Search results for: interactive user navigation

Authors: R. Malisa, E. Schwella, K. I. Theletsane

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Due to climate change, population growth and rapid urbanization, the demand for water in South Africa is inevitably surpassing supply. To address similar challenges globally, there has been a paradigm shift from conventional urban waste water management “government” to a “governance” paradigm. From the governance paradigm, Integrated Urban Water Management (IUWM) principle emerged. This principle emphasizes efficient urban waste water treatment and production of high-quality recyclable effluent. In so doing mimicking natural water systems, in their processes of recycling water efficiently, and averting depletion of natural water resources.  The objective of this study was to investigate drivers of shifting the current urban waste water management approach from a “government” paradigm towards “governance”. The study was conducted through Interactive Management soft systems research methodology which follows a qualitative research design. A case study methodology was employed, guided by realism research philosophy. Qualitative data gathered were analyzed through interpretative structural modelling using Concept Star for Professionals Decision-Making tools (CSPDM) version 3.64.  The constructed model deduced that the main drivers in shifting the Stellenbosch municipal urban waste water management towards IUWM “governance” principles are mainly social elements characterized by overambitious expectations of the public on municipal water service delivery, mis-interpretation of the constitution on access to adequate clean water and sanitation as a human right and perceptions on recycling water by different communities. Inadequate public participation also emerged as a strong driver. However, disruptive events such as draught may play a positive role in raising an awareness on the value of water, resulting in a shift on the perceptions on recycled water. Once the social elements are addressed, the alignment of governance and administration elements towards IUWM are achievable. Hence, the point of departure for the desired paradigm shift is the change of water service authorities and serviced communities’ perceptions and behaviors towards shifting urban waste water management approaches from “government” to “governance” paradigm.

Keywords: integrated urban water management, urban water system, wastewater governance, wastewater treatment works

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Authors: Carlos G. Santos, Frederico A. Genezini, A. P. Dos Santos, H. Yorivaz, P. T. D. Siqueira

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The Prompt-Gamma Activation Analysis (PGAA) is a valuable technique for investigating the elemental composition of various samples. However, the installation of a PGAA system entails specific conditions such as filtering the neutron beam according to the target and providing adequate shielding for both users and detectors. These requirements incur substantial costs, exceeding $100,000, including manpower. Nevertheless, a cost-effective approach involves leveraging an existing neutron beam facility to create a hybrid system integrating PGAA and Neutron Tomography (NT). The IEA-R1 nuclear reactor at IPEN/USP possesses an NT facility with suitable conditions for adapting and implementing a PGAA device. The NT facility offers a thermal flux slightly colder and provides shielding for user protection. The key additional requirement involves designing detector shielding to mitigate high gamma ray background and safeguard the HPGe detector from neutron-induced damage. This study employs Monte Carlo simulations with the MCNP6 code to optimize the collimator plug for PGAA within the IEA-R1 NT facility. Three collimator models are proposed and simulated to assess their effectiveness in shielding gamma and neutron radiation from nucleon fission. The aim is to achieve a focused prompt-gamma signal while shielding ambient gamma radiation. The simulation results indicate that one of the proposed designs is particularly suitable for the PGAA-NT hybrid system.

Keywords: MCNP6.1, neutron, prompt-gamma ray, prompt-gamma activation analysis

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Authors: Satyen Mondal, Frederickson Entila, Shalabh Dixit, Pompe C. Sta. Cruz, Abdelbagi M. Ismail

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Anaerobic condition caused by flooding during germination in direct seeded rice systems, known as anaerobic germination (AG), severely reduces crop establishment in both rainfed and irrigated areas. Seeds germinating in flooded soils could encounter hypoxia or even anoxia in severe cases, and this hinders germination and seedling growth. This study was conducted to quantify the effects of incorporating two major QTLs, AG1 and AG2, associated with tolerance of flooding during germination and to assess their interactive effects on enhancing crop establishment. A greenhouse experiment was conducted at the International Rice Research Institute (IRRI), Los Baňos, Philippines, using elite lines incorporating AG1, AG2 and AG1+AG2 in the background of the popular varieties PSBRc82 (PSBRc82-AG1, PSBRc82-AG2, PSBRc82-AG1+AG2) and Ciherang-Sub1 (Ciherang-Sub1-AG1, Ciherang-Sub1-AG2, Ciherang-Sub1-AG1+AG2), along with the donors Kho Hlan On (for AG1) and Ma-Zhan Red (AG2) and the recipients PSBRc82 and Ciherang-Sub1. The experiment was conducted using concrete tanks in an RCBD with three replications. Dry seeds were sown in seedling trays then flooded with 10 cm water depth. Seedling survival, root and shoot growth and relative growth rate were measured. The germinating seedlings were used for assaying nonstructural carbohydrate (NSC) and ascorbate concentrations, lipid peroxidation, total phenolic concentration, reactive oxygen species and total amylase enzyme activity. Flooding reduced overall survival, though survival of AG1+AG2 introgression lines was greater than other genotypes. Soluble sugars increased, while starch concentration decreased gradually under flooding especially in the tolerant checks and AG1+AG2 introgression lines. Less lipid peroxidation and higher amylase activity, reduced-ascorbate (RAsA) and total phenolic contents (TPC) were observed in the tolerant checks and in AG1+AG2 introgression lines. Lipid peroxidation correlated negatively with ascorbate and total phenolic concentrations and with reactive oxygen species (ROS). Introgression of AG1+AG2 QTLs upregulated total amylase activity causing rapid starch degradation and increase in ascorbate and total phenolic concentrations resulting in higher germination and seedling growth in flooded soils.

Keywords: amylase, anaerobic germination, ascorbate, direct-seeded rice, flooding, lipid peroxidation

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Authors: Bader Eddin Al Asali, N. Srinivasa Reddy

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Cities are dynamic in nature and are characterized by concentration of people, infrastructure, services and markets, which offer opportunities for production and consumption. Often growth and development in urban areas is not systematic, and is directed by number of factors like natural growth, land prices, housing availability, job locations-the central business district (CBD’s), transportation routes, distribution of resources, geographical boundaries, administrative policies, etc. One sided spatial and geographical development in cities leads to the unequal spatial distribution of population and jobs, resulting in high transportation activity. City development can be measured by the parameters such as urban size, urban form, urban shape, and urban structure. Urban Size is the city size and defined by the population of the city, and urban form is the location and size of the economic activity (CBD) over the geographical space. Urban shape is the geometrical shape of the city over which the distribution of population and economic activity occupied. And Urban Structure is the transport network within which the population and activity centers are connected by hierarchy of roads. Among the urban land-use systems transportation plays significant role and is one of the largest energy consuming sector. Transportation interaction among the land uses is measured in Passenger-Km and mean trip length, and is often used as a proxy for measurement of energy consumption in transportation sector. Among the trips generated in cities, work trips constitute more than 70 percent. Work trips are originated from the place of residence and destination to the place of employment. To understand the role of urban parameters on transportation interaction, theoretical cities of different size and urban specifications are generated through building block exercise using a specially developed interactive C++ programme and land use transportation modeling is carried. The land-use transportation modeling exercise helps in understanding the role of urban parameters and also to classify the cities for their urban form, structure, and shape. Muscat the capital city of Oman underwent rapid urbanization over the last four decades is taken as a case study for its classification. Also, a pilot survey is carried to capture urban travel characteristics. Analysis of land-use transportation modeling with field data classified Muscat as a linear city with polycentric CBD. Conclusions are drawn suggestion are given for policy making for the sustainability of Muscat City.

Keywords: land-use transportation, transportation modeling urban form, urban structure, urban rule parameters

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Revanth Rallapalli

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Manually dispensing solids and powders can be difficult as it requires gradually pour and check the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in development of such devices saving time and money by reducing the number of prototypes and testing. Furthermore, this paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to trocar’s end side is done by rotation of the screw conveyor. Thus, the performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and also at the effective area within a quick turnaround time frame.

Keywords: DDPM-KTGF, gas-solids multiphase flow, screw conveyor, Unsteady

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Authors: Tracey Bone

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Deaf inmates, whose first or preferred language is a Signed Language, experience barriers to accessing the necessary two-way communication with correctional staff, and the educational and social programs that will enhance their eligibility for conditional release from the federal prison system in Canada. The development of visual content to enhance the knowledge and skill development of correctional staff is a contemporary strategy intended to significantly improve the correctional experience for deaf inmates. This presentation reports on the development of two distinct training videos created to enhance staff’s understanding of the needs of deaf inmates; one a two-part simulation of an interaction with a deaf inmate, the second an interview with a deaf academic. Part one of video one demonstrates the challenges and misunderstandings inherent in communicating across languages without a qualified sign language interpreter; the second part demonstrates the ease of communication when communication needs are met. Video two incorporates the experiences of a deaf academic to provide the cultural grounding necessary to educate staff in the unique experiences associated with being a visual language user. Lack of staff understanding or awareness of deaf culture and language must not be acceptable reasons for the inadequate treatment of deaf visual language users in federal prisons. This paper demonstrates a contemporary approach to meeting the human rights and needs of this unique and often ignored inmate subpopulation. The deaf community supports this visual approach to enhancing staff understanding of the unique needs of this population. A study of its effectiveness is currently underway.

Keywords: accommodations, American Sign Language (ASL), deaf inmates, sensory deprivation

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: Bongs Lainjo

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The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics.

Keywords: sharing program, historical data, parameters, ridership dynamics, trip duration

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Authors: Ma Yuzhe, Burra Venkata Durga Kumar

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The computer is a great invention. As people use computers more and more frequently, the demand for PCs is growing, and the performance of computer hardware is also rising to face more complex processing and operation. However, the operating system, which provides the soul for computers, has stopped developing at a stage. In the face of the high price of UNIX (Uniplexed Information and Computering System), batch after batch of personal computer owners can only give up. Disk Operating System is too simple and difficult to bring innovation into play, which is not a good choice. And MacOS is a special operating system for Apple computers, and it can not be widely used on personal computers. In this environment, Linux, based on the UNIX system, was born. Linux combines the advantages of the operating system and is composed of many microkernels, which is relatively powerful in the core architecture. Linux system supports all Internet protocols, so it has very good network functions. Linux supports multiple users. Each user has no influence on their own files. Linux can also multitask and run different programs independently at the same time. Linux is a completely open source operating system. Users can obtain and modify the source code for free. Because of these advantages of Linux, it has also attracted a large number of users and programmers. The Linux system is also constantly upgraded and improved. It has also issued many different versions, which are suitable for community use and commercial use. Linux system has good security because it relies on a file partition system. However, due to the constant updating of vulnerabilities and hazards, the using security of the operating system also needs to be paid more attention to. This article will focus on the analysis and discussion of Linux security issues.

Keywords: Linux, operating system, system management, security

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Authors: Rishabh Ambavanekar

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Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

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Authors: Cassandra Hansen, Paul Doherty, Chris Ferner, German Whitley, Holly Torpey

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Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing.

Keywords: storytelling, wildfire progression maps, volunteered geographic information, spatial and temporal

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Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

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Authors: Marvin Chibuzo Offiah, Susanne Rosenthal, Markus Borschbach

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Certain research projects in Computer Science often involve research on existing signal processing algorithms and developing improvements on them. Research budgets are usually limited, hence there is limited time for implementing the algorithms from scratch. It is therefore common practice, to use implementations provided by other researchers as a template. These are most commonly provided in a rapid development, i.e. 4th generation, programming language, usually Matlab. Rapid development is a common method in Computer Science research for quickly implementing and testing new developed algorithms, which is also a common task within agile project organization. The growing relevance of mobile devices in the computer market also gives rise to the need to demonstrate the successful executability and performance measurement of these algorithms on a mobile device operating system and processor, particularly on a smartphone. Open mobile systems such as Android, are most suitable for this task, which is to be performed most efficiently. Furthermore, efficiently implementing an interaction between the algorithm and a graphical user interface (GUI) that runs exclusively on the mobile device is necessary in cases where the project’s goal statement also includes such a task. This paper examines different proposed solutions for porting computer algorithms obtained through rapid development into a GUI-based smartphone Android app and evaluates their feasibilities. Accordingly, the feasible methods are tested and a short success report is given for each tested method.

Keywords: SMARTNAVI, Smartphone, App, Programming languages, Rapid Development, MATLAB, Octave, C/C++, Java, Android, NDK, SDK, Linux, Ubuntu, Emulation, GUI

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Authors: Feiying Wu

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Chatbots are computer programs that attempt to engage a human in a dialogue, which originated in the 1960s with MIT's Eliza. However, they have become widespread more recently as advances in language technology have produced chatbots with increasing linguistic quality and sophistication, leading to their potential to serve as a tool for Computer-Assisted Language Learning(CALL). The aim of this article is to assess the feasibility of using two chatbots, Mitsuku and CleverBot, as pedagogical tools for learning English as a second language by stimulating L2 learners with distinct English proficiencies. Speaking of the input of stimulated learners, they are measured by AntWordProfiler to match the user's expected vocabulary proficiency. Totally, there are four chat sessions as each chatbot will converse with both beginners and advanced learners. For evaluation, it focuses on chatbots' responses from a linguistic standpoint, encompassing vocabulary and sentence levels. The vocabulary level is determined by the vocabulary range and the reaction to misspelled words. Grammatical accuracy and responsiveness to poorly formed sentences are assessed for the sentence level. In addition, the assessment of this essay sets 25% lexical and grammatical incorrect input to determine chatbots' corrective ability towards different linguistic forms. Based on statistical evidence and illustration of examples, despite the small sample size, neither Mitsuku nor CleverBot is ideal as educational tools based on their performance through word range, grammatical accuracy, topic range, and corrective feedback for incorrect words and sentences, but rather as a conversational tool for beginners of L2 English.

Keywords: chatbots, CALL, L2, corrective feedback

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Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

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Authors: Luis Prada, Jose Gomez, Arlex Chaves, Julio Pedraza

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Polymeric liquids have been used in the oil industry, especially at enhanced oil recovery (EOR). From the rheological point of view, polymers have the particularity of being viscoelastic liquids. One of the most common and useful models to describe that behavior is the Upper Convected Maxwell model (UCM). The main characteristic of the polymer used in EOR process is the increase in viscosity which pushes the oil outside of the reservoir. The elasticity could contribute in the drag of the oil that stays in the reservoir. Studying the elastic effect on the oil drop at the pore scale, bring an explanation if the addition of elastic force could mobilize the oil. This research explores if the contraction and expansion of the polymer in the pore scale may increase the elastic behavior of this kind of fluid. For that reason, this work simplified the pore geometry and build two simple geometries with micrometer lengths. Using source terms with the user define a function this work introduces the UCM model in the ANSYS fluent simulator with the purpose of evaluating the elastic effect of the polymer in a contraction and expansion geometry. Also, using the Eulerian multiphase model, this research considers the possibility that extra elastic force will show a deformation effect on the oil; for that reason, this work considers an oil drop on the upper wall of the geometry. Finally, all the simulations exhibit that at the pore scale conditions exist extra vortices at UCM model but is not possible to deform the oil completely and push it outside of the restrictions, also this research find the conditions for the oil displacement.

Keywords: ANSYS fluent, interfacial fluids mechanics, polymers, pore scale, viscoelasticity

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Authors: Milton Ayoki, Edward Bbaale

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This paper analyses the relationship between innovation and employment at firm level with the objective of understanding the contribution of the different innovation strategies in fostering employment growth in Uganda. We use National Innovation Survey (micro-data of 705 Ugandan firms) for the period 2011-2014 and follow closely Harrison et al. (2014) structured approach, and relate employment growth to process innovations and to the growth of sales separately due to innovative and unchanged products. We find positive effects of product innovation on employment at firm level, while process innovation has no discernable impact on employment. Although there is evidence to suggest displacement of labour in some cases where firms only introduce new process, this effect is compensated by growth in employment from new products, which for most firms are introduced simultaneously with new process. Results suggest that source of innovation as well as size of innovating firms or end users of innovation matter for job growth. Innovation that develops from within the firm itself (user) and involving larger firms has greater impact on employment than that developed from outside or coming from within smaller firms. In addition, innovative firms are one and half times more likely to survive in the innovation driven economy environment than those that do not innovate. These results have important implications for policymakers and stakeholders in innovation ecosystem. Supporting policies need to be correctly tailored since the impacts depend on the innovation strategy (type) and characteristics and sector of the innovative firms (small, large, industry, etc.). Policies to spur investment, particularly in innovative sectors and firms with high growth potential would have long lasting effects on job creation. JEL Classification: D24, J0, J20, L20, O30.

Keywords: employment, process innovation, product innovation, Sub-Saharan Africa

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Authors: Norshima Humaidi, Saif Hussein Abdallah Alghazo

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Cybersecurity threat have become a serious issue recently, and one of the cause is because human error, which is usually constituted by carelessness, ignorance, and failure to practice cybersecurity behaviour adequately. Using a data from a quantitative survey, Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis was used to determine the factors that affect cybersecurity protective behaviour (CPB). This study adapts cybersecurity protective behaviour model by focusing on two constructs that can enhance CPB: manager’s information security competencies (MISI) and procedural information security countermeasure (PCM) awareness. Theory of leadership competencies were adapted to measure user’s perception towards competencies among security managers/leader in the organization. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each constructs were adequate in their validity individually based on their factor loading value. Moreover, each constructs are valid based on their parameter estimates and statistical significance. The quantitative research findings show that PCM awareness strongly influences CPB compared to MISI. Meanwhile, MISI was significantlyPCM awarenss. This study believes that the research findings can contribute to human behaviour in IS studies and are particularly beneficial to policy makers in improving organizations’ strategic plans in information security, especially in this new era. Most organizations spend time and resources to provide and establish strategic plans of information security; however, if employees are not willing to comply and practice information security behaviour appropriately, then these efforts are in vain.

Keywords: cybersecurity, protection behaviour, information security, information security competencies, countermeasure awareness

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Authors: Li-Jia Chiu

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The purpose of this study is to integrate the content of professional ethics curriculum into life education. This course is a required course for the third-year students of the university. The curriculum is based on professional ethics, which can help students gain insights into a conceptual understanding of professional theory, learning the meaning and the value of life. This study enhances students' attitude toward learning through multi-teaching methods. It takes ‘professionalism’ as the subject of discussion. Additionally, the course combines the connotation and issues of the student's career development. Using the world cafe discussion method, students can think about the role of the future career, and inspire students to integrate their career development and life value reflection and connection. This study recruited the third-year undergraduate students as samples to collect data. This study was conducted in the course of the fall semester in 2016 for thematic discussions, classroom observations, course study forms, coursework, and results in publication reports, etc. The researcher conducted induction data analysis to reflect the practice and reflection of the course. The subjects included 117 students from two classes, including 54 male and 63 female students. The findings of this study comprised the following two parts: the student’s learning and teacher’s teaching reflection. The students’ gains were that: 1) The curriculum design is different from that of other subjects; 2) The curriculum is highly interactive with teachers and classmates; 3) These students are willing to actively participate and share ideas in group discussions; 4 ) They thought the possibility of further discussions with other groups of students through table-to-table discussions; 5) They experienced the respect from other students in the learning process and their appreciation of other students in the same group. The instruction reflections were as follows: 1) Students learned to get link to the value of life and future development through topical discussions; 2) After the main course design guided through gradual guidance, the students’ psychology reached a certain degree of cognition, and further themes then added would cause more sensuous learning effects; 3) Combining students’ expertise in drawing in this department (digital media design department) into curriculum design is effective in stimulating learning motivation and sense of accomplishment; 4) In order to compare and explore learning benefits, future researches are recommended to conduct the similar studies with different departments. Finally, the researcher looks forward to providing research results and findings to the related curriculum teachers as a reference for practical curriculum planning and teaching methods.

Keywords: life education, World Cafe, professional ethics, professionalism

Procedia PDF Downloads 138

Authors: Wael Elsaady, S. Olutunde Oyadiji, Adel Nasser

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The non-linear flow characteristics of magnetorheological (MR) fluids in MR dampers are studied via a coupled numerical approach that incorporates a two-phase flow model. The approach couples the Finite Element (FE) modelling of the damper magnetic circuit, with the Computational Fluid Dynamics (CFD) analysis of the flow field in the damper. The two-phase flow CFD model accounts for the effect of fluid compressibility due to the presence of liquid and gas in the closed domain of the damper. The dynamic mesh model included in ANSYS/Fluent CFD solver is used to simulate the movement of the MR damper piston in order to perform the fluid excitation. The two-phase flow analysis is studied by both Volume-Of-Fluid (VOF) model and mixture model that are included in ANSYS/Fluent. The CFD models show that the hysteretic behaviour of MR dampers is due to the effect of fluid compressibility. The flow field shows the distributions of pressure, velocity, and viscosity contours. In particular, it shows the high non-Newtonian viscosity in the affected fluid regions by the magnetic field and the low Newtonian viscosity elsewhere. Moreover, the dependence of gas volume fraction on the liquid pressure inside the damper is predicted by the mixture model. The presented approach targets a better understanding of the complicated flow characteristics of viscoplastic fluids that could be applied in different applications.

Keywords: viscoplastic fluid, magnetic FE analysis, computational fluid dynamics, two-phase flow, dynamic mesh, user-defined functions

Procedia PDF Downloads 174

Authors: Roberta Mugellesi Dow

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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

Procedia PDF Downloads 133

Authors: Ayla Hoeta

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The focus of this research is mahi Maramataka, ‘the practices of Maramataka’ as a traditional and evolving knowledge system and its connection to whaanau oranga (wellbeing) and healing. Centering kaupapa Maaori methods and knowledge this research will explore how Maramataka can be used as a tool for oranga and healing for whaanau to engage with different environments aligned with Maramataka flow and optimal time based on the environment. Maramataka is an ancestral lunar environmental knowledge system rooted within korero tuku iho, Maaori creation stories, dating back to the beginning of time. The significance of Maramataka is the ancient environmental knowledge and the connecting energy flow of mauri (life force) between whenua (land), moana (ocean) and rangi (sky). The lunar component of the Maramataka is widely understood and highlights the different phases of the moon. Each moon phase is named with references to puurakau stories and environmental and ecological information. Marama, meaning moon and taka, meaning cycle, is used as a lunar and environmental calendar. There are lunar phases that are optimal for specific activities, such as the Tangaroa phase, a time of abundance and productivity and ocean-based activities like fishing. Other periods in the Maramataka, such as Rakaunui (full moon), connect the highest tides and highest energy of the lunar cycle, ideal for social, physical activity and particularly planting. Other phases like Tamatea are unpredictable whereas Whiro (new moon/s) is reflective, deep and cautious during the darkest nights. Whaanau, particularly in urban settings have become increasingly disconnected from the natural environment, the Maramataka has become a tool that they can connect to which offers an alternative to dominant perspectives of health and is an approach that is uniquely Maaori. In doing so, this research will raise awareness of oranga or lack of oranga, and lived experience of whaanau in Tamaki Makaurau - Aotearoa, on a journey to revival of Maramataka and healing. The research engages Hautu Waka as a methodology using the methods of ancient kaupapa Māori practises based on wayfinding and attunement with the natural environment. Using ancient ways of being, knowing, seeing and doing the Hautu Waka will centre kaupapa Maaori perspectives to process design, reflection and evaluation. The methods of Hautu Waka consists of five interweaving phases, 1) Te Rapunga (the search) in infinite potential, 2) Te Kitenga (the seeing), observations of and attunement to tohu 3) te whainga (the pursuit) and deeply exploring key tohu 4) te whiwhinga (the acquiring), of knowledge and clearer ideas, 5) Te Rawenga (the celebration), reflection and acknowledgement of the journey and achievements. This research is an expansion from my creative practices across whaanau-centred inquiry, to understand the benefits of Maramataka and how it can be embodied and practised in a modern-day context to support oranga and healing. Thus, the goal is to work with kaupapa Maaori methodologies to authenticate as a Maaori practitioner and researcher and allow an authentic indigenous approach to the exploration of Maramataka and through a kaupapa Maaori lens.

Keywords: maramataka (Maaori calendar), tangata (people), taiao (environment), whenua (land), whaanau (family), hautu waka (navigation framework)

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Authors: Keshav Raj Acharya, Thakur Silwal, Neelam C. Poudyal

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Buffer zones, the peripheral areas around the national parks and wildlife reserves, are available for the purpose of benefitting the local inhabitants by providing forest products for subsistence needs of basic forest products outside the protected areas. The forest area within the buffer zone has been managed as a buffer zone community forest (BZCF) for the last 25 years after the approval of the buffer zone management regulation 1996. With a case study of select BZCF in Bardia National Park, this study aims to analyze whether the benefit provided by BZCF is equally available to poor users among other socioeconomic classes of the users. The findings are based on the analysis of cross-sectional data involving household surveys (n=305) and key informants’ interviews (n=10) as well as office records available at different 5 buffer zone community forest user groups offices. Results indicate that despite the provisions of subsidized rates for poor; poor households were more deprived due to higher forest products price particularly, the timber price in buffer zone. Evidence also indicate that due to the increased forest coverage, the incidence of wildlife damage has also increased and impacted the poor more due to lack of land ownership as well as limited alternatives. Clear community forest management guidelines with equitable benefit sharing and compensatory mechanisms to the users of poor socioeconomic class have been identified as a solution to increase the benefit to poor users in BZCFUGs.

Keywords: crop depredation, forest products, users, wellbeing ranking

Procedia PDF Downloads 51

Authors: Hiroaki Fukuda

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This paper shows a concurrent development process for modern web application, called Rich Internet Application (RIA), and describes its effect using a non-trivial application development. In the last years, RIAs such as Ajax and Flex have become popular based mainly on high-speed network. RIA provides sophisticated interfaces and user experiences, therefore, the development of RIA requires two kinds of engineer: a developer who implements business logic, and a designer who designs interface and experiences. Although collaborative works are becoming important for the development of RIAs, shared resources such as source code make it difficult. For example, if a design of interface is modified after developers have finished business logic implementations, they need to repeat the same implementations, and also tests to verify application’s behavior. MVC architecture and Object-oriented programming (OOP) enables to dividing an application into modules such as interfaces and logic, however, developers and/or designers have to write pieces of code (e.g., event handlers) that make these modules work as an application. On the other hand, Aspect-oriented programming (AOP) is ex- pected to solve complexity of application software development nowadays. AOP provides methods to separate crosscutting concerns that are scattered pieces of code from primary concerns. In this paper, we provide a concurrent development process for RIAs by introducing AOP concept. This process makes it possible to reduce shared resources between developers and designers, therefore they can perform their tasks concurrently. In addition, we describe experiences of development for a practical application using our proposed development process to show its availability.

Keywords: aspect-oriented programming, concurrent, development process, rich internet application

Procedia PDF Downloads 301

Authors: Sharifah I. N. A. Syed Azmi, Nazarina Mohd Nasir

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The Billing & Customer Relationship Management (BCRM) project is an important enabler towards realizing customer experience transformation. It involves technological shifts for future scalability, revision of multiple business processes and adoption of change by the users and impacted employees. This massive transition, if not managed properly, may result in the decline of business performance due to productivity drop. Organizational change management is an essential element in BCRM project implementation to ensure the system is well understood and embraced by all stakeholders. In order to move impacted employees from unaware state or denial mode to full-acceptance mindset and committing themselves in using the new system, their involvement in the whole change process starting from the initial stage is imperative. Through the BCRM Change Management Plan, a holistic approach was taken whereby the strategy and program for five key components namely executive sponsorship, continuous communication, process change readiness, organizational readiness and individual readiness were all carefully established. Roles of the project sponsor, change agents, change ambassadors and community of practice (CoP) were clearly defined in gaining high commitment and support across the entire organization. Continuous communication and engagement initiatives throughout project implementation have been carried out to reach all stakeholders. The business readiness was constantly monitored and assessed including effectiveness of end-user training, thorough review of process documentation and completion of roles realignment exercise.

Keywords: BCRM, change management, organizational change, transformation project

Procedia PDF Downloads 141

Authors: Chevon Fernando, Banuka Athuraliya

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The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies.

Keywords: personalized learning, study planner, time management, calendar integration

Procedia PDF Downloads 48

Authors: P. Vindin, R. Cordier, N. J. Wilson, H. Lee

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Engagement in community-based activities such as education, employment, and social relationships can improve the quality of life for individuals with Autism Spectrum Disorder (ASD). Community mobility is vital to attaining independence for individuals with ASD. Learning to drive and gaining a driver’s license is a critical link to community mobility; however, for individuals with ASD acquiring safe driving skills can be a challenging process. Issues related to anxiety, executive function, and social communication may affect driving behaviours. Driving training and education aimed at addressing barriers faced by learner drivers with ASD can help them improve their driving performance. A multi-site randomized controlled trial (RCT) was conducted to evaluate the effectiveness of an autism-specific driving training intervention for improving the on-road driving performance of learner drivers with ASD. The intervention was delivered via a training manual and interactive website consisting of five modules covering varying driving environments starting with a focus on off-road preparations and progressing through basic to complex driving skill mastery. Seventy-two learner drivers with ASD aged 16 to 35 were randomized using a blinded group allocation procedure into either the intervention or control group. The intervention group received 10 driving lessons with the instructors trained in the use of an autism-specific driving training protocol, whereas the control group received 10 driving lessons as usual. Learner drivers completed a pre- and post-observation drive using a standardized driving route to measure driving performance using the Driving Performance Checklist (DPC). They also completed anxiety, executive function, and social responsiveness measures. The findings showed that there were significant improvements in driving performance for both the intervention (d = 1.02) and the control group (d = 1.15). However, the differences were not significant between groups (p = 0.614) or study sites (p = 0.842). None of the potential moderator variables (anxiety, cognition, social responsiveness, and driving instructor experience) influenced driving performance. This study is an important step toward improving community mobility for individuals with ASD showing that an autism-specific driving training intervention can improve the driving performance of leaner drivers with ASD. It also highlighted the complexity of conducting a multi-site design even when sites were matched according to geography and traffic conditions. Driving instructors also need more and clearer information on how to communicate with learner drivers with restricted verbal expression.

Keywords: autism spectrum disorder, community mobility, driving training, transportation

Procedia PDF Downloads 132

Authors: Xu Jie

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As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decision-making problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security) by modeling the multi-job collaborative cryptographic service scheduling problem as a multi-objective optimized job flow scheduling problem and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real-time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing and effectively solves the problem of complex resource scheduling in cryptographic services.

Keywords: cloud computing, cryptography on-demand service, reinforcement learning, workflow scheduling

Procedia PDF Downloads 12