Search results for: adaptive facade
371 The Determinant Factors of Technology Adoption for Improving Firm’s Performance; Toward a Conceptual Model
Authors: Zainal Arifin, Avanti Fontana
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Considering that TOE framework is the most useful instrument for studying technology adoption in firm context, this paper will analyze the influence of technological, organizational and environmental (TOE) factors to the Dynamic capabilities (DCs) associated with technology adoption strategy for improving the firm’s performance. Focusing on the determinant factors of technology adoption at the firm level, the study will contribute to the broader study of resource base view (RBV) and dynamic capability (DC). There is no study connecting directly the TOE factors to the DCs, this paper proposes technology adoption as a functional competence/capability which mediates a relationship between technology adoptions with firm’s performance. The study wants to show a conceptual model of the indirect effects of DCs at the firm level, which can be key predictors of firm performance in dynamic business environment. The results of this research is mostly relevant to top corporate executives (BOD) or top management team (TMT) who seek to provide some supporting ‘hardware’ content and condition such as technological factors, organizational factors, environmental factors, and to improve firm's ‘software ‘ ability such as adaptive capability, absorptive capability and innovative capability, in order to achieve a successful technology adoption in organization. There are also mediating factors which are elaborated at this paper; timing and external network. A further research for showing its empirical results is highly recommended.Keywords: technology adoption, TOE framework, dynamic capability, resources based view
Procedia PDF Downloads 332370 Development of Fuzzy Logic and Neuro-Fuzzy Surface Roughness Prediction Systems Coupled with Cutting Current in Milling Operation
Authors: Joseph C. Chen, Venkata Mohan Kudapa
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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.Keywords: surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations
Procedia PDF Downloads 145369 Innovative Entrepreneurship in Tourism Business: An International Comparative Study of Key Drivers
Authors: Mohammed Gamil Montasser, Angelo Battaglia
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Entrepreneurship is mostly related to the beginning of organization. In growing business organizations, entrepreneurship expands its conceptualization. It reveals itself through new business creation in the active organization, through renewal, change, innovation, creation and development of current organization, through breaking and changing of established rules inside or outside the organization and becomes more flexible, adaptive and competitive, also improving effectiveness of organization activity. Therefore, the topic of entrepreneurship, relates the creation of firms to personal / individual characteristics of the entrepreneurs and their social context. This paper is an empirical study, which aims to address these two gaps in the literature. For this endeavor, we use the latest available data from the Global Entrepreneurship Monitor (GEM) project. This data set is widely regarded as a unique source of information about entrepreneurial activity, as well as the aspirations and attitudes of individuals across a wide number of countries and territories worldwide. This paper tries to contribute to fill this gap, by exploring the key drivers of innovative entrepreneurship in the tourism sector. Our findings are consistent with the existing literature in terms of the individual characteristics of entrepreneurs, but quite surprisingly we find an inverted U-shape relation between human development and innovative entrepreneurship in tourism sector. It has been revealed that tourism entrepreneurs are less likely to have innovative products, compared with entrepreneurs in medium developed countries.Keywords: GEM, human development, innovative entrepreneurship, occupational choice, tourism
Procedia PDF Downloads 258368 Analysis of Hard Turning Process of AISI D3-Thermal Aspects
Authors: B. Varaprasad, C. Srinivasa Rao
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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of hard turning by using commercial software DEFORM 3D has been compared to experimental results of stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.Keywords: hard turning, computer aided engineering, computational machining, finite element method
Procedia PDF Downloads 454367 On the Use of Machine Learning for Tamper Detection
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
Procedia PDF Downloads 153366 Motion Performance Analyses and Trajectory Planning of the Movable Leg-Foot Lander
Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian
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In response to the functional limitations of the fixed landers, those are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability in deep space exploration currently, a movable lander based on the leg-foot walking mechanism is presented. Firstly, a quadruped landing mechanism based on pushrod-damping is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and the multi-function main/auxiliary buffers based on the crumple-energy absorption and screw-nut mechanism. Secondly, the workspace of the end of the leg-foot mechanism is solved by Monte Carlo method, and the key points on the desired trajectory of the end of the leg-foot mechanism are fitted by cubic spline curve. Finally, an optimal time-jerk trajectory based on weight coefficient is planned and analyzed by an adaptive genetic algorithm (AGA). The simulation results prove the rationality and stability of walking motion of the movable leg-foot lander in the star catalogue. In addition, this research can also provide a technical solution integrating of soft-landing, large-scale inspection and material transfer for future star catalogue exploration, and can even serve as the technical basis for developing the reusable landers.Keywords: motion performance, trajectory planning, movable, leg-foot lander
Procedia PDF Downloads 139365 Stress and Coping Strategies: A Correlational Analysis to Profiling Maladaptive Behaviors at Work
Authors: Silvia Riva, Ezekiel Chinyio
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Introduction: Workers in different sectors are prone to stress at varying levels. They also respond to stress in different ways. An inspiration was to study stress development amongst workers in a work dangerous setting (Construction Industry) as well as how they cope with specific stress incidences. Objective: The overarching objective of the study was to study and correlate between stress and coping strategies. The research was conducted in an organizational industrial setting, and its findings on the coping actions of construction workers are reported in this article. Methods: An online cross-sectional survey was conducted with 80 participants aged 18-62. These were working for three different construction organizations in the West Midland region of the UK. Their coping actions were assessed using the COPE Inventory (Carver, 2013) instrument while the level of stress was assessed by the Perceived Stress Scale (Cohen, 1994). Results: Out of 80 workers (20 female, 25%, mean age 40.66), positive reinterpretation (M=4.15, SD=2.60) and active coping (M=4.18, SD=2.55) were the two most adaptive strategies reported by the workers while the most frequent maladaptive behavior was mental disengagement (M=3.62, SD=2.25). Among the maladaptive tactics, alcohol and drug abuse was a significant moderator in stress reactions (t=6.12, p=.000). Conclusion: Some maladaptive strategies are adopted by construction workers to cope with stress. So, it could be argued that programs of stress prevention and control in the construction industry have a basis to develop solutions that can improve and strengthen effective interventions when workers are stressed or getting stressed.Keywords: coping, organization, strategies, stress
Procedia PDF Downloads 217364 The Experience of Applying Multi-Sensory Stimulation ICU for Arousing a Patient with Traumatic Brain Injury in Intensive Care
Authors: Hsiao-Wen Tsai
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Motor vehicle accident is the first cause of head injury in the world; severe head injury cases may cause conscious disturbance and death. This is a report about a case of a young adult patient suffering from motor vehicle accident leading to severe head injury who passed through three time surgical procedures, and his mother (who is the informal caregiver). This case was followed from 28th January to 15th February 2011 by using Gordon’s 11 functional health patterns. Patient’s cognitive-perceptual and self-perception-self-concept patterns were altered. Anxiety was also noted on his informal caregiver due to patients’ condition. During the intensive care period, maintaining patient’s vital signs and cerebral perfusion pressure were essential to avoid secondary neuronal injury. Multi-sensory stimulation, caring accompanying, supporting, listening and encouraging patient’s family involved in patient care were very important to reduce informal caregiver anxiety. Finally, the patient consciousness improved from GCS 4 to GCS 11 before discharging from ICU. Patient’s primary informal caregiver, his mother, also showed anxiety improvement. This is was successful case with traumatic brain injury recovered from coma.Keywords: anxiety, multi-sensory stimulation, reduce intracranial adaptive capacity, traumatic brain injury
Procedia PDF Downloads 267363 The Data-Driven Localized Wave Solution of the Fokas-Lenells Equation Using Physics-Informed Neural Network
Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy
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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation
Procedia PDF Downloads 70362 Diagnosis and Analysis of Automated Liver and Tumor Segmentation on CT
Authors: R. R. Ramsheeja, R. Sreeraj
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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification
Procedia PDF Downloads 509361 Autonomous Kuka Youbot Navigation Based on Machine Learning and Path Planning
Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza
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The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library
Procedia PDF Downloads 177360 Touristification of Industrial Waterfronts: The Rocks and Darling Harbour
Authors: Ece Kaya
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Industrial heritage reflects the traces of an industrial past that have contributed to the economic development of a country. This heritage should be included within the scope of preservation to remind of and to connect the city and its inhabitants to the past. Through adaptive conservation, industrial heritage can be reintroduced into contemporary urban life, with suitable functions and unique identities sustained. The conservation of industrial heritage should protect the material fabric of such heritage and maintain its cultural significance. Emphasising the historical and cultural significance of industrial areas, this research argues that industrial heritage is primarily impacted by political and economic thinking rather than by informed heritage and conservation issues. Waterfront redevelopment projects create similar landscapes around the world, transforming industrial identities and cultural significances. In the case of The Rocks and Darling Harbour, the goal of redevelopment was the creation of employment opportunities, and the provision of places to work, live and shop, through tourism promoted by the NSW State Government. The two case study areas were pivotal to the European industrial development of Sydney. Sydney Cove was one of the largest commercial wharves used to handle cargo in Australia. This paper argues, together with many historians, planners and heritage experts, that these areas have not received the due diligence deserved in regards to their significance to the industrial history of Sydney and modern Australia.Keywords: industrial heritage, post-industrial city, transformation of waterfronts, tourism, consumption
Procedia PDF Downloads 241359 Form of Social Quality Moving Process of Suburb Communities in a Changing World
Authors: Supannee Chaiumporn
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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.Keywords: social quality, form of social quality moving process, happiness, different social and cultural context
Procedia PDF Downloads 384358 Hybrid Learning and Testing at times of Corona: A Case Study at an English Department
Authors: Mimoun Melliti
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In the wake of the global pandemic, educational systems worldwide faced unprecedented challenges and had to swiftly adapt to new conditions. This necessitated a fundamental shift in assessment processes, as traditional in-person exams became impractical. The present paper aims to investigate how educational systems have adapted to the new conditions imposed by the outbreak of the pandemic. This paper serves as a case study documenting the various decisions, conditions, experiments, and outcomes associated with transitioning the assessment processes of a higher education institution to a fully online format. The participants of this study consisted of 4666 students from health, engineering, science, and humanities disciplines, who were enrolled in general English (Eng101/104) and English for specific purposes (Eng102/113) courses at a preparatory year institution in Saudi Arabia. The findings of this study indicate that online assessment can be effectively implemented given the fulfillment of specific requirements. These prerequisites encompass the presence of competent staff, administrative flexibility, and the availability of necessary infrastructure and technological support. The significance of this case study lies in its comprehensive description of the various steps and measures undertaken to adapt to the "new normal" situation. Furthermore, it evaluates the impact of these measures and offers detailed recommendations for potential similar future scenarios.Keywords: hybrid learning, testing, adaptive teaching, EFL
Procedia PDF Downloads 61357 Soft Computing Approach for Diagnosis of Lassa Fever
Authors: Roseline Oghogho Osaseri, Osaseri E. I.
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Lassa fever is an epidemic hemorrhagic fever caused by the Lassa virus, an extremely virulent arena virus. This highly fatal disorder kills 10% to 50% of its victims, but those who survive its early stages usually recover and acquire immunity to secondary attacks. One of the major challenges in giving proper treatment is lack of fast and accurate diagnosis of the disease due to multiplicity of symptoms associated with the disease which could be similar to other clinical conditions and makes it difficult to diagnose early. This paper proposed an Adaptive Neuro Fuzzy Inference System (ANFIS) for the prediction of Lass Fever. In the design of the diagnostic system, four main attributes were considered as the input parameters and one output parameter for the system. The input parameters are Temperature on admission (TA), White Blood Count (WBC), Proteinuria (P) and Abdominal Pain (AP). Sixty-one percent of the datasets were used in training the system while fifty-nine used in testing. Experimental results from this study gave a reliable and accurate prediction of Lassa fever when compared with clinically confirmed cases. In this study, we have proposed Lassa fever diagnostic system to aid surgeons and medical healthcare practictionals in health care facilities who do not have ready access to Polymerase Chain Reaction (PCR) diagnosis to predict possible Lassa fever infection.Keywords: anfis, lassa fever, medical diagnosis, soft computing
Procedia PDF Downloads 269356 Adaptive Architecture and Urbanism - A Study of Coastal Cities, Climate Change Problems, Effects, Risks And Opportunities for Making Sustainable Habitat
Authors: Santosh Kumar Ketham
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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play. To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities. This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism
Procedia PDF Downloads 137355 Biodegradable Poly D,L-Lactide-Co-Glycolic Acid Microparticle Vaccine against Aeromonas hydrophila Infection
Authors: Saekil Yun, Sib Sankar Giri, Jin Woo Jun, Hyoun Joong Kim, Sang Guen Kim, Sang Wha Kim, Jung Woo Kang, Se Jin Han, Se Chang Park
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In aquaculture, vaccination is important to control and prevent diseases. In the study, we utilized poly D,L-lactide-co-glycolic acid (PLGA) microparticles (MPs) for encapsulating formalin-killed Aeromonas hydrophila cells. To assess the innate and adaptive immune responses, carps and loaches were used for the experiments. Fish were divided into three groups (A, B, C). Total antigen of 0.1 ml vaccine was adjusted by 2 x 108 CFU and injected via intraperitoneal route. Group A was vaccinated with 0.1 ml of PLGA vaccine, group B was with 0.1 ml of FKC vaccine and group C was with 0.1 ml of sterile PBS. All three groups were challenged with A. hydrophila and challenge dose was lethal dose (LD50). Loaches and carp were then challenged with A. hydrophila at 12 and 20 weeks post vaccination (wpv), and 10 and 14 wpv, respectively, and relative survival rates were calculated. For both fish species, the curve of antibody titer over time was shallower in the PLGA group than the FKC group and the PLGA groups demonstrated higher survival rates at all time-points. In the groups of PLGA-MP, relative mRNA levels of IL-1β, TNF-α, lysozyme C and IgM were significantly upregulated than FKC treated groups. Biodegradable PLGA microparticle vaccine could induce longer immune responses than original FKC vaccines to protect from A. hydrophila infection.Keywords: PLGA, microparticles, Aeromonas hydrophila, vaccine
Procedia PDF Downloads 272354 A Comparative Study between Behaviour Activation, Rational Emotive Behaviour Therapy and Waiting List Control for Major Depressive Disorder
Authors: Shweta Jha, Digambar Darekar, Krishna Kadam
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Major Depressive Disorder (MDD) is one of the most common of psychiatric disorders. It has a wide range of symptoms, aetiologies and risk factors, and these reasons make MDD affect not only the primary patient, but also their family, caregivers and associates; by negatively impacting their self dignity, economic condition and self-confidence. Thus, it is important to help individuals suffering from MDD learn adaptive mechanism and deal effectively with their environment, with that aim this study focused on a comparative therapeutic intervention using Behaviour Activation (BA), Rational Emotive Behaviour Therapy (REBT) and Waiting list control (WLC) for management of MDD. This study apart from enhancing personal skills will also help us understand which therapeutic method would be more beneficial in treating and prolonging relapse in patients with MDD in Indian population. Fifteen individuals following application of inclusion and exclusion criteria were selected as study samples. They were randomly assigned to three treatment groups. Ten sessions of therapy, forty-five minutes each according to the proposed sessions plan were conducted for each group. The individuals selected as samples were re–assessed after 2 months and 6 months post intervention. The overall result showed that individuals treated with BA and REBT showed more improvement in comparison to those in WLC.Keywords: behaviour activation, major depressive disorder, rational emotive behaviour therapy, therapeutic intervention
Procedia PDF Downloads 254353 Automatic Motion Trajectory Analysis for Dual Human Interaction Using Video Sequences
Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng
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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).Keywords: motion detection, motion tracking, trajectory analysis, video surveillance
Procedia PDF Downloads 548352 Synergizing Additive Manufacturing and Artificial Intelligence: Analyzing and Predicting the Mechanical Behavior of 3D-Printed CF-PETG Composites
Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui
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This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities
Procedia PDF Downloads 10351 REITs India- New Investment Avenue for Financing Urban Infrastructure in India
Authors: Rajat Kapoor
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Indian Real Estate sector is the second largest employer after agriculture and is slated to grow at 30 percent over the next decade. Indian cities have shown tumultuous growth since last two decades. With the growing need of infrastructure, it has become inevitable for real estate sector to adopt more organized and transparent system of investment. SPVs such as REITs ensure transparency facilitating accessibility to invest in real estate for those who find it difficult to purchase real estate as an investment option with a realistic income expectation from their investment. RIETs or real estate investment trusts is an instrument of pooling funds similar to that of mutual funds. In a simpler term REIT is an Investment Vehicle in the form a trust which holds & manages large commercial rent¬ earning properties on behalf of investors and distributes most of its profit as dividends. REIT enables individual investors to invest their money in commercial real estate assets in a diversified portfolio and on the other hand provides fiscal liquidity to developers as easy exit option and channel funds for new projects. However, the success REIT is very much dependent on the taxation structure making such models attractive and adaptive enough for both developers and investors to opt for such investment option. This paper is intended to capture an overview of REITs with context to Indian real estate scenario.Keywords: Indian real estate, real estate infrastructure trusts, urban finance, infrastructure investment trusts
Procedia PDF Downloads 467350 Effect of Climate Variability on Honeybee's Production in Ondo State, Nigeria
Authors: Justin Orimisan Ijigbade
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The study was conducted to assess the effect of climate variability on honeybee’s production in Ondo State, Nigeria. Multistage sampling technique was employed to collect the data from 60 beekeepers across six Local Government Areas in Ondo State. Data collected were subjected to descriptive statistics and multiple regression model analyses. The results showed that 93.33% of the respondents were male with 80% above 40 years of age. Majority of the respondents (96.67%) had formal education and 90% produced honey for commercial purpose. The result revealed that 90% of the respondents admitted that low temperature as a result of long hours/period of rainfall affected the foraging efficiency of the worker bees, 73.33% claimed that long period of low humidity resulted in low level of nectar flow, while 70% submitted that high temperature resulted in improper composition of workers, dunes and queen in the hive colony. The result of multiple regression showed that beekeepers’ experience, educational level, access to climate information, temperature and rainfall were the main factors affecting honey bees production in the study area. Therefore, beekeepers should be given more education on climate variability and its adaptive strategies towards ensuring better honeybees production in the study area.Keywords: climate variability, honeybees production, humidity, rainfall and temperature
Procedia PDF Downloads 272349 Support for Planning of Mobile Personnel Tasks by Solving Time-Dependent Routing Problems
Authors: Wlodzimierz Ogryczak, Tomasz Sliwinski, Jaroslaw Hurkala, Mariusz Kaleta, Bartosz Kozlowski, Piotr Palka
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Implementation concepts of a decision support system for planning and management of mobile personnel tasks (sales representatives and others) are discussed. Large-scale periodic time-dependent vehicle routing and scheduling problems with complex constraints are solved for this purpose. Complex nonuniform constraints with respect to frequency, time windows, working time, etc. are taken into account with additional fast adaptive procedures for operational rescheduling of plans in the presence of various disturbances. Five individual solution quality indicators with respect to a single personnel person are considered. This paper deals with modeling issues corresponding to the problem and general solution concepts. The research was supported by the European Union through the European Regional Development Fund under the Operational Programme ‘Innovative Economy’ for the years 2007-2013; Priority 1 Research and development of modern technologies under the project POIG.01.03.01-14-076/12: 'Decision Support System for Large-Scale Periodic Vehicle Routing and Scheduling Problems with Complex Constraints.'Keywords: mobile personnel management, multiple criteria, time dependent, time windows, vehicle routing and scheduling
Procedia PDF Downloads 323348 Design of a Photovoltaic Power Generation System Based on Artificial Intelligence and Internet of Things
Authors: Wei Hu, Wenguang Chen, Chong Dong
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In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management
Procedia PDF Downloads 123347 Self-Regulation in Socially Rejected Pupils
Authors: Karla Hrbackova, Irena Balaban Cakirpaloglu
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This paper is a report on self-regulation in socially rejected pupils. A certain form of social rejection can be found in almost every class within the school environment. Research shows that due to social rejection mechanisms supporting the individual´s effort of reintegration into the group are not triggered. Paradoxically the opposite tendency arises, i.e., an increase in selfish and defeating behaviour. The link between peer exposure and self-regulation is likely to vary as a function of a type and quality of peer interaction (e.g., rejection or acceptance). The paper aims to clarify the level of self-regulation related to interpersonal cognitive problem-solving within the process of social rejection in a school class. The research was done on a sample of 1,133 upper-primary school pupils using the Means-Ends Problem Solving technique (MEPS) and peer sociometric nomination. The results showed that the level of self-regulated skills is related to the status of social rejection. Socially rejected pupils achieve lower levels of self-regulation than other classmates. We found deficiency in the regulation of behaviour, emotions and the regulation of will in the peer rejected pupils with the exception of cognitive regulation in which no differences were detected between socially rejected pupils and other classmates. The results have implications for early prevention and intervention efforts to foster adaptive self-regulation and reduce the risk of later social rejection.Keywords: interpersonal cognitive problem-solving, self-regulation, socially rejected pupils, upper-primary school pupils
Procedia PDF Downloads 170346 A Combination of Anisotropic Diffusion and Sobel Operator to Enhance the Performance of the Morphological Component Analysis for Automatic Crack Detection
Authors: Ankur Dixit, Hiroaki Wagatsuma
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The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform
Procedia PDF Downloads 173345 Enhancing Information Technologies with AI: Unlocking Efficiency, Scalability, and Innovation
Authors: Abdal-Hafeez Alhussein
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Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.Keywords: artificial intelligence, information technology, automation, scalability
Procedia PDF Downloads 17344 Antioxidant Enzymes and Crude Mitochondria ATPases in the Radicle of Germinating Bean (Vigna unguiculata) Exposed to Different Concentrations of Crude Oil
Authors: Stella O. Olubodun, George E. Eriyamremu
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The study examined the effect of Bonny Light whole crude oil (WC) and its water soluble fraction (WSF) on the activities of antioxidant enzymes (catalase (CAT) and superoxide dismutase (SOD)) and crude mitochondria ATPases in the radicle of germinating bean (Vigna unguiculata). The percentage germination, level of lipid peroxidation, antioxidant enzyme, and mitochondria Ca2+ and Mg2+ ATPase activities were measured in the radicle of bean after 7, 14, and 21 days post germination. Viable bean seeds were planted in soils contaminated with 10ml, 25ml, and 50ml of whole crude oil (WC) and its water soluble fraction (WSF) to obtain 2, 5, and 10% v/w crude oil contamination. There was dose dependent reduction of the number of bean seeds that germinated in the contaminated soils compared with control (p<0.001). The activities of the antioxidant enzymes, as well as, adenosine triphosphatase enzymes, were also significantly (p<0.001) altered in the radicle of the plants grown in contaminated soil compared with the control. Generally, the level of lipid peroxidation was highest after 21 days post germination when compared with control. Stress to germinating bean caused by Bonny Light crude oil or its water soluble fraction resulted in adaptive changes in crude mitochondria ATPases in the radicle.Keywords: antioxidant enzymes, bonny light crude oil, radicle, mitochondria ATPases
Procedia PDF Downloads 302343 Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of Stroke; A Systematic Review
Authors: Zahra Hassani
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Background and Purpose: Poststroke depression (PSD) is one of the complications of a stroke that reduces the patient's chance of recovery, becomes irritable, and changes personality. Cognitive rehabilitation is one of the non-pharmacological methods that improve deficits such as attention, memory, and symptoms of depression. Therefore, the purpose of the present study is to evaluate the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke. Method: In this study, a systematic review of the databases Google Scholar, PubMed, Science Direct, Elsevier between the years 2015 and 2019 with the keywords cognitive rehabilitation therapy, post-stroke, depression Search is done. In this process, studies that examined the Efficacy of Cognitive Rehabilitation Therapy on Poststroke Depression among Survivors of stroke were included in the study. Results: Inclusion criteria were full-text availability, interventional study, and non-review articles. There was a significant difference between the articles in terms of the indices studied, sample number, method of implementation, and so on. A review of studies have shown that cognitive rehabilitation therapy has a significant role in reducing the symptoms of post-stroke depression. The use of these interventions is also effective in improving problem-solving skills, improving memory, and improving attention and concentration. Conclusion: This study emphasizes on the development of efficient and flexible adaptive skills through cognitive processes and its effect on reducing depression in patients after stroke.Keywords: cognitive therapy, depression, stroke, rehabilitation
Procedia PDF Downloads 124342 An Approach to Control Electric Automotive Water Pumps Deploying Artificial Neural Networks
Authors: Gabriel S. Adesina, Ruixue Cheng, Geetika Aggarwal, Michael Short
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With the global shift towards sustainability and technological advancements, electric Hybrid vehicles (EHVs) are increasingly being seen as viable alternatives to traditional internal combustion (IC) engine vehicles, which also require efficient cooling systems. The electric Automotive Water Pump (AWP) has been introduced as an alternative to IC engine belt-driven pump systems. However, current control methods for AWPs typically employ fixed gain settings, which are not ideal for the varying conditions of dynamic vehicle environments, potentially leading to overheating issues. To overcome the limitations of fixed gain control, this paper proposes implementing an artificial neural network (ANN) for managing the AWP in EHVs. The proposed ANN provides an intelligent, adaptive control strategy that enhances the AWP's performance, supported through MATLAB simulation work illustrated in this paper. Comparative analysis demonstrates that the ANN-based controller surpasses conventional PID and fuzzy logic-based controllers (FLC), exhibiting no overshoot, 0.1secs rapid response, and 0.0696 IAE performance. Consequently, the findings suggest that ANNs can be effectively utilized in EHVs.Keywords: automotive water pump, cooling system, electric hybrid vehicles, artificial neural networks, PID control, fuzzy logic control, IAE, MATLAB
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