regulations, financial reporting is an inevitable and extremely significant process for every business enterprise. Several financial elements such as Annual Reports, Quarterly Reports, ad-hoc filing, and other statutory/regulatory reports provide vital information to the investors and regulators, and establish trust and rapport between the internal and external stakeholders of an organization. Investors today are very demanding, and emphasize greatly on authenticity, accuracy, and reliability of financial data. For many companies, the Internet plays a key role in communicating business information, internally to management and externally to stakeholders. Despite high prominence being attached to external reporting, it is disconnected in most companies, who generate their external financial documents manually, resulting in high degree of errors and prolonged cycle times. Chief Executive Officers and Chief Financial Officers are increasingly susceptible to endorsing error-laden reports, late filing of reports, and non-compliance with regulatory acts. There is a lack of common platform to manage the sensitive information – internally and externally – in financial reports. The Internet financial reporting language known as eXtensible Business Reporting Language (XBRL) continues to develop in the face of challenges and has now reached the point where much of its promised benefits are available. This paper looks at the emergence of this revolutionary twenty-first century language of digital reporting. It posits that today, the world is on the brink of an Internet revolution that will redefine the ‘business reporting’ paradigm. The new Internet technology, eXtensible Business Reporting Language (XBRL), is already being deployed and used across the world. It finds that XBRL is an eXtensible Markup Language (XML) based information format that places self-describing tags around discrete pieces of business information. Once tags are assigned, it is possible to extract only desired information, rather than having to download or print an entire document. XBRL is platform-independent and it will work on any current or recent-year operating system, or any computer and interface with virtually any software. The paper concludes that corporate stakeholders and the government cannot afford to ignore the XBRL. It therefore recommends that all must act locally and think globally now via the adoption of XBRL that is changing the face of worldwide business reporting.

Keywords: XBRL, financial reporting, internet, internal and external reports

Procedia PDF Downloads 257

Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

Procedia PDF Downloads 260

Authors: Iryna Biskub

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The interdisciplinary approach to modern linguistic studies is exemplified by the merge of various research methods, which sometimes causes complications related to the verification of the research results. This methodological confusion can be resolved by means of creating new techniques of linguistic analysis combining several scientific paradigms. Modern linguistics has developed really productive and efficient methods for the investigation of cognitive and communicative phenomena of which language is the central issue. In the field of discourse studies, one of the best examples of research methods is the method of Critical Discourse Analysis (CDA). CDA can be viewed both as a method of investigation, as well as a critical multidisciplinary perspective. In CDA the position of the scholar is crucial from the point of view exemplifying his or her social and political convictions. The generally accepted approach to obtaining scientifically reliable results is to use a special well-defined scientific method for researching special types of language phenomena: cognitive methods applied to the exploration of cognitive aspects of language, whereas communicative methods are thought to be relevant only for the investigation of communicative nature of language. In the recent decades discourse as a sociocultural phenomenon has been the focus of careful linguistic research. The very concept of discourse represents an integral unity of cognitive and communicative aspects of human verbal activity. Since a human being is never able to discriminate between cognitive and communicative planes of discourse communication, it doesn’t make much sense to apply cognitive and communicative methods of research taken in isolation. It is possible to modify the classical CDA procedure by means of mapping human cognitive procedures onto the strategic communicative planning of discourse communication. The analysis of the electronic petition 'Block Donald J Trump from UK entry. The signatories believe Donald J Trump should be banned from UK entry' (584, 459 signatures) and the parliamentary debates on it has demonstrated the ability to map cognitive and communicative levels in the following way: the strategy of discourse modeling (communicative level) overlaps with the extraction of semantic macrostructures (cognitive level); the strategy of discourse management overlaps with the analysis of local meanings in discourse communication; the strategy of cognitive monitoring of the discourse overlaps with the formation of attitudes and ideologies at the cognitive level. Thus, the experimental data have shown that it is possible to develop a new complex methodology of discourse analysis, where cognition would meet communication, both metaphorically and literally. The same approach may appear to be productive for the creation of computational models of human-computer interaction, where the automatic generation of a particular type of a discourse could be based on the rules of strategic planning involving cognitive models of CDA.

Keywords: cognition, communication, discourse, strategy

Procedia PDF Downloads 229

Authors: Margo O'Sullivan, Xuefeng Chen, Qi Zhao, J. Jiang, Ning Fu

Abstract:

Early childhood development, or ECD, is about the 'whole child' – the physical, social and emotional, cognitive thinking and language progression of each young individual. Overwhelming evidence is now available to support investment in Early Childhood Development internationally, attendance at ECD leads to: improved learning outcomes; improved completion and reduced less dropout rates; and most notably, Professor Heckman, Nobel Laureate’s, findings that for every dollar invested, there is an economic return of up to 17%. Notably, ECD has been included in the 2015-2030 Sustainable Development Goals. The Government of China (GOC) has embraced this research and in 2010, State Council, announced focus on ECD setting a target to provide access to ECD for 85% of 3-6 year olds by 2020; to date, the target has surpassed expectations and reached 70.4%. GoC is also increasingly focusing on the even more critical 0-3 age group, when the plasticity of the brain is at its peak and neurons form connections as fast as 1,000 per second. Key to ECD are parents and caregivers of young children, with parental education critical to fully exploiting the significant potential of the early years of children. In China, with such vast numbers, one in seven pre-school age children in the world live in China, the Ministry of Education (MoE) and the National Centre for Education Technology, explored how to best provide parental education and provide key child developmental related knowledge to parents and caregivers. In response, MoE and UNICEF created a resource for parenting information that began with a computer website in 2012, followed by piloting a kiosk service in 2013 for parents in remote areas without access to the internet, and then a mobile phone application in 2014. The resource includes 269 ECD messages and 200 micro-videos covering critical issues of early childhood development from birth to age 6 years: daily care, nutrition and feeding, disease prevention, immunization, development and education, and safety and protection. To date, there have been 397,599 unique views on the website, and data for the mobile app currently being analysed (Links: http://yuer.cbern.gov.cn/; App: https://appsto.re/cn/OiKPZ.i). This paper will explore the development of this resource, its use by parents and the public, efforts to assess the effectiveness in improving parenting and child development, and future plans to roll an updated version in 2016 to all parents.

Keywords: early childhood development, mobile apps for education, parental education, China

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