Search results for: structural change model

Authors: Spanova Yerkezhan, Amantay Ayan, Alimzhanova Laura

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This article discusses the concept of rebranding and its relationship to cybersecurity. Rebranding is the process of changing the appearance and image of a company or organization in order to appeal to new customers or change the perception of a company. It can be a powerful tool for businesses looking to renew their reputation or expand into new markets. In today's digital age, companies increasingly rely on technology and the internet to conduct business; rebranding can also present significant cybersecurity risks. This is because a rebranding effort can create new vulnerabilities for companies, particularly in terms of their online presence. This article explores the potential hazards associated with rebranding and provides recommendations for mitigating those risks. It also highlights the importance of considering cybersecurity in the rebranding process and how it can be integrated into the overall strategy for a successful and secure rebranding.

Keywords: rebranding, cybersecurity, cyberattack, logo, vulnerability

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Authors: Muhammad Umer Zubair, Kamran Akhtar, Muhammad Arsalan Khan

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This paper is based on a research carried out on a failed slope in Defence Housing Authority (DHA) Phase I, Islamabad. The research included determination of Soil parameters, Site Surveying and Cost Estimation. Apart from these, the use of three dimensional (3D) slope stability analysis in conjunction with two dimensional (2D) analysis was used determination of slope conditions. In addition collection of soil reports, a detailed survey was carried out to create a 3D model in Surfer 8 software. 2D cross-sections that needed to be analyzed for stability were generated from 3D model. Slope stability softwares, Rocscience Slide 6.0 and Clara-W were employed for 2D and 3D Analyses respectively which have the ability to solve complex mathematical functions. Results of the analyses were used to confirm site conditions and the threats were identified to recommend suitable remedies.The most effective remedy was suggested for slope stability after analyzing all remedies in software Slide 6 and its feasibility was determined through cost benefit analysis. This paper should be helpful to Geotechnical engineers, design engineers and the organizations working with slope stability.

Keywords: slope stability, Rocscience, Clara W., 2d analysis, 3D analysis, sensitivity analysis

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Authors: U. Narumitbowonkul, P. Keangin, P. Rattanadecho

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Both numerical and experimental investigation of the temperature distribution and electric field in a natural rubber glove (NRG) during microwave heating are studied. A three-dimensional model of NRG and microwave oven are considered in this work. The influences of position, heating time and rotation angle of NRG on temperature distribution and electric field are presented in details. The coupled equations of electromagnetic wave propagation and heat transfer are solved using the finite element method (FEM). The numerical model is validated with an experimental study at a frequency of 2.45 GHz. The results show that the numerical results closely match the experimental results. Furthermore, it is found that the temperature distribution and electric field increases with increasing heating time. The hot spot zone appears in NRG at the tip of middle finger while the maximum temperature occurs in case of rotation angle of NRG = 60 degree. This investigation provides the essential aspects for a fundamental understanding of heat transport of NRG using microwave energy in industry.

Keywords: electric field, finite element method, microwave energy, natural rubber glove

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Authors: Pradapet Krutchangthong, Jirawat Sudsawart

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This research aims to study the health tourism administration and factors related to health tourism promotion at Ban Nam Chieo Community, Laem Ngop, Trat Province. The sample in this research is 361 tourists who use the service and Ban Nam Chieo Community residents who provide the service. Sampling was done from a population size of 3,780 using Taro Yamane’s formula. The tools used in the study were questionnaires and interviews. The statistics used in this research are percentage, mean and standard deviation. The result of Model Development of Health Tourism at Ban Nam Chieo Community, Laem Ngop , Trat Province shows that most of them are female with bachelor degree. They are government officers with an average income between 16,001-20,000 Baht. Suggested health system activities for health tourism development are: 1) health massage, 2) herbal compress, 3) exercise in the water by walking on shell. Meanwhile, factors related to health tourism promotion at Ban Nam Chieo Community, Laem Ngop, Trat Province are: 1) understanding the context of the community and service providers, 2) cooperation from related government and private sectors.

Keywords: health tourism, health system activities, promotion, administration

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Authors: Nermin Mahmoud Gohar, Aisha Tarek Noour

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Learner satisfaction has been a vital field of interest in the literature. Accordingly, the paper will explore the reasons behind individual differences in motivation and satisfaction. This study examines the effect of both; Herzberg’s and Maslow’s theories on learners satisfaction. A self-administered questionnaire was used to collect data from learners who were geographically widely spread around the College of Maritime Transport and Technology (CMTT) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. One hundred and fifty undergraduates responded to a questionnaire survey. Respondents were drawn from two branches in Alexandria and Port Said. The data analysis used was SPSS 22 and AMOS 18. Factor analysis technique was used to find out the dimensions under study verified by Herzberg’s and Maslow’s theories. In addition, regression analysis and structural equation modeling were applied to find the effect of the above-mentioned theories on maritime transport learners’ satisfaction. Concerning the limitation of this study, it used the available number of learners in the CMTT due to the relatively low population in this field.

Keywords: motivation, satisfaction, needs, education, Herzberg’s and Maslow’s theories

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Abdullah Abu-Tineh, Youmen Chaaban

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This study examines the development of a professional development (PD) model for teacher growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge and skills of both school leadership and teachers in an attempt to improve student learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents findings from an evaluation of this PD program. Based on an adaptation of Guskey’s evaluation of PD models, 100 teachers at the participating schools were selected for classroom observations and 40 took part in in-depth interviews to examine changed classroom practices. The impact of the PD program on student learning was also examined. Teachers’ practices and their students’ achievement in English, Arabic, mathematics and science were measured at the beginning and at the end of the intervention.

Keywords: initiative, professional development, school based support Program (SBSP), school reform

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Authors: Qi Wang

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Accurate pronunciation is the first condition of communication. Compared with the alphabetic languages, Chinese is more difficult for the foreigners to study as a second language, due to the tonal language with the meaningful characters as the written system, especially speaking. This research first presents the statistics of the typical errors of the pronunciations, based on the data of our two- year program of graduate students, which shown 90% of their speaking with strong foreign accents and no obvious change of the pitches, even if they could speak Chinese fluently. Second part, analyzed the caused reasons in the learning and teaching processes. Third part, this result of this research, based the theory of Chinese prosodic words, shown that the earlier the students get trained on prosodics at the beginning and suprasegmentals at intermediate and advanced levels, the better effects for them to communicate in Chinese as a second language.

Keywords: second language, prosodic word, foot, suprasegmental

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Authors: Azizah Hashim, Rohana Ngah

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Transformation of Economic Development is aimed to transform Malaysia to become a high-income developed nation with a knowledge-based economy by 2020. To achieve this national agenda, the country needs to further strengthen its economic development, growth and well-being. Therefore, this study aspires to examine the relationship between market orientation, human resource management and adoption of information communication technology and SMEs performance and cash management as a mediator. This study will employ quantitative approaches. Questionnaires will be distributed to managers and owners in service sectors. The data collected will be analyzed using SPSS and Structural Equation Modelling. Resource Based Theory (RBT) adopts as an integral part of management literature that explains the performance of organizations through building resources and implement of their strategies.

Keywords: small medium enterprises (SMEs), market orientation, human resource management, adoption of information communication technology

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Authors: Wasim Orfali, Hesham Tolba

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This research investigates the acoustical characteristics of Al-Madinah Holy Mosque. Extensive field measurements were conducted in different locations of Al-Madinah Holy Mosque to characterize its acoustic characteristics. The acoustical characteristics are usually evaluated by the use of objective parameters in unoccupied rooms due to practical considerations. However, under normal conditions, the room occupancy can vary such characteristics due to the effect of the additional sound absorption present in the room or by the change in signal-to-noise ratio. Based on the acoustic measurements carried out in Al-Madinah Holy Mosque with and without occupancy, and the analysis of such measurements, the existence of acoustical deficiencies has been confirmed.

Keywords: Al-Madinah Holy Mosque, mosque acoustics, speech intelligibility, worship sound

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Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

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Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R² of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

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Authors: Mohammed Umar Manko

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A series of batch experiments were conducted in order to investigate the feasibility of Balanitesaegyptiaca seeds based activated carbon as compared with industrial activated carbon for the removal of chromium and lead ions from aqueous solution by the adsorption process within 30 to 150 minutes contact time. The activated samples were prepared using zinc chloride and tetraoxophophate(VI) acid. The results obtained showed that the activated carbon of Balanitesaegyptiaca seeds studied had relatively high adsorption capacities for these heavy metal ions compared with industrial Activated Carbon. The percentage removal of Cr (VI) and lead (II) ions by the three activated carbon samples were 64%, 70% and 71%; 60%, 66% and 60% respectively. Adsorption equilibrium was established in 90 minutes for the heavy metal ions. The equilibrium data fitted the pseudo second order out of the pseudo first, pseudo second, Elovich ,Natarajan and Khalaf models tested. The investigation also showed that the adsorbents can effectively remove metal ions from similar wastewater and aqueous media.

Keywords: activated carbon, pseudo second order, chromium, lead, Elovich model

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Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

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Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

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Authors: Naima Boudieb, Mohamed Loucif Seaid, Imad Rati, Imane Benammane

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The aim of this study is to synthesis of a copolymer PANI/PEDOT:PSS by electrochemical means to apply in supercapacitors. Polyaniline (PANI) is a conductive polymer; it was synthesized by electrochemical polymerization. It exhibits very stable properties in different environments, whereas PEDOT:PSS is a conductive polymer based on poly(3,4-ethylenedioxythiophene) (PEDOT) and poly(styrene sulfonate)(PSS). It is commonly used with polyaniline to improve its electrical conductivity. Several physicochemical and electrochemical techniques were used for the characterization of PANI/PEDOT:PSS: cyclic voltammetry (VC), electrochemical impedance spectroscopy (EIS), open circuit potential, SEM, X-ray diffraction, etc. The results showed that the PANI/PEDOT:PSS composite is a promising material for supercapacitors due to its high electrical conductivity and high porosity. Electrochemical and physicochemical characterization tests have shown that the composite has high electrical and structural performances, making it a material of choice for high-performance energy storage applications.

Keywords: energy storage, supercapacitors, SIE, VC, PANI, poly(3, 4-ethylenedioxythiophene, PEDOT, polystyrene sulfonate

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Authors: Kumar N., Verma S., Park J., Srivastava V. C.

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Organic carbonates have the potential to be used as fuels and because of this, their production through non-phosgene routes is a thrust area of research. Di-ethyl carbonate (DEC) synthesis from propylene carbonate (PC) in the presence of alcohol is a green route. In this study, the use of reduced graphene oxide (rGO) based metal oxide catalysts [rGO-MO, where M = Ce] with different amounts of graphene oxide (0.2%, 0.5%, 1%, and 2%) has been investigated for the synthesis of DEC by using PC and ethanol as reactants. The GO sheets were synthesized by an electrochemical process and the catalysts were synthesized using an in-situ method. A theoretical study of the thermodynamics of the reaction was done, which revealed that the reaction is mildly endothermic. The theoretical value of optimum temperature was found to be 420 K. The synthesized catalysts were characterized for their morphological, structural and textural properties using field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), N2 adsorption/desorption, thermogravimetric analysis (TGA), and Raman spectroscopy. Optimization studies were carried out to study the effect of different reaction conditions like temperature (140 °C to 180 °C) and catalyst dosage (0.102 g to 0.255 g) on the yield of DEC. Amongst the various synthesized catalysts, 1% rGO-CeO2 gave the maximum yield of DEC.

Keywords: GO, DEC, propylene carbonate, transesterification, thermodynamics

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Authors: B. Varaprasad, C. Srinivasa Rao

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Hard turning has been explored as an alternative to the conventional one used for manufacture of Parts using tool steels. In the present study, the effects of cutting speed, feed rate and Depth of Cut (DOC) on cutting forces, specific cutting force, power and surface roughness in the hard turning are experimentally investigated. Experiments are carried out using mixed ceramic(Al2O3+TiC) cutting tool of corner radius 0.8mm, in turning operations on AISI H13 tool steel, heat treated to a hardness of 62 HRC. Based on Design of Experiments (DOE), a total of 20 tests are carried out. The range of each one of the three parameters is set at three different levels, viz, low, medium and high. The validity of the model is checked by Analysis of variance (ANOVA). Predicted models are derived from regression analysis. Comparison of experimental and predicted values of specific cutting force, power and surface roughness shows that good agreement has been achieved between them. Therefore, the developed model may be recommended to be used for predicting specific cutting force, power and surface roughness in hard turning of tool steel that is AISI H13 steel.

Keywords: hard turning, specific cutting force, power, surface roughness, AISI H13, mixed ceramic

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

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Contemporary cities are facing serious congestion and parking problems. In urban transport policy the introduction of the park and ride system (P&R) is an increasingly popular way of limiting vehicular traffic. The determining of P&R facilities location is a key aspect of the system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. The research outsourced to specialists are expensive and time consuming. The most focus is on the examination of a few selected places. The practice has shown that the choice of the location of these sites in a intuitive way without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. Methods of location as a research topic are also widely taken in the scientific literature. Built mathematical models often do not bring the problem comprehensively, e.g. assuming that the city is linear, developed along one important communications corridor. The paper presents a new method where the expert knowledge is applied to fuzzy inference model. With such a built system even a less experienced person could benefit from it, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed location can also be verified in a short time. The proposed method is intended for testing of car parks location in a city. The paper will show selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analysis of existing objects will also be shown in the paper and they will be confronted with the opinions of the system users, with particular emphasis on unpopular locations. The research are executed using the fuzzy inference model which was built and described in more detail in the earlier paper of the authors. The results of analyzes are compared to documents of P&R facilities location outsourced by the city and opinions of existing facilities users expressed on social networking sites. The research of existing facilities were conducted by means of the fuzzy model. The results are consistent with actual users feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. The performed studies show that the method has been confirmed. The method can be applied in urban planning of the P&R facilities location in relation to the accompanying functions. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: fuzzy logic inference, park and ride system, P&R facilities, P&R location

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Wajiha Fatima

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Based on Rod Ellis’s (2002) the methodology of task-based teaching, this study explored the effects of pre-task activities on the Job Application letter of 102 ESL students (who were female and undergraduate learners). For this purpose, students were divided among three groups (Group A, Group B, and Group C), kept in control and experimental settings as well. Pre-task phase motivates the learners to perform the actual task. Ellis reportedly discussed four pre-task phases: (1) performing a similar task; (2) providing a model; (3) non-task preparation activities and (4) strategic planning. They were taught through above given three pre-task activities. Accordingly, the learners in control setting were supposed to write without any teaching aid while learners in an experimental situation were provided three different pre-task activities in each group. In order to compare the scores of the pre-test and post-test of the three groups, sample paired t-test was utilized. The obtained results of the written job application by the female students revealed that pre-task activities improved their performance in writing. On the other hand, the comparison of the three pre-task activities revealed that 'providing a model' outperformed the other two activities. For this purpose, ANOVA was utilized.

Keywords: pre-task activities, second language learners, task based language teaching, writing

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: Xiao Wang, Qinge Zhang

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Background: This randomized, open-label study examined the therapeutic effects of computerized cognitive training (CCT) combined with selective serotonin reuptake inhibitors (SSRIs) on cognitive impairment among patients with late-life depression (LLD). Method: Study data were collected from May 5, 2021, to April 21, 2023. Outpatients who met diagnostic criteria for major depressive disorder according to the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria (i.e., a total score on the 17-item Hamilton Depression Rating Scale (HAMD-17) ≥ 18 and a total score on the Montreal Cognitive Assessment scale (MOCA) <26) were randomly assigned to receive up to 12 weeks of CCT and SSRIs treatment (n=57) or SSRIs and Control treatment (n=61). The primary outcome was the change in Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores from baseline to week 12 between the two groups. The secondary outcomes included changes in the HAMD-17 score, Hamilton Anxiety Scale (HAMA) score and Neuropsychiatric Inventory (NPI) score. Mixed model repeated measures (MMRM) analysis was performed on modified intention-to-treat (mITT) and completer populations. Results: The full analysis set (FAS) included 118 patients (CCT and SSRIs group, n=57; SSRIs and Control group, n =61). Over the 12-week study period, the reduction in the ADAS-cog total score was significant (P < 0.001) in both groups, while MMRM analysis revealed a significantly greater reduction in cognitive function (ADAS-cog total scores) from baseline to posttreatment in the CCT and SSRIs group than in the SSRI and Control group [(F (1,115) =13.65, least-squares mean difference [95% CI]: −2.77 [−3.73, −1.81], p<0.001)]. There were significantly greater improvements in depression symptoms (measured by the HAMD-17) in the CCT and SSRIs group than in the control group [MMRM, estimated mean difference (SE) between groups −3.59 [−5.02, −2.15], p < 0.001]. The least-squares mean changes in the HAMA scores and NPI scores between baseline and week 8 were greater in the CCT and SSRIs group than in the control group (all P < 0.05). There was no significant difference between groups on response rates and remission rates by using the last-observation-carried-forward (LOCF) method (all P > 0.05). The most frequent adverse events (AEs) in both groups were dry mouth, somnolence, and constipation. There was no significant difference in the incidence of adverse events between the two groups. Conclusions: CCT combined with SSRIs was efficacious and well tolerated in LLD patients with cognitive impairment.

Keywords: late-life depression, cognitive function, computerized cognitive training, SSRIs

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Authors: Georg Brunnthaller, Sandra Stein, Wilfried Sihn

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Logistics service providers are facing increasing volatility concerning future transport demand. Short-term planning horizons and planning uncertainties lead to reduced capacity utilisation and increasing empty mileage. To overcome these challenges, a model is proposed to continuously pre-plan future transport capacity in order to redesign and adjust the intermodal fleet accordingly. It is expected that the model will enable logistics service providers to organise more economically and ecologically sustainable transport chains in a more flexible way. To further describe such planning aspects, this paper gives a structured literature review on transport planning problems. The focus is on strategic and tactical planning levels, comprising relevant fleet-sizing-, network-design- and choice-of-carriers-problems. Models and their developed solution techniques are presented and the literature review is concluded with an outlook to our future research objectives

Keywords: choice of transport mode, fleet-sizing, freight transport planning, multimodal, review, service network design

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Authors: Vadim Kulikov

Abstract:

The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

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Authors: Geon Bae, Cheol Hee Moon

Abstract:

Organic Light Emitting Diodes (OLEDs) are being developed rapidly as next-generation displays due to their self-luminous and flexible characteristics. OLEDs are highly susceptible to moisture and oxygen due to their structural properties. Thus, requiring a high level of encapsulation technology. Recently, encapsulation technology such as Thin Film Encapsulation (TFE) has been developed for OLED, but it is not perfect to prevent moisture permeation on the side. In this study, we propose OLED encapsulation method using Low melting Point Alloy (LMPA). The LMPA line was designed in square box shape on the outer edge of the device and was formed by screen printing method. To determine if LMPA has an effect on OLED, we fabricated solution processed OLEDs with a square-shaped LMPA line and evaluate the I-V-L characteristics of the OLEDs. Also, the resistance characteristic of the LMPA line was observed by repeatedly bending the LMPA line. It is expected that LMPA encapsulation will have a great advantage in shortening the process time and cost reduction.

Keywords: OLED, encapsulation, LMPA, solution process

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Authors: Nellija Titova

Abstract:

Latvia, Lithuania, and Estonia, as Baltic Countries, have gone throughout transformational changes since 90s leading to the high level of economic development. As countries departing Soviet Union with industrialization policy moved to service economies, the issues of intangibles, human capital, structural capital, and innovation capital have gained impetus. Following the growing demand of practitioners and later academia, intellectual capital as a discipline, which appeared in 90s, became fundamental nowadays. Aim of the paper is to analyze the Baltic companies entering stock markets at Nasdaq Baltic from the perspective of Intellectual Capital. Methodology of the research is based on a longitudinal analysis of the companies using composite ratios of Intellectual Capital and Business performance in the period 2012-2019. Data for 2020 as COVID year) were excluded from the analysis. Findings allow concluding there is a pattern of influence and companies clearly experience the systemic impact of IC on business performance, identifying also time effect investing in intangibles.

Keywords: intellectual capital, impact analysis, longitudinal effect, composite ratios

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Authors: Sajjad Yahaghifar

Abstract:

From the end of the last century, the importance and use of renewable energy sources have gained prominence, due not only by the fossil fuels dependence reduction, but mainly by environmental reasons related to climate change and the effects to the humanity. Consequently, solar energy has been arousing interest in several countries for being a technology considered clean, with reduced environmental impact. The output power of photo voltaic (PV) arrays is always changing with weather conditions,i.e., solar irradiation and atmospheric temperature. Therefore, maximum power point tracking (MPPT) control to extract maximum power from the PV arrays at real time becomes indispensable in PV generation system. This paper Study MPPT and total harmonic distortion (THD) in the city of Tabriz, Iran with the grid-connected PV system as distributed generation.

Keywords: MPPT, THD, grid-connected, PV system

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Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

Abstract:

This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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Authors: A. Khodadadi, Hasani, Salehi

Abstract:

The advantages of using modified asphalt binders are widely recognized—primarily, improved rutting resistance, reduced fatigue cracking and less cold-temperature cracking. Nanoclays are known to enhance the properties of many polymers. Nanoclays are used to improve modulus and tensile strength, flame resistance and thermal and structural properties of many materials. This paper intends to investigate the application and development of nano-technological concepts for bituminous materials and asphalt pavements. The application of nano clay on the fatigue life of asphalt pavement have not been yet thoroughly understood. In this research, two type of highway asphalt materials, dense Marshall specimens, with 2% nano clay and without nano clay, were employed for the fatigue behavior of the asphalt pavement.The effect of nano additive on the performance of flexible pavements has been investigated through the indirect tensile test for the samples prepared with 2% nano clay and without nano clay in four stress levels from 200–500 kPa. The primary results indicated samples with 2% nano clay have almost double or even more fatigue life in most of stress levels.

Keywords: Nano clay, Asphalt, fatigue life, pavement

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