Search results for: principals' emotionally intelligent behaviours

Authors: Francisco Toledo-Castillo, Pilar Peiró-Torres, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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The communication presented is about tasks that are been developed in the research project “safeRoute”, “Information safety system for professional road driving” (IPT-2012-110-370000). This R&D project was proposed by the consortium formed by Fagor Electronica la SEU 3 and the University of Valencia to the Ministry of Economy and Competitiveness, which approved it inside the INNPACTO subprogramme grants. Through this type of calls, the Ministry promote the innovative capacity of the Spanish companies and turn on the mechanism for competing internationally. With this kind of calls, private investments for technological and industrial development join their R & D resources with public entities to implement innovative project that could have an international exposure. Thus INNPACTO subprogramme promotes the creation of research projects with public-private partnerships that create exploitable final products. The “safeRoute” Project pretends develop a tool to help to make more safety the travels of commercial transport vehicles of goods and passengers. To achieve its objectives, the project is focused in three main lines of research: vehicle safety, the safety of the roads that they are using, and the safety which drivers do their job, their behaviour while they are driving. To improve safety, the project gives information about these three factors to all people that are involved in the safety of the professional transport. These three factors have influence to the occurrence of traffic accidents, thanks to the information provided and treated about these factors, we can achieve a significant reduction in occupational accidents in the transport sector. SafeRoute provide information about routes, vehicles, and driver behaviours, and in this manner pretends provide to transport companies a tool which could result in a safer driving results and could reduce their costs related to traffic accidents of their vehicles, in that way, this tool could help them to be more competitive, and give a more reliable service. This paper will focus mainly on the information about routes that drivers use to travel in their professional work, and how the researchers of this project have catalogued and evaluated these routes, and finally how that information will be provided to users.

Keywords: driver support systems, professional drivers, road safety, safeRoute

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Authors: Zelal Polat, Şebnem Harsa, Semra Ülkü

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Lactic acid exists in nature optically in two forms, L(+), D(-)-lactic acid, and has been used in food, leather, textile, pharmaceutical and cosmetic industries. Moreover, L(+)-lactic acid constitutes the raw material for the production of poly-L-lactic acid which is used in biomedical applications. Microbially produced lactic acid was aimed to be recovered from the fermentation media efficiently and economically. Among the various downstream operations, ion exchange chromatography is highly selective and yields a low cost product recovery within a short period of time. In this project, Lactobacillus casei NRRL B-441 was used for the production of L(+)-lactic acid from whey by fermentation at pH 5.5 and 37°C that took 12 hours. The product concentration was 50 g/l with 100% L(+)-lactic acid content. Next, the suitable resin was selected due to its high sorption capacity with rapid equilibrium behavior. Dowex marathon WBA, weakly basic anion exchanger in OH form reached the equilibrium in 15 minutes. The batch adsorption experiments were done approximately at pH 7.0 and 30°C and sampling was continued for 20 hours. Furthermore, the effect of temperature and pH was investigated and their influence was found to be unimportant. All the adsorption/desorption experiments were applied to both model lactic acid and biomass free fermentation broth. The ion exchange equilibria of lactic acid and L(+)-lactic acid in fermentation broth on Dowex marathon WBA was explained by Langmuir isotherm. The maximum exchange capacity (qm) for model lactic acid was 0.25 g La/g wet resin and for fermentation broth 0.04 g La/g wet resin. The equilibrium loading and exchange efficiency of L(+)-lactic acid in fermentation broth were reduced as a result of competition by other ionic species. The competing ions inhibit the binding of L(+)-lactic acid to the free sites of ion exchanger. Moreover, column operations were applied to recover adsorbed lactic acid from the ion exchanger. 2.0 M HCl was the suitable eluting agent to recover the bound L(+)-lactic acid with a flowrate of 1 ml/min at ambient temperature. About 95% of bound L(+)-lactic acid was recovered from Dowex marathon WBA. The equilibrium was reached within 15 minutes. The aim of this project was to investigate the purification of L(+)-lactic acid with ion exchange method from fermentation broth. The additional goals were to investigate the end product purity, to obtain new data on the adsorption/desorption behaviours of lactic acid and applicability of the system in industrial usage.

Keywords: fermentation, ion exchange, lactic acid, purification, whey

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Authors: Safa Gharbi, Hayfa Zgaya, Nesrine Zoghlami, Slim Hammadi, Cyril De Barbarin, Laurent Vinatier, Christiane Coupier

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Increasing productivity and quality of service, improving the working comfort and ensuring the efficiency of all processes are important challenges for every warehouse. The order picking is recognized to be the most important and costly activity of all the process in warehouses. This paper presents a new approach using Augmented Reality (AR) in the field of logistics. It aims to create a Head-Up Display (HUD) interface with a Warehouse Management System (WMS), using AR glasses. Integrating AR technology allows the optimization of order picking by reducing time of picking process, increasing the efficiency and delivering quickly. The picker will be able to access immediately to all the information needed for his tasks. All the information is displayed when needed in the field of vision (FOV) of the operator, without any action requested from him. These research works are part of the industrial project RASL (Réalité Augmentée au Service de la Logistique) which gathers two major partners: the LAGIS (Laboratory of Automatics, Computer Engineering and Signal Processing in Lille-France) and Genrix Group, European leader in warehouses logistics, who provided his software for implementation, and his logistics expertise.

Keywords: Augmented Reality (AR), logistics and optimization, Warehouse Management System (WMS), Head-Up Display (HUD)

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Authors: Tacho Rubby Kong

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Community health workers’ performances are known to influence members’ behaviours and practices while translating policies into service delivery. However, little remains known about the extent to which this remains true within interventions aimed at addressing malaria burden in low-resource settings like Cameroon. The objective of this study was to examine the health workers’ performance and their influence on the adoption of strategies to address the malaria burden at a subnational level health system in Cameroon. A qualitative exploratory design was adopted on a purposively selected sample of 18 key informants. The study was conducted in Konye health district among sub-national health systems, managers, health facility in-charges, and frontline community health workers. Data was collected using semi-structured interview guides in a face-to-face interview with respondents. The analysis adopted a thematic approach utilising journals, credible authors, and peer review articles for data management. Participants acknowledged that workplace networks were influential during the implementation of policies to address malaria. The influence exerted was in form of linkage with other services, caution, and advice regarding strict adherence to policy recommendations, perhaps reflective of the level of trust in providers’ ability to adhere to policy provisions. At the district health management level and among non-state actors, support in perceived areas of weak performance in policy implementation was observed. In addition, timely initiation of contact and subsequent referral was another aspect where community health workers exerted influence while translating policies to address the malaria burden. While the level of support from among network peers was observed to influence community health workers’ adoption and implementation of strategies to address the malaria burden, different mechanisms triggered subsequent response and level of adherence to recommended policy aspects. Drawing from the elicited responses, it was infer that community health workers’ performance influence the direction and extent of success in policy implementation to address the malaria burden at the subnational level.

Keywords: subnational, community, malaria, strategy

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Authors: Rabaa Tlili Yaakoubi, Hind Nakouri, Olivier Blanpain

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of the CARDIO project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 40 to 100%. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 60% of total volume rejected to the natural environment and of 80 % in the number of discharges.

Keywords: RTC, paradigm, optimization, automation

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Authors: Jyh-Cherng Gu, Ming-Ta Yang, Chao-Fong Yan, Hsin-Yung Chung, Yung-Ruei Chang, Yih-Der Lee, Chen-Min Chan, Chia-Hao Hsu

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There are a number of distributed generations (DGs) installed in microgrid, which may have diverse path and direction of power flow or fault current. The overcurrent protection scheme for the traditional radial type distribution system will no longer meet the needs of microgrid protection. Integrating the intelligent electronic device (IED) and a supervisory control and data acquisition (SCADA) with IEC 61850 communication protocol, the paper proposes a microgrid protection management system (MPMS) to protect power system from the fault. In the proposed method, the MPMS performs logic programming of each IED to coordinate their tripping sequence. The GOOSE message defined in IEC 61850 is used as the transmission information medium among IEDs. Moreover, to cope with the difference in fault current of microgrid between grid-connected mode and islanded mode, the proposed MPMS applies the group setting feature of IED to protect system and robust adaptability. Once the microgrid topology varies, the MPMS will recalculate the fault current and update the group setting of IED. Provided there is a fault, IEDs will isolate the fault at once. Finally, the Matlab/Simulink and Elipse Power Studio software are used to simulate and demonstrate the feasibility of the proposed method.

Keywords: IEC 61850, IED, group Setting, microgrid

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: artificial neural networks, digital image processing, pattern recognition, phytosanitary

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Authors: Song Shengli, Tan Zhitao, Li Qing, Fang Husheng, Ye Qing, Zhang Xinglong

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Lower extremity power-assisted exoskeleton (LEPEX) is a kind of wearable electromechanical integration intelligent system, walking in synchronization with the wearer, which can assist the wearer walk by means of the driver mounted in the exoskeleton on each joint. In this paper, dynamic analysis and design of the LEPEX are performed. First of all, human walking process is divided into single leg support phase, double legs support phase and ground collision model. The three kinds of dynamics modeling is established using the Lagrange method. Then, the flat walking and climbing stairs dynamic information such as torque and power of lower extremity joints is derived for loading 75kg according to scholar Stansfield measured data of flat walking and scholars R. Riener measured data of climbing stair respectively. On this basis, the joint drive way in the sagittal plane is determined, and the structure of LEPEX is designed. Finally, the designed LEPEX is simulated under ADAMS by using a person’s joint sports information acquired under flat walking and climbing stairs. The simulation result effectively verified the correctness of the structure.

Keywords: kinematics, lower extremity exoskeleton, simulation, structure

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Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

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Authors: Joanne Danker, Iva Strnadová, Therese Cumming

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As a consequence of the increased evidence of the bi-directional relationship between student well-being and positive educational outcomes, there has been a surge in the number of research studies dedicated to understanding the notion of student well-being and the ways to enhance it. In spite of these efforts, the concept of student well-being remains elusive. Additionally, studies on student well-being mainly consulted adults' perspectives and failed to take into account students' views, which if considered, could contribute to a clearer understanding of the complex concept of student well-being. Furthermore, there is a lack of studies focusing on the well-being of students with autism spectrum disorder (ASD), and these students continue to fare worse in post-school outcomes as compared to students without disabilities, indicating a significant gap in the current research literature. Findings from research conducted on students without disabilities may not be applicable to students with ASD as their educational experiences may differ due to the characteristics associated with ASD. Thus, the purpose of this study was to explore how students with ASD, their parents, and teachers conceptualise student well-being. It also aims to identify the barriers and assets of the well-being of these students. To collect data, 19 teachers and 11 parents participated in interviews while 16 high school students with ASD were involved in a photovoice project regarding their well-being in school. Grounded theory approaches such as open and axial coding, memo-writing, diagramming, and making constant comparisons were adopted to analyse the data. All three groups of participants conceptualised student well-being as a multidimensional construct consisting of several domains. These domains were relationships, engagement, positive/negative emotions, and accomplishment. Three categories of barriers were identified. These were environmental, attitudes and behaviours of others, and impact of characteristics associated with ASD. The identified internal assets that could contribute to student well-being were acceptance, resilience, self-regulation, and ability to work with others. External assets were knowledgeable and inclusive school community, and having access to various school programs and resources. It is crucial that schools and policymakers provide ample resources and programs to adequately support the development of each identified domain of student well-being. This could in turn enhance student well-being and lead to more successful educational outcomes for students with ASD.

Keywords: autism spectrum disorder, grounded theory approach, school experiences, student well-being

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Authors: P. Nafisi Poor, P. Javid

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Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

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Authors: Manahil Alfuraydan, Jodie Croxall, Lisa Hurt, Mike Kerr, Sinead Brophy

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Autism Spectrum Disorder (ASD) is a developmental condition characterised by impairment in terms of social communication, social interaction, and a repetitive or restricted pattern of interest, behaviour, and activity. There is a significant delay between seeking help and a confirmed diagnosis of ASD. This may result in delay in receiving early intervention services, which are critical for positive outcomes. The long wait times also cause stress for the individuals and their families. Telehealth potentially offers a way of improving the diagnostic pathway for ASD. This review of the literature aims to examine which telehealth approaches have been used in the diagnosis and assessment of autism in children and adults, whether they are feasible and acceptable, and how they compare with face-to-face diagnosis and assessment methods. A comprehensive search of following databases- MEDLINE, CINAHL Plus with Full text, Business Sources Complete, Web of Science, Scopus, PsycINFO and trail and systematic review databases including Cochrane Library, Health Technology Assessment, Database of Abstracts and Reviews of Effectiveness and NHS Economic Evaluation was conducted, combining the terms of autism and telehealth from 2000 to 2018. A total of 10 studies were identified for inclusion in the review. This review of the literature found there to be two methods of using telehealth: (a) video conferencing to enable teams in different areas to consult with the families and to assess the child/adult in real time and (b) a video upload to a web portal that enables the clinical assessment of behaviours in the family home. The findings were positive, finding there to be high agreement in terms of the diagnosis between remote methods and face to face methods and with high levels of satisfaction among the families and clinicians. This field is in the very early stages, and so only studies with small sample size were identified, but the findings suggest that there is potential for telehealth methods to improve assessment and diagnosis of autism used in conjunction with existing methods, especially for those with clear autism traits and adults with autism. Larger randomised controlled trials of this technology are warranted.

Keywords: assessment, autism spectrum disorder, diagnosis, telehealth

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Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

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Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: gripper, haptic, stiffness, robotic

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Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

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In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

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Authors: Muhammad Asim, Mehvish Amjad

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Background: Less than half of women in South Asia (SA) use any modern contraceptive method which leads to a huge burden of unintended pregnancies, unsafe abortions, maternal deaths, and socioeconomic loss. Women empowerment plays a pivotal role in improving various health seeking behaviours, including contraceptive use. The objective of this study to explore the association between women's empowerment and modern contraceptive, among rich and poor segment of population in SA. Methods: We used the most recent, large-scale, demographic health survey data of five South Asian countries, namely Afghanistan, Pakistan, Bangladesh, India, and Nepal. The outcome variable was the current use of modern contraceptive methods. The main exposure variable was a combination (interaction) of socio-economic status (SES) and women’s level of empowerment (low, medium, and high), where SES was bifurcated into poor and rich; and women empowerment was divided into three categories: decision making, attitude to violence and social independence. Moreover, overall women empowerment indicator was also created by using three dimensions of women empowerment. We applied both descriptive statistics and multivariable logistic regression techniques for data analyses. Results: Most of the women possessed ‘medium’ level of empowerment across South Asian Countries. The lowest attitude to violence empowerment was found in Afghanistan, and the lowest social independence empowerment was observed in Bangladesh across SA. However, Pakistani women have the lowest decision-making empowerment in the region. The lowest modern contraceptive use (22.1%) was found in Afghanistan and the highest (53.2%) in Bangladesh. The multivariate results depict that the overall measure of women empowerment does not affect modern contraceptive use among poor and rich women in most of South Asian countries. However, the decision-making empowerment plays a significant role among both poor and rich women to use modern contraceptive methods across South Asian countries. Conclusions: The effect of women’s empowerment on modern contraceptive use is not consistent across countries, and among poor and rich segment of population. Of the three dimensions of women’s empowerment, the autonomy of decision making in household affairs emerged as a stronger determinant of mCPR as compared with social independence and attitude towards violence against women.

Keywords: women empowerment, modern contraceptive use, South Asia, socio economic status

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Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

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Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

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Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Catharina Dwi Astuti Depari, Gregorius Agung Setyonugroho

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In concern for human safety, living in disaster-prone areas is twofold: it is profoundly cataclysmic yet perceptibly contributive. This paradox could be identified in Kalitengah Lor Sub-village community who inhabit Mount Merapi’s most hazardous area, putting them to the highest exposure to eruptions’ cataclysmic impacts. After the devastating incident in 2010, through the Action Plan for Rehabilitation and Reconstruction, the National Government with immediate aid from humanitarian agencies initiated a relocation program by establishing nearly 2,613 temporary shelters throughout the mountain’s region. The problem arose as some of the most affected communities including those in Kalitengah Lor Sub-village, persistently refused to relocate. The obnoxious experience of those living in temporary shelters resulted from the program’s failure to support a long-term living was assumed to instigate the rejection. From the psychological standpoint, this phenomenon reflects the emotional bond between the affected communities with their former dwellings. Regarding this, the paper aims to reveal the factors influencing the emotional attachment of Kalitengah Lor community to their former dwellings including the dwellings’ spatial design transformation prior and post the eruption in 2010. The research adopted Likert five scale-questionnaire comprising a wide range of responses from strongly agree to strongly disagree. The responses were then statistically measured, leading to consensus that provides bases for further interpretations toward the local’s characteristics. Using purposive unit sampling technique, 50 respondents from 217 local households were randomly selected. Questions in the questionnaire were developed with concerns on the aspects of place attachment concept: affection, cognitive, behavior, and perception. Combined with quantitative method, the research adopted diachronic method which was aimed to analyze the spatial design transformation of each dwelling in relation to the inhabitant’s daily activities and personal preferences. The research found that access to natural resources like sand mining, agricultural farms and wood forests, social relationship and physical proximity from house to personal asset like cattle shed, are the dominant factors encouraging the locals to emotionally attached to their former dwellings. Consequently, each dwelling’s spatial design is suffered from changes in which the current house is typically larger in dimension and the bathroom is replaced by public toilet located outside the house’s backyard. Relatively unchanged, the cattle shed is still located in front of the house, the continuous visual relationship, particularly between the living and family room, is maintained, as well as the main orientation of the house towards the local street.

Keywords: diachronic method, former dwellings, local’s characteristics, place attachment, spatial design transformation

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Johnson-Egemba Helen Amaka

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Music is emotional in the sense that it controls people’s feelings. The way and manner people react to music at a point in time depend on the type of music that is playing. Music can make someone to march or dance, to cry or laugh, to be happy or sad, to fight or make peace and so on. It therefore makes someone o exhibit some kind of behaviours, either positive or negative. Even dangerous animals have been found to be controlled by music. In the psychiatric homes, mad people are always found to be dancing to music. During funeral ceremony, music singing and dancing are sources of comfort to the bereaved. As a background to the study, Tarok ethnic group in Plateau State was used. The Tarok comprise of Langtang North and South Local Government Areas. The ethnic group of Tarok integrates music in almost all the activities of their lives. A total of six (6) types of folk songs were identified. These songs range from marriages, funeral, royalty, togetherness, war, rituals, festivals, and farming. This paper points out the significance of basic responsiveness of the Tarok people towards the folk songs, their reaction generally whether positive or negative. The methods of data collection employed in this work include oral interview approach, recording of various types of Tarok folk songs, consulting of journals, magazines and textbooks. The researcher used oral interview as her primary source of information which is found to be the most effective procedure in carrying out this task. The songs were textually analyzed with a view to unveiling their meanings, thought processes, and conveying their direction and functions within the context of their rendition. The major findings of the study are that music in Tarok culture covers the physical, mental, emotional and social experiences. The physical aspect is the motor skills, which include dancing and demonstration of the songs. The mental experiences are intellectual levels which include construction and manufacturing of musical instruments, composing songs, teaching and learning etc. Furthermore, this research provided in addition to musical activities, the literature, history and culture of the Tarok communities.

Keywords: cultural, music, practice, responsiveness

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Nilanthi Ratnayake, Wen-Ling Liu

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Prior research indicates an increasing gap between the skills and capabilities of graduates in the contemporary workplace across the globe. The challenge of addressing this issue primarily lies on the hands of higher education institutes/universities. In particular, surveys of UK employers and retailers found that soft skills including communication, numeracy, teamwork, confidence, analytical ability, digital/IT skills, business sense, language, and social skills are highly valued by graduate employers, and in achieving this, there are various assessed and non-assessed learning exercises have already been embedded into the university curriculum. To this end, this research study aims to explore the reflections of postgraduate student participation in a live commercial project (i.e. designing an advertising campaign for open days, summer school etc.) implemented with the intention of offering a transformative experience by deploying this project. Qualitative research methodology has been followed in this study, collecting data from three types of target audiences; students, academics and employers via a series of personal interviews and focus group discussions. Recorded data were transcribed, entered into NVIVO, and analysed using meaning condensation and content analysis. Students reported that they had a very positive impact towards improving self-efficacy, especially in relation to soft skills and confidence in seeking employment opportunities. In addition, this project has reduced cultural barriers for international students in general communications. Academic staff and potential employers who attended on the presentation day expressed their gratitude for offering a lifelong experience for students, and indeed believed that these type of projects contribute significantly to enhance skills and capabilities of students to cater the demands of employers. In essence, key findings demonstrate that an integration of knowledge-based skills into a live commercial project facilitate individuals to make the transition from education to employment in terms of skills, abilities and work behaviours more effectively in comparison to some other activities/assuagements that are currently in place in higher education institutions/universities.

Keywords: soft skills, commercially live project, higher education, student participation

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Authors: Jane E. Hill

Abstract:

Sexual, physical, or emotional abuses are behaviors used by one person in a relationship or within a family unit to control the other person. Physical abuse can consist of, but not limited to hitting, pushing, and shoving. Sexual abuse is unwanted or forced sexual activity on a person without their consent. Abusive behaviors include intimidation, manipulation, humiliation, isolation, frightening, terrorizing, coercing, threatening, blaming, hurting, injuring, or wounding another individual. Although emotional, psychological and financial abuses are not criminal behaviors, they are forms of abuse and can leave emotional scars on their victim. The purpose of this literature review research was to examine characteristics of female offenders, past abuse, and pathways to offending. The question that guided this research: does past abuse influence recidivism? The theoretical foundation used was relational theory by Jean Baker Miller. One common feature of female offenders is abuse (sexual, physical, or verbal). Abuse can cause mental illnesses and substance abuse. The abuse does not directly affect the women's recidivism. However, results indicated the psychological and maladaptive behaviors as a result of the abuse did contribute to indirect pathways to continue offending. The female offenders’ symptoms of ongoing depression, anxiety, and engaging in substance abuse (self medicating) did lead to the women's incarceration. Using the childhood victimization model as the treatment approach for women's mental illness and substance abuse disorders that were a result from history of child abuse have shown success. With that in mind, if issues surrounding early victimization are not addressed, then the women offenders may not recover from their mental illness or addiction and are at a higher risk of reoffending. However, if the women are not emotionally ready to engage in the treatment process, then it should not be forced onto them because it may cause harm (targeting prior traumatic experiences). Social capital is family support and sources that assist in helping the individual with education, employment opportunities that can lead to success. Human capital refers to internal knowledge, skills, and capacities that help the individual act in new and appropriate ways. The lack of human and social capital is common among female offenders, which leads to extreme poverty and economic marginalization, more often in frequent numbers than men. In addition, the changes in welfare reform have exacerbated women’s difficulties in gaining adequate-paying jobs to support themselves and their children that have contributed to female offenders reoffending. With that in mind, one way to lower the risk factor of female offenders from reoffending is to provide them with educational and vocational training, enhance their self-efficacy, and teach them appropriate coping skills and life skills. Furthermore, it is important to strengthen family bonds and support. Having a supportive family relationship was a statistically significant protective factor for women offenders.

Keywords: characteristics, childhood victimization model, female offenders, treatment

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints

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Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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The optimal construction design used during the execution of a construction project is a key factor in determining high productivity and customer satisfaction, however, this management process sometimes is carried out without care and the systematic method that it deserves, bringing negative consequences. This study proposes a knowledge management (KM) approach that will enable the intelligent use of experienced and acknowledged engineers to improve the management of construction design works for a project. Then a knowledge-based application to support this decision-making process is proposed and described. To define and design the system for the application, semi-structured interviews were conducted within five construction consulting organizations with the purpose of studying the way that the method’ optimizing process is implemented in practice and the knowledge supported with it. A system of an optimizing construction design works (OCDW) based on knowledge was developed then validated with construction experts. The OCDW was liked as a valuable tool for construction design works’ optimization, by supporting organizations to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The benefits are described as provided by the performance support system, reducing costs and time, improving product design quality, satisfying customer requirements, expanding the brand organization.

Keywords: optimizing construction design work, construction consultant organization, knowledge management, knowledge-based application

Procedia PDF Downloads 130