Search results for: effective Lagrangian approach

Authors: Muhammad Awais Kiani, Maryam Kiani

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This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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Authors: Evgen Prokhorov, Gabriel Luna-Barcenas

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The polysaccharide chitosan (CS) is an attractive biopolymer for the stabilization of several nanoparticles in acidic aqueous media. This is due in part to the presence of abundant primary NH2 and OH groups which may lead to steric or chemical stabilization. Applications of most CS nanocomposites are based upon the interaction of high surface area nanoparticles (NPs) with different substance. Therefore, agglomeration of NPs leads to decreasing effective surface area such that it may decrease the efficiency of nanocomposites. The aim of this work is to measure nanocomposite’s electrical conductivity phenomena that will allow one to formulate optimal concentrations of conductivity NPs in CS-based nanocomposites. Additionally, by comparing the efficiency of such nanocomposites, one can guide applications in the biomedical (antibacterial properties and tissue regeneration) and sensor fields (detection of copper and nitrate ions in aqueous solutions). It was shown that the best antibacterial (CS-AgNPs, CS-AgNPs-carbon nanotubes) and would healing properties (CS-AuNPs) are observed in nanocomposites with concentrations of NPs near the percolation threshold. In this regard, the best detection limit in potentiometric and impedimetric sensors for detection of copper ions (using CS-AuNPs membrane) and nitrate ions (using CS-clay membrane) in aqueous solutions have been observed for membranes with concentrations of NPs near percolation threshold. It is well known that at the percolation concentration of NPs an abrupt increasing of conductivity is observed due to the presence of physical contacts between NPs; above this concentration, agglomeration of NPs takes place such that a decrease in the effective surface and performance of nanocomposite appear. The obtained relationship between electrical percolation threshold and performance of polymer nanocomposites with conductivity NPs is important for the design and optimization of polymer-based nanocomposites for different applications.

Keywords: chitosan, conductivity nanoparticles, percolation threshold, polymer nanocomposites

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Authors: Tsz Ching Jasmine Lam

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Linguistic landscape (LL) can serve as both top-down and bottom-up approaches to understanding language planning policy in various dimensions. It can reflect the language identities, motives and contestations perceived by stakeholders of different decision-making levels. Prior studies adopted the bottom-up approach to investigate the language practice and ideologies reflected by the design and linguistic features observed in the linguistic landscapes in ethnically and linguistically diverse areas, like Medan in Russia and Seoul in Korea. As Hong Kong is also a trilingual city with an inclusive combination of nationalities, this paper is intended to take it as a case study to explore the de facto language ideologies reflected by LL at the micro-level. We would look into the catering industry from a holistic perspective by reviewing the food menus of 66 restaurants located in diversified districts and serving different types of cuisines. This bottom-up LL research reveals that business owners and the public share the language ideologies of perceiving English as a prestigious language, multilingualism and traditional Chinese as a standard character.

Keywords: bottom-up, language ideologies, language planning policy, language policy, language identities, linguistic landscape

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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Authors: Kasman, Darmawansyah, Alimin Maidin, Amran Razak

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Background: In decentralization, advocacy is needed to increase the health budget in Parepare District. One of the advocacy methods recommended by the World Bank is the economic loss approach. Methods: This research is observational in the field of health economics that contributes directly to the magnitude of the economic loss of the community and the government and provides advocacy to the executive and legislative to see the harm it causes. Results: The research results show the amount of direct cost, which consists of household expenditure for transport Rp.295,865,500. Indirect Cost of YLD of Rp.14.688.000, and YLL of Rp.28.986.336.00, so the amount of DALY is Rp.43.674.336.000. The total economic loss of Rp.43.970.201.500. These huge economic losses can be prevented by increasing the allocation of health budgets for promotive and preventive efforts and expanding the coverage of health insurance for the community. Conclusion: There is a need to advocate the executive and legislative about the importance of guarantee on public health financing by conducting studies in terms of economic losses so that all strategic alliances believe that health is an investment.

Keywords: advocacy, economic lost, health insurance, economic losses

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Authors: Mohammad Sadegh Allahyari, Sorush Marzban

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The main aim of this study was to investigate the factors affecting farmers' attitude of the Shanderman District in Masal (Guilan Province in the north of Iran), towards the concepts of multifunctional agriculture. The statistical population consisted of all 4908 in Shanderman.The sample of the present study consisted of 209 subjects who were selected from the total population using the Bartlett et al. Table. Questionnaire as the main tool of data collection was divided in two parts. The first part of questionnaire consisted of farmers' profiles regarding individual, technical-agronomic, economic and social characteristics. The second part included items to identify the farmers’ attitudes regarding different aspects of multifunctional agriculture. The validity of the questionnaire was assessed by professors and experts. Cronbach's alpha was used to determine the reliability (α= 0.844), which is considered an acceptable reliability value. Overall, the average scores of attitudes towards multifunctional agriculture show a positive tendency towards multifunctional agriculture, considering farmers' attitudes of the Shanderman district (SD = 0.53, M = 3.81). Results also highlight a significant difference between farmers' income source levels (F = 0.049) and agricultural literature review (F = 0.022) toward farmers' attitudes considering multifunctional agriculture (p < 0.05). Pearson correlations also indicated that there is a positive relationship between positive attitudes and family size (r = 0.154), farmers' experience (r = 0.246), size of land under cultivation (r = 0.186), income (r = 0.227), and social contribution activities (r = 0.224). The results of multiple regression analyses showed that the variation in the dependent variable depended on the farmers' experience in agricultural activities and their social contribution activities. This means that the variables included in the regression analysis are estimated to explain 12 percent of the variation in the dependent variable.

Keywords: multifunctional agriculture, attitude, effective factor, sustainable agriculture

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Authors: Jafar W. Al-Badarneh, Abdalkareem R. Al-Hawary, Abdulmalik M. Morghem, Mostafa Z. Ali, Rami S. Al-Gharaibeh

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Archeological heritage is at the heart of each country’s national glory. Moreover, it could develop into a source of national income. Heritage management requires socially-responsible marketing that achieves high visitor satisfaction while maintaining high site conservation. We have developed an Augmented Reality (AR) experience for heritage and cultural reservation at Dar-As-Saraya museum in Jordan. Our application of this notion relied on markerless-based tracking approach. This approach uses keypoints extraction technique where features of the environment are identified and defined into the system as keypoints. A set of these keypoints forms a tracker for an augmented object to be displayed and overlaid with a real scene at Dar As-Saraya museum. We tested and compared several techniques for markerless tracking and then applied the best technique to complete a mosaic artifact with AR content. The successful results from our application open the door for applications in open archeological sites where markerless tracking is mostly needed.

Keywords: augmented reality, cultural heritage, keypoints extraction, virtual recreation

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Authors: Sharafat Karimi, Jamil Jafari

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The impact of Western Literature on other nations' pieces of literature (including Arabic) has caused critics to ignore the importance of Arabic cultural & literary heritage in the formation of contemporary Arabic fiction; but on the contrary, an important part of literary genres in any society, especially fiction has been formed in the past and depends on ancient literary events. The current paper, utilizing the descriptive-analytical method and by means of library studies, tries to challenge those critics who regard Western Literature as the only effective factor on the appearance of Arabic fiction. Furthermore, this research tries to find out effective Islamic-Arabic elements on the development of Arabic novel by the investigation of some fictional works. The results show that in addition to regarding Western literature as an important factor, Arab novelists have applied their heritage, culture, and ancient history, either written or orally transmitted to the current generation, in their innovations. Among great historical works containing moral stories, allegorical legends, myths, tales of heroes, and folklore, we can refer to Arabian Nights, Kalila & Dimna, romantic stories, historical puzzles, history of Islam, history of ancient Egypt, Maqama, and Quranic stories. Famous novels like 'Hadith Isa ibn-Hisham', 'Layali Alif Layla', 'Abas al-Aqdar', 'Radoubis', 'Ahlam Shahrzad, and 'Alam Bela Kharaet' were compiled on the basis of ancient literary heritage not only in the theme but also in the structure; so one can conclude that the ancient literary-cultural heritage and Islamic-Arabian history have been influential on Arabic novel appearance and development.

Keywords: Arabic fictional literature, culture, heritage, history, language, novel

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Authors: Pratap Sing, Chaman. K. Jadon, H. P. Meena, D. L.yadav, S. L. Yadav, Uditi Dhakad

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The experiment was conducted at Agricultural Research Station, Agriculture University, Kota, Rajasthan, India during kharif and rabi 2020-21 and 2021-22 to study the biofficacy of diclosulam and its residual effect on succeeding wheat crop. The treatments comprised of Diclosulam 84 % WDG viz. 6.25, 12.50, 25.00 and 37.50 g/ha as pre emergence (PE), Pendimethalin 30% EC 3.33 l/ha, Sulfentrazon 48% SC 750 g/ha, hand weeding at 30 and 45 DAS and weedy check, were evaluated in randomized block design in three replications. The experimental soil was clay in texture and non-calcareous. Experimental field was mainly dominated by grasses-Echinochloa colonum, E.crusgalli,Cynodon dactylon, Sedges-Cyperus rotundus and broad leaved weeds Celosia argentea and Digera arvensis.The result revealed that application of Diclosulam 84 % WDG 25 g/ha PE was found effective in controlling mostly weed species and registered higher weed control efficiency 81.2, 74.3, 69.6 per cent at 30, 45 days after sowing and at harvest. Diclosulam 84 % WDG (6.25-25.0 g/ha) was found selective to the soybean crop as no any phytotoxicity symptoms were observed. Among the herbicidal treatments, Diclosulam 84 % WDG 25 g/ha registered maximum and significantly higher soybean seed yield (1889 and 1431 kg/ha during kharif 2020 and 2021, respectively and was at par with Sulfentrazone 48% SC 750 g/ha and over weedy check( 1027 and 667 kg/ha).The wheat crop growth, yield attributes and seed yield were not influenced due to carry over effect of the Diclosulam 84 % WDG( 6.25-25.0 g/ha) and no any phytotoxicity symptoms were observed. Henceforth, the Diclosulam 84 % WDG 25.0 g/ha as pre emergence may be used in the soybean for effective weed control without carry over effect on succeeding wheat crop.

Keywords: Diclosulam, soybean, carry over effect, succeeding wheat

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Authors: Bahadir Aydin

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It is difficult to access accurate knowledge because of mass data. This huge data make environment more and more caotic. Data are main piller of intelligence. The affiliation between intelligence and knowledge is quite significant to understand underlying truths. The data gathered from different sources can be modified, interpreted and classified by using intelligence cycle process. This process is applied in order to progress to wisdom as well as intelligence. Within this process the effect of tacit knowledge is crucial. Knowledge which is classified as explicit and tacit knowledge is the key element for any purpose. Tacit knowledge can be seen as "the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence cycle is scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose of all organizations is to be successful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. Thanks to this process the decision-makers can be presented with a clear holistic understanding, as early as possible in the decision making process. Altering from the current traditional reactive approach to a proactive intelligence cycle approach would reduce extensive duplication of work in the organization. Applying new result-oriented cycle and tacit knowledge intelligence can be procured and utilized more effectively and timely.

Keywords: information, intelligence cycle, knowledge, tacit Knowledge

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Mustafa Eruyar, Ersoy Pehlivan, Fatih Kafalı, Fatih Gundogan

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All megacities are not only under the pressure of common urbanization and growth problems but also dealing with different challenges according to their specific circumstances. However, the majority of cities focuses mainly on popular smart city projects, which are usually driven by strong private sector, regardless of their characteristics, each city needs to develop customized projects within a tailor-made smart city roadmap to be able to solve its own challenges. Smart city manifest, helps citizens to feel the action better than good reading smart city vision statements, which consists of five elements; namely purpose, values, mission, vision, and strategy. This study designs a methodology for smart city roadmap based on a top-down approach, breaking down of smart city manifest to feasible projects for a systematic smart city transformation. This methodology was implemented in Istanbul smart city transformation program which includes smart city literature review, current state analysis, roadmap, and architecture projects, respectively. Istanbul smart city roadmap project followed an extensive literature review of certain leading smart cities around the world and benchmarking of the city’s current state using well known smart city indices. In the project, needs of citizens and service providers of the city were identified via stakeholder, persona and social media analysis. The project aimed to develop smart city projects targeting fulfilling related needs by implementing a gap analysis between current state and foreseen plans. As a result, in 11 smart city domains and enablers; 24 strategic objectives, 50 programs, and 101 projects were developed with the support of 183 smart city stakeholder entities and based on 125 citizen persona profiles and last one-year social media analysis. In conclusion, the followed methodology helps cities to identify and prioritize their needs and plan for long-term sustainable development, despite limited resources.

Keywords: needs-based, manifest, roadmap, smart city, top-down approach

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Authors: Xhevrie Mamaqi

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Organization capacity learning is a process referring to the sum total of individual and collective learning through training programs, experience and experimentation, among others. Today, in-business ongoing training is one of the most important strategies for human capital development and it is crucial to sustain and improve workers’ knowledge and skills. Many organizations, firms and business are adopting a strategy of continuous learning, encouraging employees to learn new skills continually to be innovative and to try new processes and work in order to achieve a competitive advantage and superior business results. This paper uses the Resource Based View and Capacities (RBV) approach to construct a hypothetical relationships model between training and business results. The test of the model is applied on transversal data. A sample of 266 business of Spanish sector service has been selected. A Structural Equation Model (SEM) is used to estimate the relationship between ongoing training, represented by two latent dimension denominated Human and Social Capital resources and economic business results. The coefficients estimated have shown the efficient of some training aspects explaining the variation in business results.

Keywords: business results, human and social capital resources, training, RBV theory, SEM

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Authors: Akbar Farahani, Afsaneh Hassani, Peyman M. Farkhondeh

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Human Resource Management as one of the core processes of the project-based companies, despite its key role in the success and competitive advantage, is relatively unknown. In the project-based companies, due to the accelerated movement of knowledge in the work activities and the temporary nature of the project, the need to develop mechanisms for achieving optimal management of this issues is very challenging. Approach to human resource management in these companies evolves with goals, strategies, and operational processes. Therefore, the need for appropriate tools to facilitate implementation of the optimized human resource management in the project is more than before,Which currently with the development of information technology and modern communication, appropriate to address the optimal approach for dynamic management of human resources in the project have been provided.This is done by using the referral system implemented in Mahab GCE that provides 1: the ability to use humans in projects without geographic limitation and 2:information on the activities and outcomes of referrals.Furthermore, by using this system, recording the lessons learned after any particular activity on projects,accessing quantitative information, procedures, documentation of learned practices that have been stored in the data base as well as using them in future projects is provided.

Keywords: human resource management, project base company, ERP, referrals system

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Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

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Authors: R. Hosny, Mahmoud F. Mubarak, Heba M. Salem, Asmaa A. Abdelrahman

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Oilfield scaling is a major problem in the oil and gas industry. Scale issues cost the industry millions of dollars in damage and lost production every year. One of the main causes of global production decline is scale. In this study, solid scale inhibitors based on silver tungstate loaded KIT-6 were synthesized and evaluated in both static and scale inhibition modeling. The silver tungstate loaded KIT-6 catalysts were synthesized via a simple impregnated method using 3D mesoporous KIT-6 as support. The synthesized materials were characterized using wide and low XRD, N2 adsorption–desorption analysis, TGA analysis, and FTIR, SEM, and XPS analysis. The scale inhibition efficiency of the synthesized materials was evaluated using a static scale inhibition test. The results of this study demonstrate the potential application of silver tungstate-loaded KIT-6 solid scale inhibitors for the oil and gas industry. The results of this study will contribute to the development of new and innovative solid scale inhibitors based on silver tungstate-loaded KIT-6. The inhibition efficiency of the scale inhibitor increases, and calcite scale inhibitor decreases with increasing pH (2 to8), it proposes that the scale inhibitor was more effective under alkaline conditions. An inhibition efficiency of 99% on calcium carbonate can be achieved at the optimal dosage of 7.5 ppm at 55oC, indicating that the scale inhibitor exhibits a relatively good inhibition performance on calcium carbonate. The use of these materials can potentially lead to more efficient and cost-effective solutions for scaling inhibition in various industrial processes.

Keywords: produced water treatment, solid scale inhibitors, calcite, silver tungestate, 3 D mesoporous KIT-6, oilfield scales, adsorption

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Authors: Smriti, Ajeet Kumar

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We present a variant of the Irving-Kirkwood procedure to obtain the microscopic expressions of the cross-section averaged continuum fields such as internal force and moment in one-dimensional nanostructures in the non-equilibrium setting. In one-dimensional continuum theories for slender bodies, we deal with quantities such as mass, linear momentum, angular momentum, and strain energy densities, all defined per unit length. These quantities are obtained by integrating the corresponding pointwise (per unit volume) quantities over the cross-section of the slender body. However, no well-defined cross-section exists for these nanostructures at finite temperature. We thus define the cross-section of a nanorod to be an infinite plane which is fixed in space even when time progresses and defines the above continuum quantities by integrating the pointwise microscopic quantities over this infinite plane. The method yields explicit expressions of both the potential and kinetic parts of the above quantities. We further specialize in these expressions for helically repeating one-dimensional nanostructures in order to use them in molecular dynamics study of extension, torsion, and bending of such nanostructures. As, the Irving-Kirkwood procedure does not yield expressions of stiffnesses, we resort to a thermodynamic equilibrium approach to obtain the expressions of axial force, twisting moment, bending moment, and the associated stiffnesses by taking the first and second derivatives of the Helmholtz free energy with respect to conjugate strain measures. The equilibrium approach yields expressions independent of kinetic terms. We then establish the equivalence of the expressions obtained using the two approaches. The derived expressions are used to understand the extension, torsion, and bending of single-walled carbon nanotubes at non-zero temperatures.

Keywords: thermoelasticity, molecular dynamics, one dimensional nanostructures, nanotube buckling

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Authors: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Weikang Gong, Chunhua Li

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Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

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Authors: Isaiah Phillip Smith, Sam Erevbenagie Usadolo, Pamela Theresa Tancsik

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This paper is part of ongoing doctoral research that examines the role of Theatre for Development (TfD) in addressing climate change in the Mosuthu community in Reservoir Hills, Durban, South Africa. The context of the research underscores the pressing challenges facing South Africa, including drought, water shortages, deterioration of land, and civil unrest that require innovative approaches to the mitigation of climate change. TfD, described as a dialogical form of theatre that allows communities to express and contribute to development, emerges as a strategic medium for engaging communities in the process. The research problem focused on the unexamined potential of TfD in promoting community involvement and critical awareness of climate change. The study objectives included assessing the community's understanding of climate change, exploring TfD's potential as a participatory tool, examining its role in community mobilization, and developing recommendations for its effective implementation. A review of relevant literature and preliminary investigations in the research community indicates that TfD is an effective medium for promoting societal transformation and engaging marginalized communities. Through culturally resonant narratives, TfD can instill a deeper understanding of environmental challenges, fostering empathy and motivating behavioural changes. By integrating community voices and cultural elements, TfD serves as a powerful catalyst for promoting climate change awareness and inspiring collective action within the South African context. This research contributes to the global discourse on innovative approaches to climate change awareness and action.

Keywords: TfD, climate change, community involvement, societal transformation, culture

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Authors: Muogbo Chukwudi Peter, Gbabo Agidi

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Influence of different turmeric rhizome sizes and machine operational speed on the field capacity and efficiency of a developed prototype tractor-drawn turmeric planter was studied. This was done with a view to ascertaining how the field capacity and field efficiency were affected by the turmeric rhizome lengths and tractor operational speed. The turmeric rhizome planter consists of trapezoidal hopper, grooved cylindrical metering devise, rectangular frame, ground wheels made of mild steel, furrow opener, chain/sprocket drive system, three linkage point seed delivery tube and press wheel. The experiment was randomized in a factorial design of three levels of rhizome lengths (30, 45 and 60 mm) and operational speeds of 8, 10, and 12 kmh-1. About 3 kg cleaned turmeric rhizomes were introduced into each hopper of the planter and were planted 30 m2 of experimental plot. During the field evaluation of the planter, the effective field capacity, field efficiency, missing index, multiple index and percentage rhizome bruise were evaluated. 30.08% was recorded for maximum percentage bruise on the rhizome. The mean effective field capacity ranged between 0.63 – 0.96hah-1 at operational speeds of 8 and 12kmh-1 respectively and 45 mm rhizome length. The result also shows that the mean efficiency was obtained to be 65.8%. The percentage rhizome bruise decreases with increase in operational speed. The highest and lowest percentage turmeric rhizome miss index of 35% were recorded for turmeric rhizome length of 30 mm at a speed of 10 kmhr-1 and 8 kmhr-1, respectively. The potential implications of the experimental result is to determine the optimal machine process conditions for higher field capacity and gross reduction in mechanical injury (bruise) of planted turmeric rhizomes.

Keywords: rhizome sizes, operational speed, field capacity. field efficiency, turmeric rhizome, planter

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Authors: Mahsaossadat Pourrahmati Khelejan

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The purpose of this research was to identify and prioritize the sustainable development of sports venues using new and degradable energies with using the AHP Hierarchical Analysis approach. The research method is a descriptive strategy with regard to the direction of implementation and is a hierarchical research with a practical purpose. In this study, 30 experts (physical education faculty members, geography professors, accredited sports venues managers, and renewable energy engineers) were selected using purposeful sampling method as the research population. The research tool was a researcher-made questionnaire on the factors affecting the sustainable development of sports venues by using new technologies and degradable energy. Finally, the research questionnaire was designed with four components and 21 items. All steps were performed by using Expert Choice software. The importance of indicators that influence the sustainable development of sports venues is highlighted by the use of clean and degradable energy, for example: 1. Economic factor, weighing 0.420 2. Environmental index, weighing 0. 320 3. Physical index, weighing 0.148 4. Social index, weighing 0.122.

Keywords: Sports Venues, Sustainable Development, Degradable Energies, Prioritize

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Authors: D. Farsi, G. Dokhtvasi, S. Abbasi, S. Shafiee Ardestani, E. Payani

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Background and aim:It has not been well studied whether fentanyl-thiopental (FT) is effective and safe for PSA in orthopedic procedures in Emergency Department (ED). The aim of this trial was to evaluate the effectiveness of intravenous FTversusfentanyl-midazolam (FM)in patients who suffered from shoulder dislocation or distal radial fracture-dislocation. Methods:In this randomized double-blinded study, Seventy-six eligible patients were entered the study and randomly received intravenous FT or FM. The success rate, onset of action and recovery time, pain score, physicians’ satisfaction and adverse events were assessed and recorded by treating emergency physicians. The statistical analysis was intention to treat. Results: The success rate after administrating loading dose in FT group was significantly higher than FM group (71.7% vs. 48.9%, p=0.04); however, the ultimate unsuccess rate after 3 doses of drugs in the FT group was higher than the FM group (3 to 1) but it did not reach to significant level (p=0.61). Despite near equal onset of action time in two study group (P=0.464), the recovery period in patients receiving FT was markedly shorter than FM group (P<0.001). The occurrence of adverse effects was low in both groups (p=0.31). Conclusion: PSA using FT is effective and appears to be safe for orthopedic procedures in the ED. Therefore, regarding the prompt onset of action, short recovery period of thiopental, it seems that this combination can be considered more for performing PSA in orthopedic procedures in ED.

Keywords: procedural sedation and analgesia, thiopental, fentanyl, midazolam, orthopedic procedure, emergency department, pain

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Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

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There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: Jiangbo Li, Wenqian Huang

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Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

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Authors: Sateesh Kumar Pisini, Swetha Priya Darshini, Sanjay Kumar Shukla

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This paper seeks to present a research study on sustainability in construction of retaining wall using geosynthetics. Sustainable construction is a way for the building and infrastructure industry to move towards achieving sustainable development, taking into account environmental, socioeconomic and cultural issues. Geotechnical engineering, being very resource intensive, warrants an environmental sustainability study, but a quantitative framework for assessing the sustainability of geotechnical practices, particularly at the planning and design stages, does not exist. In geotechnical projects, major economic issues to be addressed are in the design and construction of stable slopes and retaining structures within space constraints. In this paper, quantitative indicators for assessing the environmental sustainability of retaining wall with geosynthetics are compared with conventional concrete retaining wall through life cycle assessment (LCA). Geosynthetics can make a real difference in sustainable construction techniques and contribute to development in developing countries in particular. Their imaginative application can result in considerable cost savings over the use of conventional designs and materials. The acceptance of geosynthetics in reinforced retaining wall construction has been triggered by a number of factors, including aesthetics, reliability, simple construction techniques, good seismic performance, and the ability to tolerate large deformations without structural distress. Reinforced retaining wall with geosynthetics is the best cost-effective and eco-friendly solution as compared with traditional concrete retaining wall construction. This paper presents an analysis of the theme of sustainability applied to the design and construction of traditional concrete retaining wall and presenting a cost-effective and environmental solution using geosynthetics.

Keywords: sustainability, retaining wall, geosynthetics, life cycle assessment

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

Procedia PDF Downloads 387