Search results for: storage performance

Authors: Marcelo Sifuentes López

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Strategic performance definition and follow-up processes have to be clear in order to provide value in today’s competitive world. Customer expectations must be linked to internal organization strategic objectives leading to profitability and supported by visibility and flexibility among others.By taking a whole picture of the supply chain, the executive, and its team will define the current supply chain situation and an insight into potential opportunities to improve processes and provide value to main stakeholders. A systematic performance evaluation process based on operational and financial indicators defined by customer requirements needs to be implemented and periodically reviewed in order to mitigate costs and risks on time.Supplier long term relationship and collaboration plays a key role using resources available, real-time communication, innovation and new ways to capitalize global opportunities like emerging markets; efforts have to focus on the reduction of uncertainties in supply and demand. Leadership has to promote consistency of communication and execution involving suppliers, customers, and the entire organization through the support of a strategic sourcing methodology that assure the targeted competitive strategy and sustainable growth. As customer requirements and expectations are met, results could be captured in a casual picture like a “selfie”; where outcomes could be perceived from any desired angle by them; or like most “selfies”, can be taken with a camera held at arm's length by a third party company rather than using a self-timer.

Keywords: supply chain management, competitive advantage, value creation, collaboration and innovation, global marketplace

Procedia PDF Downloads 417

Authors: Mohd A. Azizan, Mohd Z. Zali

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It is well established that exposure to vibration has an adverse effect on human health, comfort, and performance. However, there is little quantitative knowledge on performance combined with drowsiness level during vibration exposure. This paper reports a study investigating the influence of vibration amplitude on seated occupant reaction time and drowsiness level. Eighteen male volunteers were recruited for this experiment. Before commencing the experiment, total transmitted acceleration measured at interfaces between the seat pan and seatback to human body was adjusted to become 0.2 ms-2 r.m.s and 0.4 ms-2 r.m.s for each volunteer. Seated volunteers were exposed to Gaussian random vibration with frequency band 1-15 Hz at two level of amplitude (low vibration amplitude and medium vibration amplitude) for 20-minutes in separate days. For the purpose of drowsiness measurement, volunteers were asked to complete 10-minutes PVT test before and after vibration exposure and rate their subjective drowsiness by giving score using Karolinska Sleepiness Scale (KSS) before vibration, every 5-minutes interval and following 20-minutes of vibration exposure. Strong evidence of drowsiness was found as there was a significant increase in reaction time and number of lapse following exposure to vibration in both conditions. However, the effect is more apparent in medium vibration amplitude. A steady increase of drowsiness level can also be observed in KSS in all volunteers. However, no significant differences were found in KSS between low vibration amplitude and medium vibration amplitude. It is concluded that exposure to vibration has an adverse effect on human alertness level and more pronounced at higher vibration amplitude. Taken together, these findings suggest a role of vibration in promoting drowsiness, especially at higher vibration amplitude.

Keywords: drowsiness, human vibration, karolinska sleepiness scale, psychomotor vigilance test

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Authors: Umesh Kumar Sinha, Y. K. Nayak, N. Kumar, Swapnil Saurav, Monika Kashyap

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The authors investigate the effect of system and operating parameters on the performance of high temperature solar concentrator for power generation. The effects of system and operating parameters were investigated using the developed mathematical expressions for collector efficiency, heat removal factor, fluid outlet temperature and power, etc. The results were simulated using C++program. The simulated results were plotted for investigation like effect of thermal loss parameter and radiative loss parameters on the collector efficiency, heat removal factor, fluid outlet temperature, rise of temperature and effect of mass flow rate of the fluid outlet temperature. In connection with the power generation, plots were drawn for the effect of (TM–TAMB) on the variation of concentration efficiency, concentrator irradiance on PM/PMN, evaporation temperature on thermal to electric power efficiency (Conversion efficiency) of the plant and overall efficiency of solar power plant.

Keywords: parabolic trough solar collector, radiative and thermal loss parameters, collector efficiency, heat removal factor, fluid outlet and inlet temperatures, rise of temperature, mass flow rate, conversion efficiency, concentrator irradiance

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Authors: Sadegh Sadeghi, Negar Shabani

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From a thermal point of view, zeotropic mixtures are likely to be more efficient than azeotropic fluids in low-temperature thermodynamic cycles due to their suitable boiling characteristics. In this study, performance of a low-temperature Kalina cycle with R717/water working fluid used in different existing power plants is mathematically investigated. To analyze the behavior of the cycle, mass conservation, energy conservation, and exergy balance equations are presented. With regard to the similarity in molar mass of R717 (17.03 gr/mol) and water (18.01 gr/mol), there is no need to alter the size of Kalina system components such as turbine and pump. To optimize the cycle energy and exergy efficiencies simultaneously, a constrained multi-objective optimization is carried out applying an Artificial Bee Colony algorithm. The main motivation behind using this algorithm lies on its robustness, reliability, remarkable precision and high–speed convergence rate in dealing with complicated constrained multi-objective problems. Convergence rates of the algorithm for calculating the optimal energy and exergy efficiencies are presented. Subsequently, due to the importance of exergy concept in Kalina cycles, exergy destructions occurring in the components are computed. Finally, the impacts of pressure, temperature, mass fraction and mass flow rate on the energy and exergy efficiencies are elaborately studied.

Keywords: artificial bee colony algorithm, binary zeotropic mixture, constrained multi-objective optimization, energy efficiency, exergy efficiency, Kalina cycle

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Authors: Maike Andresen, Georg Dochtmann

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Due to political, social, and societal changes in labor organization, top-sharing, defined as job-sharing in leading positions, becomes more important in HRM. German companies are looking for practical and economically meaningful solutions that allow to enduringly increase women’s ratio in management, not only because of a recently implemented quota. Furthermore, supporting employees in achieving work-life balance is perceived as an important goal for a sustainable HRM to gain competitive advantage. Top-sharing is seen as being suitable to reach both goals. To evaluate determinants leading to effective top-sharing, a case study of a newly implemented top-sharing tandem in a large German enterprise was conducted over a period of 15 months. In this company, a full leadership position was split into two 60%-part-time positions held by an experienced female leader in her late career and a female college who took over her first leadership position (mid-career). We assumed a person-person fit in terms of a match of the top sharing partners’ personality profiles (Big Five) and their leadership motivations to be important prerequisites for an effective collaboration between them. We evaluated the person-person fit variables once before the tandem started to work. Both leaders were expected to learn from each other (mentoring, competency development). On an operational level, they were supposed to lead together the same employees in an effective manner (leader-member exchange), presupposing an effective cooperation between both (handing over information). To see developments over time, these processes were evaluated three times over the span of the project. Top-Sharing and the underlined processes are expected to positively influence the tandem’s performance which has been evaluated twice, at the beginning and the end of the project, to assess its development over time as well. The evaluation of the personality and the basic motives suggests that both executives can be a successful top-sharing tandem. The competency evaluations (supervisor as well as self-assessment) increased over the time span. Although the top sharing tandem worked on equal terms, they implemented rather classical than peer-mentoring due to different career ambitions of the tandem partners. Thus, opportunities were not used completely. Team-member exchange scores proved the good cooperation between the top-sharers. Although the employees did not evaluate the leader-member-exchange between them and the two leaders of the tandem homogeneously, the top-sharing tandem itself did not have the impression that the employees’ task performance depended on whom of the tandem was responsible for the task. Furthermore, top-sharing did not negatively influence the performance of both leaders. During qualitative interviews with the top-sharers and their team, we found that the top-sharers could focus more easily on their tasks. The results suggest positive outcomes of top-sharing (e.g. competency improvement, learning from each other through mentoring). Top-Sharing does not hamper performance. Thus, further research and practical implementations are suggested. As part-time jobs are still more often a female solution to increase their work-life- and work-family-balance, top-sharing may be a suitable solution to increase the woman’s ratio in leadership positions as well as to sustainable increase work-life-balance of executives.

Keywords: mentoring, part-time leadership, top-sharing, work-life-balance

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Authors: Nuno Biga

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Continuous processes’ improvement is a permanent challenge for managers of any organization. Lean management means that efficiency gains can be obtained through a systematic framework able to explore synergies between processes, eliminate waste of time, and other resources. Leaderships in organizations determine the efficiency of the teams through their influence on collaborators, their motivation, and consolidation of ownership (group) feeling. The “organization health” depends on the leadership style, which is directly influenced by the intrinsic characteristics of each personality and leadership ability (leadership competencies). Therefore, it’s important that managers can correct in advance any deviation from expected leadership exercises. Top management teams must assume themselves as regulatory agents of leadership within the organization, ensuring monitoring of actions and the alignment of managers in accordance with the humanist standards anchored in a visible Code of Ethics and Conduct. This article is built around an innovative model of “Business Interactive Games” (BI GAMES) that simulates a real-life management environment. It shows that the strategic management of operations depends on a complex set of endogenous and exogenous variables to the intervening agents that require specific skills and a set of critical processes to monitor. BI GAMES are designed for each management reality and have already been applied successfully in several contexts over the last five years comprising the educational and enterprise ones. Results from these experiences are used to demonstrate how serious games in working living labs contributed to improve the organizational environment by focusing on the evaluation of players’ (agents’) skills, empower its capabilities, and the critical factors that create value in each context. The implementation of the BI GAMES simulator highlights that leadership skills are decisive for the performance of teams, regardless of the sector of activity and the specificities of each organization whose operation is intended to simulate. The players in the BI GAMES can be managers or employees of different roles in the organization or students in the learning context. They interact with each other and are asked to decide/make choices in the presence of several options for the follow-up operation, for example, when the costs and benefits are not fully known but depend on the actions of external parties (e.g., subcontracted enterprises and actions of regulatory bodies). Each team must evaluate resources used/needed in each operation, identify bottlenecks in the system of operations, assess the performance of the system through a set of key performance indicators, and set a coherent strategy to improve efficiency. Through the gamification and the serious games approach, organizational managers will be able to confront the scientific approach in strategic decision-making versus their real-life approach based on experiences undertaken. Considering that each BI GAME’s team has a leader (chosen by draw), the performance of this player has a direct impact on the results obtained. Leadership skills are thus put to the test during the simulation of the functioning of each organization, allowing conclusions to be drawn at the end of the simulation, including its discussion amongst participants.

Keywords: business interactive games, gamification, management empowerment skills, simulation living labs

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Authors: Polina Prokopovich

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Disease-modifying osteoarthritis drugs (DMOADs) are a new therapeutic class for OA, preventing or inhibiting OA development. Unfortunately, none of the DMOADs have been clinically approved due to their poor therapeutic effects in clinical trials. The joint environment has played a role in the poor clinical performance of these drugs by limiting the amount of drug effectively delivered as well as the time that the drug spends within the joint space. The current study aims to enhance the cartilage uptake and retention time of the DMOADs-model (licofelone), which showed a significant therapeutic effect against OA progression and is currently in phase III. Licofelone will be covalently conjugated to the hydrolysable, cytocompatible, and cationic poly beta-amino ester polymers (PBAE). The cationic polymers (A16 and A87) can be electrostatically attached to the negatively charged cartilage component (glycosaminoglycan), which will increase the drug penetration through the cartilage and extend the drug time within the cartilage. In the cartilage uptake and retention time studies, an increase of 18 to 37 times of the total conjugated licofelone to A87 and A16 was observed when compared to the free licofelone. Furthermore, the conjugated licofelone to A87 was detectable within the cartilage at 120 minutes, while the free licofelone was not detectable after 60 minutes. Additionally, the A87-licofelone conjugate showed no effect on the chondrocyte viability. In conclusion, the cationic A87 and A16 polymers increased the percentage of licofelone within the cartilage, which could potentially enhance the therapeutic effect and pharmacokinetic performance of licofelone or other DMOADs clinically.

Keywords: PBAE, cartilage., osteoarthritis, injectable biomaterials, drug delivery

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Authors: Sazzad Hossain Talukder

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Survival in the competitive international market with unforeseen environmental contingencies has always been a concern of the firms that led to adopting different strategies to deal with different situations. Language strategy is considered to enhance the international performance of a firm by organizing language diversity and fostering communications within and outside the firm. Yet there is a lack of theoretical attention or model development on the role of language strategy on firm international survival. From resource dependence perspective, the adoption of language strategy and its relationship with firm survival are determined by the firm´s capability to prevent dependency concentration and/or increase relative power on the external environment. However, the impact of language strategy on firm survival is complex and multifaceted as the strategy influence firm performance indirectly through communication, coordination, learning and value creation. The evidence of various types of language strategies and different forms of firm survival also bring in complexities to understand the effects of a language strategy on the international survival of a firm. Based on language literatures and resource dependence logic, certain propositions are developed to conceptualize the relationship between language strategy and firm international survival in this conceptual paper. For the purpose of this paper, a conceptual model is proposed to examine how different kinds of language strategy foster reduction of resource dependency that lead to firm international survival in respond to local responsiveness and global integration. In this proposed model, it is theorized that language strategy has a positive relationship with the international survival of the firm, as the strategy is likely to reduce external resource dependency and increase the ability to continue independent operations both in short and long term.

Keywords: language strategy, language diversity, firm international survival, resource dependence logic

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Authors: Jessica Hemberg, Mikaela Miller

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Unreasonable workload and work-related stress can reduce nurse leaders’ job satisfaction and productivity and can increase absence and burnout. Nurse leaders’ workload in public healthcare settings is relatively unresearched. The aim of this study was to investigate nurse leaders’ perceptions of workload and task distribution with relation to leading work tasks in public healthcare. A qualitative explorative design was used. The data material consisted of texts from interviews with nurse leaders in public healthcare (N=8). The method was inspired by content analysis. The COREQ checklist was used. Informed consent was sought from the participants regarding study participation and the storage and handling of data for research purposes. Six main themes were found: Increased and unreasonable workload, Length of work experience as nurse leader affects perception of workload, Number of staff and staff characteristics affect perception of workload, Versatile and flexible task distribution, Working overtime as a way of managing high workload, and Insufficient time for leadership mission. The workload for nurse leaders in a public healthcare setting was perceived to be unreasonable. Common measures for managing high workload included working overtime, delegating work tasks and organizing more staff resources in the form of additional staff. How nurse leaders perceive their workload was linked to both the number of staff and staff characteristics. These should both be considered equally important when determining staff levels and measuring nurse leaders’ workload. Future research should focus on investigating workload and task distribution from nurses’ perspectives.

Keywords: nurse leaders, workload, task distribution, public healthcare, qualitative

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Authors: Nima Pirhadi, Shao Yong Bo, Xusheng Wan, Jianguo Lu, Jilei Hu

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Although gravels and gravelly soils are assumed to be non-liquefiable because of high conductivity and small modulus; however, the occurrence of this phenomenon in some historical earthquakes, especially recently earthquakes during 2008 Wenchuan, Mw= 7.9, 2014 Cephalonia, Greece, Mw= 6.1 and 2016, Kaikoura, New Zealand, Mw = 7.8, has been promoted the essential consideration to evaluate risk assessment and hazard analysis of seismic gravelly soil liquefaction. Due to the limitation in sampling and laboratory testing of this type of soil, in situ tests and site exploration of case histories are the most accepted procedures. Of all in situ tests, dynamic penetration test (DPT), Which is well known as the Chinese dynamic penetration test, and shear wave velocity (Vs) test, have been demonstrated high performance to evaluate seismic gravelly soil liquefaction. However, the lack of a sufficient number of case histories provides an essential limitation for developing new models. This study at first investigates recent earthquakes that caused liquefaction in gravelly soils to collect new data. Then, it adds these data to the available literature’s dataset to extend them and finally develops new models to assess seismic gravelly soil liquefaction. To validate the presented models, their results are compared to extra available models. The results show the reasonable performance of the proposed models and the critical effect of gravel content (GC)% on the assessment.

Keywords: liquefaction, gravel, dynamic penetration test, shear wave velocity

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu

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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.

Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law

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Authors: Carolina Beltran, Carlos De Los Reyes

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Acquired brain injury (ABI) is any physical and functional injury secondary to events that affect the brain tissue. It is one of the biggest causes of disability in the world and it has a high annual incidence in the pediatric population. There are several causes of ABI such as traumatic brain injury, central nervous system infection, stroke, hypoxia, tumors and others. The consequences can be cognitive, behavioral, emotional and functional. The cognitive rehabilitation is necessary to achieve the best outcomes for pediatric people with ABI. Cognitive orientation to daily occupational performance (CO-OP) is an individualized client-centered, performance-based, problem-solving approach that focuses on the strategy used to support the acquisition of three client-chosen goals. It has demonstrated improvements in the pediatric population with other neurological disorder but not in Spanish speakers with ABI. Aim: The main objective of this study was to determine the efficacy of cognitive orientation to daily occupational performances (CO-OP) adapted to Spanish speakers, in the level of independence and behavior in a pediatric population with ABI. Methods: Case studies with measure pre/post-treatment were used in three children with ABI, sustained at least before 6 months assessment, in school, aged 8 to 16 years, age ABI after 6 years old and above average intellectual ability. Twelve sessions of CO-OP adapted to Spanish speakers were used and videotaped. The outcomes were based on cognitive, behavior and functional independence measurements such as Child Behavior Checklist (CBCL), Behavior Rating Inventory of Executive Function (BRIEF), The Vineland Adaptive Behavior Scales (VINELAND, Social Support Scale (MOS-SSS) and others neuropsychological measures. This study was approved by the ethics committee of Universidad del Norte in Colombia. Informed parental written consent was obtained for all participants. Results: children were able to identify three goals and use the global strategy ‘goal-plan-do-check’ during each session. Verbal self-instruction was used by all children. CO-OP showed a clinically significant improvement in goals regarding with independence level and behavior according to parents and teachers. Conclusion: The results indicated that CO-OP and the use of a global strategy such as ‘goal-plan-do-check’ can be used in children with ABI in order to improve their specific goals. This is a preliminary version of a big study carrying in Colombia as part of the experimental design.

Keywords: cognitive rehabilitation, acquired brain injury, pediatric population, cognitive orientation to daily occupational performance

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Authors: Agah Tuğrul Korucu, Handan Atun

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Diversity and usefulness of information that used in education are have increased due to development of technology. Web technologies have made enormous contributions to the distance learning system especially. Mobile systems, one of the most widely used technology in distance education, made much easier to access web technologies. Not bounding by space and time, individuals have had the opportunity to access the information on web. In addition to this, the storage of educational information and resources and accessing these information and resources is crucial for both students and teachers. Because of this importance, development and dissemination of web technologies supply ease of access to information and resources are provided by web technologies. Dynamic web technologies introduced as new technologies that enable sharing and reuse of information, resource or applications via the Internet and bring websites into expandable platforms are commonly known as Web 2.0 technologies. Cloud systems are one of the dynamic web technologies that defined as a model provides approaching the demanded information independent from time and space in appropriate circumstances and developed by NIST. One of the most important advantages of cloud systems is meeting the requirements of users directly on the web regardless of hardware, software, and dealing with install. Hence, this study aims at using cloud services in education and investigating the services provided by the cloud computing. Survey method has been used as research method. In the findings of this research the fact that cloud systems are used such studies as resource sharing, collaborative work, assignment submission and feedback, developing project in the field of education, and also, it is revealed that cloud systems have plenty of significant advantages in terms of facilitating teaching activities and the interaction between teacher, student and environment.

Keywords: cloud systems, cloud systems in education, online learning environment, integration of information technologies, e-learning, distance learning

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Authors: Yulia A. Kononova, Znang X. Ning

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Nowadays, architectural development is getting faster and faster. Nevertheless, modern architecture often does not meet all the points, which could help our planet to get better. As we know, people are spending an enormous amount of energy every day of their lives. Because of the uncontrolled energy usage, people have to increase energy production. As energy production process demands a lot of fuel sources, it courses a lot of problems such as climate changes, environment pollution, animals’ distinction, and lack of energy sources also. Nevertheless, nowadays humanity has all the opportunities to change this situation. Architecture is one of the most popular fields where it is possible to apply new methods of saving energy or even creating it. Nowadays we have kinds of buildings, which can meet new willing. One of them is energy effective buildings, which can save or even produce energy, combining several energy-saving principles. The main aim of this research is to provide information that helps to apply energy-saving methods while designing an environment-friendly building. The research methodology requires gathering relevant information from literature, building guidelines documents and previous research works in order to analyze it and sum up into a material that can be applied to energy-efficient building design. To mark results it should be noted that the usage of all the energy-saving methods applied to a design project of building results in ultra-low energy buildings that require little energy for space heating or cooling. As a conclusion it can be stated that developing methods of passive house design can decrease the need of energy production, which is an important issue that has to be solved in order to save planet sources and decrease environment pollution.

Keywords: accumulation, energy-efficient building, storage, superinsulation, passive house

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Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

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Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, material recycling, optimization modeling

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Authors: Çağrı Bekir Baysal, Göktuğ Burak Çalık

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Armored vehicles may have different traction layouts as a result of terrain capabilities and mobility needs. Two main categories of layouts can be separated as wheeled and tracked. Tracked vehicles have superior off-road capabilities but what they gain on terrain performance they lose on mobility front. Wheeled vehicles on the other hand do not have as good terrain capabilities as tracked vehicles but they have superior mobility capabilities such as top speed, range and agility with respect to tracked vehicles. Conventional armored vehicles employ a diesel ICE as main power source. In these vehicles ICE is mechanically connected to the powertrain. This determines the ICE rpm as a result of speed and torque requested by the driver. ICE efficiency changes drastically with torque and speed required and conventional vehicles suffer in terms of fuel consumption because of this. Hybrid electric vehicles employ at least one electric motor in order to improve fuel efficiency. There are different types of hybrid vehicles but main types are Series Hybrid, Parallel Hybrid and Series-Parallel Hybrid. These vehicles introduce an electric motor for traction and also can have a generator electric motor for range extending purposes. Having an electric motor as the traction power source brings the flexibility of either using the ICE as an alternative traction source while it is in efficient range or completely separating the ICE from traction and using it solely considering efficiency. Hybrid configurations have additional advantages for armored vehicles in addition to fuel efficiency. Heat signature, silent operation and prolonged stationary missions can be possible with the help of the high-power battery pack that will be present in the vehicle for hybrid drivetrain. Because of the reasons explained, hybrid armored vehicles are becoming a target area for military and also for vehicle suppliers. In order to have a better idea and starting point when starting a hybrid armored vehicle design, hybrid drivetrain configuration has to be selected after performing a trade-off study. This study has to include vehicle mobility simulations, integration level, vehicle level and performance level criteria. In this study different hybrid traction configurations possible for an 8x8 vehicle is compared using above mentioned criteria set. In order to compare hybrid traction configurations ease of application, cost, weight advantage, reliability, maintainability, redundancy and performance criteria have been used. Performance criteria points have been defined with the help of vehicle simulations and tests. Results of these simulations and tests also help determining required tractive power for an armored vehicle including conditions like trench and obstacle crossing, gradient climb. With the method explained in this study, each configuration is assigned a point for each criterion. This way, correct configuration can be selected objectively for every application. Also, key aspects of armored vehicles, mine protection and ballistic protection will be considered for hybrid configurations. Results are expected to vary for different types of vehicles but it is observed that having longitudinal differential locking capability improves mobility and having high motor count increases complexity in general.

Keywords: armored vehicles, electric drivetrain, electric mobility, hybrid vehicles

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Authors: Xuan Li, Weian Huang, Jinsheng Sun, Fuhao Zhao, Zhiyuan Wang, Jintang Wang

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Natural gas hydrates (NGHs) as promising alternative energy sources have gained increasing attention. Hydrate-bearing formation in marine areas is highly unconsolidated formation and is fragile, which is composed of weakly cemented sand-clay and silty sediments. During the drilling process, the invasion of drilling fluid can easily lead to excessive water content in the formation. It will change the soil liquid plastic limit index, which significantly affects the formation quality, leading to wellbore instability due to the metastable character of hydrate-bearing sediments. Therefore, controlling the filtrate loss into the formation in the drilling process has to be highly regarded for protecting the stability of the wellbore. In this study, the temperature-sensitive nanogel of P(NIPAM-co-AMPS-co-tBA) was prepared by soap-free emulsion polymerization, and the temperature-sensitive behavior was employed to achieve self-adaptive plugging in hydrate sediments. First, the effects of additional amounts of AMPS, tBA, and cross-linker MBA on the microgel synthesis process and temperature-sensitive behaviors were investigated. Results showed that, as a reactive emulsifier, AMPS can not only participate in the polymerization reaction but also act as an emulsifier to stabilize micelles and enhance the stability of nanoparticles. The volume phase transition temperature (VPTT) of nanogels gradually decreased with the increase of the contents of hydrophobic monomer tBA. An increase in the content of the cross-linking agent MBA can lead to a rise in the coagulum content and instability of the emulsion. The plugging performance of nanogel was evaluated in a core sample with a pore size distribution range of 100-1000nm. The temperature-sensitive nanogel can effectively improve the microfiltration performance of drilling fluid. Since a combination of a series of nanogels could have a wide particle size distribution at any temperature, around 200nm to 800nm, the self-adaptive plugging capacity of nanogels for the hydrate sediments was revealed. Thermosensitive nanogel is a potential intelligent plugging material for drilling operations in natural gas hydrate-bearing sediments.

Keywords: temperature-sensitive nanogel, NIPAM, self-adaptive plugging performance, drilling operations, hydrate-bearing sediments

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Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Niphattha Hannapha

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This paper examines how the classroom environment influences slow learners’ learning achievement; it focuses on how seating patterns affect students’ behaviours and which patterns best contribute to students’ learning performance. The researcher studied how slow learners’ characteristics and seating patterns influenced their behaviours and performance at Ban Hin Lad School. As a nonparticipant observation, the target groups included 15 slow learners from Prathomsueksa (Grades) 4 and 5. Students’ behaviours were recorded during their learning activities in order to minimize their reading and written expression disorder in Thai language tutorials. The result showed four seating patterns and two behaviors which obstructed students’ learning. The average of both behaviours mostly occurred when students were seated with patterns 1 (the seat facing the door, with the corridor alongside) and 3 (the seat alongside the door, facing the aisle) respectively. Seating patterns 1 and 3 demonstrated visibility (the front and side) of a walking path with two-way movement. However, seating patterns 2 (seating with the door alongside and the aisle at the back) and 4 (sitting with the door at the back and the aisle alongside) demonstrated visibility (the side) of a walking path with one-way movement. In Summary, environmental design is important to enhance concentration in slow learners who have reading and writing disabilities. This study suggests that students should be seated where they can have the least visibility of movement to help them increase continuous learning. That means they can have a better chance of developing reading and writing abilities in comparison with other patterns of seating.

Keywords: slow learning, interior design, interior environment, classroom

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Authors: Hui Zhang, Sherif Beskhyroun

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In this study, a highly flexible LoRa-Based wireless sensing system was used to assess the strain state performance of building structures. The system was developed to address the local damage limitation of structural health monitoring (SHM) systems. The system is part of an intelligent SHM system designed to monitor, collect and transmit strain changes in key structural components. The main purpose of the wireless sensor system is to reduce the development and installation costs, and reduce the power consumption of the system, so as to achieve long-time monitoring. The highly stretchable flexible strain gauge is mounted on the surface of the structure and is waterproof, heat resistant, and low temperature resistant, greatly reducing the installation and maintenance costs of the sensor. The system was also developed with the aim of using LoRa wireless communication technology to achieve both low power consumption and long-distance transmission, therefore solving the problem of large-scale deployment of sensors to cover more areas in large structures. In the long-term monitoring of the building structure, the system shows very high performance, very low actual power consumption, and wireless transmission stability. The results show that the developed system has a high resolution, sensitivity, and high possibility of long-term monitoring.

Keywords: LoRa, SHM system, strain measurement, civil structures, flexible sensing system

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Authors: S. Rodosik, J. P. Poirot-Crouvezier, Y. Bultel

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With the expansion of the hydrogen economy, Proton Exchange Membrane Fuel Cell (PEMFC) systems are often presented as promising energy converters suitable for transport applications. However, reaching a durability of 5000 h recommended by the U.S. Department of Energy and decreasing system cost are still major hurdles to their development. In order to increase the system efficiency and simplify the system without affecting the fuel cell lifetime, an architecture called alternative fuel feeding has been developed. It consists in a fuel cell stack divided into two parts, alternatively fed, implemented on a 5-kW system for real scale testing. The operation strategy can be considered close to Dead End Anode (DEA) with specific modifications to avoid water and nitrogen accumulation in the cells. The two half-stacks are connected in series to enable each stack to be alternatively fed. Water and nitrogen accumulated can be shifted from one half-stack to the other one according to the alternative feeding frequency. Thanks to the homogenization of water vapor along the stack, water management was improved. The operating conditions obtained at system scale are close to recirculation without the need of a pump or an ejector. In a first part, a performance comparison with the DEA strategy has been performed. At high temperature and low pressure (80°C, 1.2 bar), performance of alternative fuel feeding was higher, and the system efficiency increased. In a second part, in order to highlight the benefits of the architecture on the fuel cell lifetime, two durability tests, lasting up to 1000h, have been conducted. A test on the 5-kW system has been compared to a reference test performed on a test bench with a shorter stack, conducted with well-controlled operating parameters and flow-through hydrogen strategy. The durability test is based upon the Fuel Cell Dynamic Load Cycle (FC-DLC) protocol but adapted to the system limitations: without OCV steps and a maximum current density of 0.4 A/cm². In situ local measurements with a segmented S++® plate performed all along the tests, showed a more homogeneous distribution of the current density with alternative fuel feeding than in flow-through strategy. Tests performed in this work enabled the understanding of this architecture advantages and drawbacks. Alternative fuel feeding architecture appeared to be a promising solution to ensure the humidification function at the anode side with a simplified fuel cell system.

Keywords: automotive conditions, durability, fuel cell system, proton exchange membrane fuel cell, stack architecture

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Authors: Muntadher Sallal, Gareth Owenson, Mo Adda, Safa Shubbar

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Bitcoin is a digital currency based on a peer-to-peer network to propagate and verify transactions. Bitcoin is gaining wider adoption than any previous crypto-currency. However, the mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation, which makes the system vulnerable to double-spend attacks. Aiming at alleviating the propagation delay problem, this paper introduces proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol, that are based on how clusters are formulated and how nodes can define their membership, is to improve the information propagation delay in the Bitcoin network. In MNBC protocol, physical internet connectivity increases, as well as the number of hops between nodes, decreases through assigning nodes to be responsible for maintaining clusters based on physical internet proximity. We show, through simulations, that the proposed protocol defines better clustering structures that optimize the performance of the transaction propagation over the Bitcoin protocol. The evaluation of partition attacks in the MNBC protocol, as well as the Bitcoin network, was done in this paper. Evaluation results prove that even though the Bitcoin network is more resistant against the partitioning attack than the MNBC protocol, more resources are needed to be spent to split the network in the MNBC protocol, especially with a higher number of nodes.

Keywords: Bitcoin network, propagation delay, clustering, scalability

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Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

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Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

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Authors: Ka C. Lam, Oluwafunmibi S. Idowu

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Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

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Authors: Qiong He, S. Thomas Ng

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Upgrading the thermal performance of building envelope of existing residential buildings is an effective way to reduce heat gain or heat loss. Overhang device is a common solution for building envelope improvement as it can cut down solar heat gain and thereby can reduce the energy used for space cooling in summer time. Despite that, overhang can increase the demand for indoor heating in winter due to its function of lowering the solar heat gain. Obviously, overhang has different impacts on energy use in different climatic zones which have different energy demand. To evaluate the impact of overhang device on building energy performance under different climates of China, an energy analysis model is built up in a computer-based simulation program known as DesignBuilder based on the data of a typical high-rise residential building. The energy simulation results show that single overhang is able to cut down around 5% of the energy consumption of the case building in the stand-alone situation or about 2% when the building is surrounded by other buildings in regions which predominantly rely on space cooling though it has no contribution to energy reduction in cold region. In regions with cold summer and cold winter, adding overhang over windows can cut down around 4% and 1.8% energy use with and without adjoining buildings, respectively. The results indicate that overhang might not an effective shading device to reduce the energy consumption in the mixed climate or cold regions.

Keywords: overhang, energy analysis, computer-based simulation, design builder, high-rise residential building, climate, BIM model

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

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While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

Procedia PDF Downloads 75