Search results for: hierarchical model predictive control

Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

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Authors: Tariqul Islam, Shaheen Mollah

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The study's main objective is to assess the relationship between psychological adjustment and parental acceptance-rejection, teacher acceptance-rejection, and best friend acceptance-rejection among secondary school students. This study was conducted on a sample of 300 (6th through 10th-grade students) recruited from over ten schools in Dhaka. While the schools were selected purposively, the respondents within each school were selected conveniently. The collected data were analyzed using Pearson product-moment correlation, hierarchical regression, and simultaneous regression analysis. The results showed that psychological adjustment is positively correlated with paternal, maternal, teacher, and best friend acceptance. The paternal acceptance was significantly connected with maternal acceptance. The teacher and best friend acceptance are correlated substantially with paternal and maternal acceptance. The hierarchical multiple regressions indicated that maternal, paternal, teacher, and best friend acceptance-rejection contributed significantly to students' psychological adjustment. The results revealed substantial independent contributions of maternal, paternal, teacher, and best friend acceptance on the students' psychological adjustment. The simultaneous regression analysis indicates that the maternal and best friend acceptances (but not paternal acceptance) were significant predictors of psychological adjustments. It showed that 41.7% variability in psychological adjustment could be explained by paternal, maternal, and best friend acceptance. The findings of the present study are exciting. They may contribute to developing insight in parents and best friends for behaving properly with their offspring and friend, respectively, for better psychological adjustment.

Keywords: adjustment, parenting, rejection, acceptance

Procedia PDF Downloads 139

Authors: Imam Taufik, Hilkatul Ilmi, Puryani, Mochammad Yuwono, Aty Widyawaruyanti

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Artocarpus champeden Spreng stembark (Moraceae) in Indonesia well known as ‘cempedak’ had been traditionally used for malarial remedies. The difference of growth locations could cause the difference of metabolite profiling. As a consequence, there were difference antimalarial activities in spite of the same plants. The aim of this research was to obtain the profile of metabolites that contained in A. champeden stembark from different locations in Indonesia for authentication and quality control purpose of this extract. The profiling had been performed by HPTLC-Densitometry technique and antimalarial activity had been also determined by HRP2-ELISA technique. The correlation between metabolite fingerprinting and antimalarial activity had been analyzed by Principle Component Analysis, Hierarchical Clustering Analysis and Partial Least Square. As a result, there is correlation between the difference metabolite fingerprinting and antimalarial activity from several different growth locations.

Keywords: antimalarial, artocarpus champeden spreng, metabolite fingerprinting, multivariate analysis

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Authors: Jair Servín-Aguilar, Yu Tang

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We address the problem of robust attitude tracking for agile satellites under unknown bounded torque disturbances using a double-gimbal variable-speed control-moment gyro (DGVSCMG) driven by a cluster of three permanent magnet synchronous motors (PMSMs). Uniform practical asymptotic stability is achieved at the torque control level first. The desired speed of gimbals and the acceleration of the spin wheel to produce the required torque are then calculated by a velocity-based steering law and tracked at the PMSM speed-control level by designing a speed-tracking controller with compensation for the vibration caused by eccentricity and imbalance due to mechanical imperfection in the DGVSCMG. Uniform practical asymptotic stability of the overall system is ensured by loan relying on the analysis of the resulting cascaded system. Numerical simulations are included to show the performance improvement of the proposed controller.

Keywords: agile satellites, vibration compensation, internal model, stability

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Authors: Hosein I. Hosein, Ragab Azzam, Ahmed M. S. Menshawy, Sherin Rouby, Khaled Hendy, Ayman Mahrous, Hany Hussien

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Brucellosis is a highly contagious bacterial zoonotic disease of a worldwide spread and has different names; Infectious or enzootic abortion and Bang's disease in animals; and Mediterranean or Malta fever, Undulant Fever and Rock fever in humans. It is caused by the different species of genus Brucella which is a Gram-negative, aerobic, non-spore forming, facultative intracellular bacterium. Brucella affects a wide range of mammals including bovines, small ruminants, pigs, equines, rodents, marine mammals as well as human resulting in serious economic losses in animal populations. In human, Brucella causes a severe illness representing a great public health problem. The disease was reported in Egypt for the first time in 1939; since then the disease remained endemic at high levels among cattle, buffalo, sheep and goat and is still representing a public health hazard. The annual economic losses due to brucellosis were estimated to be about 60 million Egyptian pounds yearly, but actual estimates are still missing despite almost 30 years of implementation of the Egyptian control programme. Despite being the gold standard, bacterial isolation has been reported to show poor sensitivity for samples with low-level of Brucella and is impractical for regular screening of large populations. Thus, serological tests still remain the corner stone for routine diagnosis of brucellosis, especially in developing countries. In the present study, a total of 1533 cows (256 from Beni-Suef Governorate, 445 from Al-Fayoum Governorate and 832 from Damietta Governorate), were employed for estimation of relative sensitivity, relative specificity, positive predictive value and negative predictive value of buffered acidified plate antigen test (BPAT), rose bengal test (RBT) and complement fixation test (CFT). The overall seroprevalence of brucellosis revealed (19.63%). Relative sensitivity, relative specificity, positive predictive value and negative predictive value of BPAT,RBT and CFT were estimated as, (96.27 %, 96.76 %, 87.65 % and 99.10 %), (93.42 %, 96.27 %, 90.16 % and 98.35%) and (89.30 %, 98.60 %, 94.35 %and 97.24 %) respectively. BPAT showed the highest sensitivity among the three employed serological tests. RBT was less specific than BPAT. CFT showed the least sensitivity 89.30 % among the three employed serological tests but showed the highest specificity. Different tissues specimens of 22 seropositive cows (spleen, retropharyngeal udder, and supra-mammary lymph nodes) were subjected for bacteriological studies for isolation and identification of Brucella organisms. Brucella melitensis biovar 3 could be recovered from 12 (54.55%) cows. Bacteriological examinations failed to classify 10 cases (45.45%) and were culture negative. Bruce-ladder PCR was carried out for molecular identification of the 12 Brucella isolates at the species level. Three fragments of 587 bp, 1071 bp and 1682 bp sizes were amplified indicating Brucella melitensis. The results indicated the importance of using several procedures to overcome the problem of escaping of some infected animals from diagnosis.Bruce-ladder PCR is an important tool for diagnosis and epidemiologic studies, providing relevant information for identification of Brucella spp.

Keywords: brucellosis, relative sensitivity, relative specificity, Bruce-ladder, Egypt

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Authors: Le Kang

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On the research question of 'how to achieve USR', this contribution reflects the concept of university social responsibility, identify three achievement models of USR as the society - diversified model, the university-cooperation model, the government - compound model, also conduct a case study to explore characteristics of Chinese achievement model of USR. The contribution concludes with discussion of how the university, government and society balance demands and roles, make necessarily strategic adjustment and innovative approach to repair the shortcomings of each achievement model.

Keywords: modern university, USR, achievement model, compound model

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Authors: Ellis Kofi Akwaa-Sekyi, Jordi Moreno Gené

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Managerial actions which negatively profile banks and impair corporate reputation are addressed through effective internal control systems. Disregard for acceptable standards and procedures for granting credit have affected bank loan portfolios and could be cited for the crises in some European countries. The study intends to determine the effectiveness of internal control systems, investigate whether perceived agency problems exist on the part of board members and to establish the relationship between internal controls and credit risk among listed banks in the European Union. Drawing theoretical support from the behavioural compliance and agency theories, about seventeen internal control variables (drawn from the revised COSO framework), bank-specific, country, stock market and macro-economic variables will be involved in the study. A purely quantitative approach will be employed to model internal control variables covering the control environment, risk management, control activities, information and communication and monitoring. Panel data from 2005-2014 on listed banks from 28 European Union countries will be used for the study. Hypotheses will be tested and the Generalized Least Squares (GLS) regression will be run to establish the relationship between dependent and independent variables. The Hausman test will be used to select whether random or fixed effect model will be used. It is expected that listed banks will have sound internal control systems but their effectiveness cannot be confirmed. A perceived agency problem on the part of the board of directors is expected to be confirmed. The study expects significant effect of internal controls on credit risk. The study will uncover another perspective of internal controls as not only an operational risk issue but credit risk too. Banks will be cautious that observing effective internal control systems is an ethical and socially responsible act since the collapse (crisis) of financial institutions as a result of excessive default is a major contagion. This study deviates from the usual primary data approach to measuring internal control variables and rather models internal control variables in a quantitative approach for the panel data. Thus a grey area in approaching the revised COSO framework for internal controls is opened for further research. Most bank failures and crises could be averted if effective internal control systems are religiously adhered to.

Keywords: agency theory, credit risk, internal controls, revised COSO framework

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Authors: J. Karthik, G. Vinayagamurthy

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Aerodynamic flow control is achieved by interaction of flowing medium with corresponding structure so that its natural flow state is disturbed to delay the transition point. This paper explains the aerodynamic effect and optimized design of Vortex Generators on the turbine blade to achieve maximum flow control. The airfoil is chosen from NREL [National Renewable Energy Laboratory] S-series airfoil as they are characterized with good lift characteristics and lower noise. Vortex generators typically chosen are Ogival, Rectangular, Triangular and Tapered Fin shapes attached near leading edge. Vortex generators are typically distributed from the primary to tip of the blade section. The design wind speed is taken as 6m/s and the computational analysis is executed. The blade surface is simulated using k- ɛ SST model and results are compared with X-FOIL results. The computational results are validated using Wind Tunnel Testing of the blade corresponding to the design speed. The effect of Vortex generators on the flow characteristics is studied from the results of analysis. By comparing the computational and test results of all shapes of Vortex generators; the optimized design is achieved for effective flow control corresponding to the blade.

Keywords: flow control, vortex generators, design optimisation, CFD

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Ali Oveysi Sarabi

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In this paper, controller design for the attitude and altitude dynamics of an outdoor quadrotor, which is constructed with low cost actuators and drivers, is aimed. Before designing the controller, the quadrotor is modeled mathematically in Matlab-Simulink environment. To control attitude dynamics, linear quadratic regulator (LQR) based controllers are designed, simulated and applied to the system. Two different proportional-integral-derivative action (PID) controllers are designed to control yaw and altitude dynamics. During the implementation of the designed controllers, different test setups are used. Designed controllers are implemented and tuned on the real system using xPC Target. Tests show that these basic control structures are successful to control the attitude and altitude dynamics.

Keywords: helicopter balance, flight dynamics, autonomous landing, control robotics

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Authors: Michel Zaitouni, Mohamed Nassar

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The purpose of this study is first, to explore the effect of employees’ perception of justice on trust in the supervisor in the context of performance appraisal; Second, to assess the role of perceived supervisor support as a mediator between organizational justice and trust in the supervisor in a non-western society such as Kuwait.The survey data consisted of 415 employees working at different hierarchical levels in three major banks in Kuwait. Hierarchical regression analysis was used to test the research hypotheses. Results supported hypothesized relationships between distributive, informational and interpersonal justice and trust in the supervisor but failed to support that procedural justice positively and significantly relate to trust in the supervisor. Moreover, results found that this relationship is partially mediated by perceived supervisor support. A potential limitation of this study is that data were obtained from the same industry which limits the generalizability of this study to other industries. Moreover, a longitudinal research will be helpful to strengthen the mediating relationship. The findings provide valuable information for the development of common perspectives regarding the perception of justice in the context of performance appraisal between the western and non-western societies. The paper has the privilege to explore additional relationships related to justice perceptions in the Kuwaiti banking sector, whereas previous research focused mainly on procedural and distributive justice as predictors of trust in the supervisor.

Keywords: Kuwait, organizational justice, perceived supervisor support, trust in the supervisor

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Kazuya Sato, Toru Kasahara, Junji Kuroda

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In this paper, an autonomous hovering control method of multicopter using only Web camera is proposed. Recently, various control method of an autonomous flight for multicopter are proposed. But, in the previously proposed methods, a motion capture system (i.e., OptiTrack) and laser range finder are often used to measure the position and posture of multicopter. To achieve an autonomous flight control of multicopter with simple equipment, we propose an autonomous flight control method using AR marker and Web camera. AR marker can measure the position of multicopter with Cartesian coordinate in three dimensional, then its position connects with aileron, elevator, and accelerator throttle operation. A simple PID control method is applied to the each operation and adjust the controller gains. Experimental result are given to show the effectiveness of our proposed method. Moreover, another simple operation method for autonomous flight control multicopter is also proposed.

Keywords: autonomous hovering control, multicopter, Web camera, operation

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Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

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In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).

Keywords: network security management, device organization, emergency response, cross-network

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Authors: Maryam Hajrezaie, Mahmood Ameen Abdulla, Nazia AbdulMajid, Maryam Zahedifard

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Colon cancer is one of the most prevalent cancers in the world. Cancer chemoprevention is defined as the use of natural or synthetic compounds capable of inducing biological mechanisms necessary to preserve genomic fidelity. New schiff based compounds are reported to exhibit a wide spectrum of biological activities of therapeutic importance. To evaluate inhibitory properties of CdCl2(C14H21N3O2) complex on colonic aberrant crypt foci, five groups of 7-week-old male rats were used. Control group was fed with 10% Tween 20 once a day, cancer control group was intra-peritoneally injected with 15 mg/kg Azoxymethan, drug control group was injected with 15 mg/kg azoxymethan and 5-Flourouracil, experimental groups were fed with 2.5 and 5 mg/kg CdCl2(C14H21N3O2) compound each once a day. Administration of compound were found to be effectively chemoprotective. Andrographolide suppressed total colonic ACF formation up to 72% to 74%, respectively, when compared with control group. The results also showed a significant increase in glutathione peroxidase, superoxide dismutase, catalase activities and a decrease in malondialdehyde level. Immunohistochemical staining demonstrated down-regulation of PCNA protein. According to the Western blot comparison analysis, COX-2 and Bcl2 is up-regulated whilst the Bax is down-regulated. according to these data, this compound plays promising chemoprotective activity, in a model of AOM-induced in ACF.

Keywords: chemopreventive, Schiff based compound, aberrant crypt foci (ACF), immunohistochemical staining

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Authors: D. Maneetham

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The developed exoskeleton device has to control joints between shoulder and arm. Exoskeleton device can help patients with hemiplegia upper so that the patient can help themselves in their daily life. Exoskeleton device includes a robot arm wear that looks like the movement is similar to the normal arm. Exoskeleton arm is powered by the motor through the cable with a control system that developed to control the movement of the joint of a robot arm. The arm will include the shoulder, the elbow, and the wrist. The control system is used Arduino Mega 2560 controller and the operation of the DC motor through the relay module. The control system can be divided into two modes such as the manual control with the joystick mode and automatically control with the movement of the head by Gyro sensor. The controller is also designed to move between the shoulder and the arm movement from their original location. Results have shown that the controller gave the best performance and all movements can be controlled.

Keywords: exoskeleton arm, hemiplegia upper, shoulder and arm, stroke

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Authors: Chyi Jaw

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Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.

Keywords: cognitive rigidity, consumer emotions, new technology acceptance, routine seeking, technology complexity

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Noa Nelson, Meitar Moshe, Dana Cohen

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Work-family conflict (WFC) is a significant source of stress for contemporary employees, with research indicating its heightened severity for women. The conservation of resources theory argues that individuals experience stress when their resources fall short of demands, and attempt to reach balance by obtaining resources. Presumably then, to achieve work-family balance women would need to negotiate for resources such as spouse support, employer support and work flexibility. The current research tested the hypotheses that competent negotiation at home and at work associated with increased family and job resources and with decreased WFC, as well as with higher work, marital and life satisfaction. In the first study, 113 employed mothers, married or cohabiting, reported to what extent they conducted satisfactory negotiation with spouse over division of housework, and their actual housework load compared to spouse. They answered a WFC questionnaire, measuring how much work interferes with family (WIF) and how much family interferes with work (FIW), and finally, measurements of satisfaction. In the second study, 94 employed mothers, married or cohabiting reported to what extent they conducted satisfactory negotiation with their boss over balancing work demands with family needs. They reported the levels of three job resources: flexibility, control and family-friendly organizational culture. Finally, they answered the same WFC and satisfaction measurements from study 1. Statistical analyses –t-tests, correlations, and hierarchical linear regressions- showed that in both studies, women reported higher WIF than FIW. Negotiations associated with increased resources: support from spouse, work flexibility and control and a family-friendly culture; negotiation with spouse associated also with satisfaction measurements. However, negotiations or resources (except family-friendly culture) did not associate with reduced conflict. The studies demonstrate the role of negotiation in obtaining family and job resources. Causation cannot be determined, but the fact is that employed mothers who enjoyed more support (at both home and work), flexibility and control, were more likely to keep active interactions to increase them. This finding has theoretical and practical implications, especially in view of research on female avoidance of negotiation. It is intriguing that negotiations and resources generally did not associate with reduced WFC. This finding might reflect the severity of the conflict, especially of work interfering with family, which characterizes many contemporary jobs. It might also suggest that employed mothers have high expectations from themselves, and even under supportive circumstances, experience the challenge of balancing two significant and demanding roles. The research contributes to the fields of negotiation, gender, and work-life balance. It calls for further studies, to test its model in additional populations and validate the role employees have in actively negotiating for the balance that they need. It also calls for further research to understand the contributions of job and family resources to reducing work-family conflict, and the circumstances under which they contribute.

Keywords: sork-family conflict, work-life balance, negotiation, gender, job resources, family resources

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate which minimize the total incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: subcontracting, optimal control, deterioration, simulation, production planning

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: Khalil Ibrahim, Ahmed Ramadan, Mohamed Fanni, Yo Kobayashi, Ahmed Abo-Ismail, Masakatus G. Fujie

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This paper deals with the design process and the dynamic control simulation of a new type of 4-DOFs parallel mechanism that can be used as an endoscopic surgical manipulator. The proposed mechanism, 2-PUU_2-PUS, is designed based on the screw theory and the parallel virtual chain type synthesis method. Based on the structure analysis of the 4-DOF parallel mechanism, the inverse position equation is studied using the inverse analysis theory of kinematics. The design and the stress analysis of the mechanism are investigated using SolidWorks software. The virtual prototype of the parallel mechanism is constructed, and the dynamic simulation is performed using ADAMS TM software. The system model utilizing PID and PI controllers has been built using MATLAB software. A more realistic simulation in accordance with a given bending angle and point to point control is implemented by the use of both ADAMS/MATLAB software. The simulation results showed that this control method has solved the coordinate control for the 4-DOF parallel manipulator so that each output is feedback to the four driving rods. From the results, the tracking performance is achieved. Other control techniques, such as intelligent ones, are recommended to improve the tracking performance and reduce the numerical truncation error.

Keywords: parallel mechanisms, medical robotics, tracjectory control, virtual chain type synthesis method

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Authors: Martina Kaufmann, Thomas Goetz, Anastasiya A. Lipnevich, Reinhard Pekrun

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Positive emotions have been shown to benefit from optimistic perceptions, even if these perceptions are illusory. The current research investigated the impact of illusions of control on positive emotions. There is empirical evidence showing that people are more emotionally attentive to losses than to gains. Hence, we expected that, compared to gains, losses in illusory control would have a stronger impact on positive emotions. The results of two experimental studies support this assumption: Participants who experienced gains in illusory control showed no substantial change in positive emotions. However, positive emotions decreased when they perceived a loss in illusory control. These results suggest that a loss of illusory control (but not a gain thereof) mediates the impact of the situation on individuals’ positive emotions. Implications for emotion theory and practice are discussed.

Keywords: cognitive appraisal, control, illusions, optimism, positive emotions

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Authors: Tingyu Zhang

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This paper utilizes the Super-SBM model to assess water resources green efficiency (WRGE) among provinces in China and investigate its spatial and temporal features, based on the characteristic framework of “economy-environment-society.” The social network analysis is employed to examine the network pattern and spatial interaction of WRGE. Further, the quadratic assignment procedure method is utilized for examining the influencing factors of the spatial association of WRGE regarding “relationship.” The study reveals that: (1) the spatial distribution of WRGE demonstrates a distribution pattern of Eastern>Western>Central; (2) a remarkable spatial association exists among provinces; however, no strict hierarchical structure is observed. The internal structure of the WRGE network is characterized by the feature of "Eastern strong and Western weak". The block model analysis discovers that the members of the “net spillover” and “two-way spillover” blocks are mostly in the eastern and central provinces; “broker” block, which plays an intermediary role, is mostly in the central provinces; and members of the “net beneficiary” block are mostly in the western region. (3) Differences in economic development, degree of urbanization, water use environment, and water management have significant impacts on the spatial connection of WRGE. This study is dedicated to the realization of regional linkages and synergistic enhancement of WRGE, which provides a meaningful basis for building a harmonious society of human and water coexistence.

Keywords: water resources green efficiency, super-SBM model, social network analysis, quadratic assignment procedure

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Authors: Yao Wu

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In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.

Keywords: digital inclusive finance, high-quality development of export trade, fixed effects, binary marginal effects

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Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m². 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal Breast Cancer, Hormone Sensitivity, Iraq, Risk Factors

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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Authors: Mohd Ritzman Abdul Karim, Zhaohui Huang

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A current focus in seismic engineering practice is the development of seismic design approach that focuses on the performance-based design. Performance-based design aims to design the structures to achieve specified performance based on the damage limit states. This damage limit is more restrictive limit than life safety and needs to be carefully estimated to avoid damage in piers due to failure in transverse reinforcement. In this paper, a different perspective of damage limit states has been explored by integrating two damage control material limit state, concrete and reinforcement by introduced parameters such as expected yield stress of transverse reinforcement where peak tension strain prior to bar buckling is introduced in a recent study. The different perspective of damage limit states with modified yield displacement and the modified plastic-hinge length is used in order to predict damage-control target displacement for reinforced concreate (RC) bridge pier. Three-dimensional (3D) finite element (FE) model has been developed for estimating damage target displacement to validate proposed damage limit states. The result from 3D FE analysis was validated with experimental study found in the literature. The validated model then was applied to predict the damage target displacement for RC bridge pier and to validate the proposed study. The tensile strain on reinforcement and compression on concrete were used to determine the predicted damage target displacement and compared with the proposed study. The result shows that the proposed damage limit states were efficient in predicting damage-control target displacement consistent with FE simulations.

Keywords: damage-control target displacement, damage limit states, reinforced concrete bridge pier, yield displacement

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Authors: Mohd Salmi Md Noorani, Ghada Al-Mahbashi, Sakhinah Abu Bakar

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This paper investigates projective lag synchronization (PLS) behavior in drive response dynamical networks (DRDNs) model with identical nodes. A hybrid feedback control method is designed to achieve the PLS with mismatch and without mismatch terms. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Moreover, the numerical simulations results demonstrate the validity of the proposed method.

Keywords: drive-response dynamical network, projective lag synchronization, hybrid feedback control, stability theory

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