A Hybrid Model for Reliability Aware and Energy-Efficiency in Multicore Systems

Recently,Multicore systems use Dynamic Voltage/Frequency Scaling(DV/FS)technology to allow the cores to operate with various voltage and/or frequencies than other cores to save power and enhance the performance.In this paper,an effective and reliable hybridmodel to reduce the energy and makespan in multicore systems is proposed.The proposed hybrid model enhances and integrates the greedy approach with dynamic programming to achieve optimal Voltage/Frequency(Vmin/F)levels.Then,the allocation process is applied based on the availableworkloads.The hybrid model consists of three stages.The first stage gets the optimum safe voltage while the second stage sets the level of energy efficiency,and finally,the third is the allocation stage.Experimental results on various benchmarks show that the proposed model can generate optimal solutions to save energy while minimizing the makespan penalty.Comparisons with other competitive algorithms show that the proposed model provides on average 48%improvements in energy-saving and achieves an 18%reduction in computation time while ensuring a high degree of system reliability.

A Homeowner-Based Methodology for Economic Analysis of Energy-Efficiency Measures in Residences

Residential energy-efficiency measures, besides energy savings, provide opportunities for improvement of thermal comfort, air quality, lighting quality, and operation. However, all these benefits sometimes are not enough to convince a homeowner to pay the incremental cost associated with the energy-efficiency measure. The objective of this work is to develop a methodology for the economic evaluation of residential energy-efficiency measures that can simplify the economic analysis for the homeowner while taking into consideration all factors associated with the purchase, ownership, and selling of the house with the energy-efficiency measure. The methodology accounts for direct and indirect economic parameters associated to an energy-efficiency measure;direct parameters such as the mortgage interest and fuel price escalation rate, and indirect parameters such as savings account interest and marginal income tax rate. The methodology also considers different cases based on the service life of the energy-efficiency measure and loss of efficiency through a derating factor. To estimate the market value, the methodology uses the future energy cost savings instead of the cost of the EEM. Results from the methodology offer to homeowner annual net savings and net assets. The annual net savings gives the homeowner a measure of the annual positive cash flow that can be obtained from an energy-efficiency project;but more important, the net assets offer a measure of the added net wealth. To simplify and increase the use of the methodology by homeowners, the methodology has been implemented in an Excel tool that can be downloaded from the TxAIRE’s website.

An Energy-Efficient Routing Algorithm for UAV Formation Based on Time-Aggregated Graph

The limited energy and high mobility of unmanned aerial vehicles(UAVs)lead to drastic topology changes in UAV formation.The existing routing protocols necessitate a large number of messages for route discovery and maintenance,greatly increasing network delay and control overhead.A energyefficient routing method based on the discrete timeaggregated graph(TAG)theory is proposed since UAV formation is a defined time-varying network.The network is characterized using the TAG,which utilizes the prior knowledge in UAV formation.An energyefficient routing algorithm is designed based on TAG,considering the link delay,relative mobility,and residual energy of UAVs.The routing path is determined with global network information before requesting communication.Simulation results demonstrate that the routing method can improve the end-to-end delay,packet delivery ratio,routing control overhead,and residual energy.Consequently,introducing timevarying graphs to design routing algorithms is more effective for UAV formation.

Energy-Efficient and Cost-Effective Approaches through Energy Modeling for Hotel Building

Hotel buildings are currently among the largest energy consumers in the world.Heating,ventilation,and air conditioning are the most energy-intensive building systems,accounting for more than half of total energy consumption.An energy audit is used to predict the weak points of a building’s energy use system.Various factors influence building energy consumption,which can be modified to achieve more energy-efficient strategies.In this study,an existing hotel building in Central Taiwan is evaluated by simulating several scenarios using energy modeling over a year.Energy modeling is conducted by using Autodesk Revit 2025.It was discovered from the results that arranging the lighting schedule based on the ASHRAE Standard 90.1 could save up to 8.22%of energy consumption.And then the results also revealed that changing the glazing of the building into double-layer lowemissivity glass could reduce energy consumption by 14.58%.While the energy consumption of the building could also be decreased to 7.20%by changing the building orientation to the north.Meanwhile,moving the building location to Northern Taiwan could also minimize the energy consumption of the building by 3.23%.The results revealed that the double layer offers better thermal insulation,and low-emissivity glass can lower energy consumption,electricity costs,and CO_(2)emissions by up to 15.27%annually.While adjusting orientation and location can enhance energy performance,this approach is impractical for existing buildings,but this could be considered for designing new buildings.The results showed the relevancy of energy performance to CO_(2)emission production and electricity expenses.

Characteristics of Infertile Clientele Attending a Public in Vitro Fertilization Clinic: Appraising Priorities in a Low-Income Country

Introduction: Infertilityaffects one in six couples, and it is an important public health issue largely due to thepervasive effects on the emotional and psychological wellbeing of affected couples. In many developing nations emphasis is placed on childbirth and inability to fulfill this role can be very distressing. There is an unmet need for assisted reproductive technology (ART) in many developing countries and where facilities exist, they are mostly privately owned, expensive and concentrated in urban areas. To bridge this gap, public fertility clinics have been established to provide subsidized care. Evaluating the characteristics and peculiarities of clientele presenting at these public facilities will aid planning and prioritization of care. Methodology: A descriptive retrospective study of 116 infertile patients presenting to the fertility clinic of the University College Hospital, Ibadan, Nigeria from inception on the 14th of February 2019 and 31st of December 2022.Data was analyzed using the Statical Package for Social Sciences (IBM, SPSS, New York) version 23. Descriptive statistics were used to summarize the results which were presented with the aid of bar charts and frequency tables. Result: The mean age of the patients was 40.70 ± 6.62 years. Post-menopausal patients accounted for about one-fifth of the study population while 80.2% (93 women) were older than 35 years. The mean duration of infertility was 9.39 ± 6.11years and nine patients (7.8%) had a duration greater than 2 decades. Secondary infertility occurred in 67.2% of the women. Twenty-nine women (25%) had undergone myomectomy prior to presentation. Hypertension (11.2%) was the most prevalent comorbidity. Nineteen patients (16.4%) had used contraceptives in the past with the male condom (36.8%)being the most preponderant. Sixty-seven patients had experienced pregnancy losses before 28 weeks of gestation while just 16 patients (13.8%) had undergone ART, and none was successful. Conclusion: Secondary infertility was the prevalent type of infertility and may not be unconnected with the low contraceptive usage and high risk of sexually transmitted infection. Late presentation coupled with a large proportion of post-menopausal clientele suggests delayed health-seeking behavior most probably due to the prohibitive cost of ART. The need to streamline services offered in public fertility clinics is paramount in low-income countries grappling with scarce resources. A pragmatic approach will involve the provision of low-cost ART, while enhancing gamete donation programs through the implementation of gamete sharing policies. This will invariably bridge the unmet need and skewed access to ART in developing countries.

A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.

Increasing realism in modelling energy losses in railway vehicles and their impact to energy-efficient train control

The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.

Applying an Ordinal Priority Approach Based Neutrosophic Fuzzy Axiomatic Design Approach to Develop Sustainable Geothermal Energy Source

Geothermal energy is considered a renewable,environmentally friendly,especially carbon-free,sustainable energy source that can solve the problem of climate change.In general,countries with geothermal energy resources are the ones going through the ring of fire.Therefore,not every country is lucky enough to own this resource.As a country with 117 active volcanoes and within the world’s ring of fire,it is a country whose geothermal resources are estimated to be about 40%of the world’s geothermal energy potential.However,the percentage used compared to the geothermal potential is too small.Therefore,this is the main energy source that Indonesia is aiming to exploit and use.However,the deployment and development of this energy source are still facing many obstacles due to many aspects from budget sources due to high capital costs,factory construction location,quality of resources,and conflicts of the local community.In this context,determining the optimal locations for geothermal energy sites(GES)is one of the most important and necessary issues.To strengthen the selection methods,this study applies a two-layer fuzzy multi-criteria decision-making method.Through the layers,the Ordinal Priority Approach(OPA)is proposed to weight the sub-criteria,the main criterion,and the sustainability factors.In layer 2,the Neutrosophic Fuzzy Axiomatic Design(NFAD)is applied to rank and evaluate potential locations for geothermal plant construction.Choosing the right geothermal energy site can bring low-cost efficiency,no greenhouse gas emissions,and quickly become the main energy source providing electricity for Indonesia.The final ranking shows Papua,Kawah Cibuni,and Moluccas as the three most suitable cities to build geothermal energy systems.Kawah Cibuni was identified as the most potential GES in Indonesia,with a score of 0.46.Papua is the second most promising GES with a score of 0.45.Next is the Moluccas,with a score of 0.39.However,the three least potential sites among the 15 studied sites are Lumut Balai,Moluccas and Patuha,with scores of 0.08,0.11 and 0.17,respectively.The conclusion of this study also classifies positions into groups to aid in decision-making.

COMRADES FOREVER--To Lam’s visit demonstrates that China remains Vietnam’s top foreign policy priority

On August 20,2024,General Secretary of the Communist Party of Vietnam(CPV)Central Committee and Vietnamese President To Lam concluded his state visit to China.China was the destination for Lam's first overseas visit after taking office as general secretary of the CPV Central Committee,which clearly demonstrates that the heads of both countries attach importance to developing the bilateral relations and that Vietnam regards China as the strategic choice and top priority for its foreign policy.

Shape Analysis of Agricultural Parcels for Land Consolidation Priorities in Tekirdag Province,Turkey

Shape irregularity,a sub-factor of parcel fragmentation is a problem that hinders sustainable agriculture and is solved using land consolidation projects.Determination of the parcel shape degree contributes significantly to spatial prioritization where there is also a high probability of achieving positive effects of consolidation projects.This study aims to determine the shape degree of the agricultural parcels both at singular and rural county scales in Tekirdag Province,Turkey in 2020 by combining the parcel shape index(PSI) with the minimum bounding geometry index(MBG) to improve parcel scores.Hot-spot zones of the highly irregular and near optimum parcels were also determined using Getis-Ord G_(i)^(*) statistic.The parcel degrees were classified into four categories,namely highly irregular,irregular,regular and near optimum.The obtained unweighted scores of the parameters exhibit deviations from the expected values.After weighting by pairwise comparison,the values approached ideal scores.Among 346 740 parcels,53% were highly irregular and irregular and 47% were regular and near optimum shapes after weighting whereas these were 70% and 30%,respectively before weighting.The average parcel degree of 63 rural counties was regular while the average parcel degree of the remaining 264 rural counties was irregular.The combined use of PSI and MBG index improved the correctness of the parcel shape score.It could be suggested to use as a tool in land consolidation prioritization.

A priority-based electric vehicle-assisted grid frequency regulation system

During electric vehicle(EV)-assisted grid frequency modulation,inconsistent state of charge(SOC)among EVs can result in overcharging and discharging of the batteries,affecting the stability of the electrical system.As a solution,this paper proposes a priority-based frequency regulation strategy for EVs.Firstly,models for the primary and secondary frequency regulation of EV-assisted power grids are established.Secondly,a consensus algorithm is used to construct a distributed com-munication system for EVs.Target SOC values are used to obtain a local frequency regulation priori-ty list.The list is used in an optimal control plan allowing individual EVs to participate in frequency regulation.Finally,a simulation of this strategy under several scenarios is conducted.The results indicate that the strategy ensures uniform SOC among the participating group of EVs,thereby avoi-ding overcharging and discharging of their batteries.It also reduces frequency fluctuations in the electrical system,making the system more robust compared with the frequency regulation strategy that is not priority-based.

一种融合Priority-Flood算法与D8算法特点的河网提取方法

基于数字高程模型(Digital Elevation Models)进行河网提取是数字地形分析的重要研究内容和水文分析的关键步骤,而流向算法是其中最重要的部分。然而,传统的流向算法在平坦地形区域容易形成平行河网。为解决平行河网问题,该文提出了一种结合Priority-Flood算法漫水思想和改进D8算法的流向算法。借助Priority-Flood算法的漫水思想,可以保证流向符合宏观地形特征;同时将地形划分为上坡、平地和下坡3种类型,辅以PriorityFlood算法可以实现在不填洼的基础上计算流向,而且针对不同地形,采用相应的改进D8流向算法,从而保证流向符合微观地形特征。通过这两种算法的结合,可以直接使用原始DEM提取河网,消除了填洼过程,提高了流向计算效率,同时消除了填洼造成的大量平地,有效地解决了平地区域平行河网问题。最后,选取全球不同区域SRTM数据对J&D算法与新算法进行对比实验,结果表明,新算法能够有效地改善平行河网问题。

Energy-efficient mechanism based on ACO for the coverage problem in sensor networks

An energy-efficient heuristic mechanism is presented to obtain the optimal solution for the coverage problem in sensor networks. The mechanism can ensure that all targets are fully covered corresponding to their levels of importance at minimum cost, and the ant colony optimization algorithm （ACO） is adopted to achieve the above metrics. Based on the novel design of heuristic factors, artificial ants can adaptively detect the energy status and coverage ability of sensor networks via local information. By introducing the evaluation function to global pheromone updating rule, the pheromone trail on the best solution is greatly enhanced, so that the convergence process of the algorithm is speed up. Finally, the optimal solution with a higher coverage- efficiency and a longer lifetime is obtained.

Priority approach based on quadratic programming model to fuzzy preference relation

We investigate the decision-making problem with a finite set of alternatives,in which the decision information takes the form of a fuzzy preference relation. We develop asimple and practical approach to obtaining the priority vector of a fuzzy preference relation. Theprominent characteristic of the developed approach is that the priority vector can generally beobtained by a simple formula, which is derived from a quadratic programming model. We utilize theconsistency ratio to check the consistency of fuzzy preference relation. If the fuzzy preferencerelation is of unacceptable consistency, then we can return it to the decision maker to reconsiderstructuring a new fuzzy preference relation until the fuzzy preference relation with acceptableconsistency is obtained. We finally illustrate the priority approach by two numerical examples. Thenumerical results show that the developed approach is straightforward, effective, and can easily beperformed on a computer.

On Application of Nida’s Priorities in Translation

This paper analyzes Nida’s theory of translation, also his system of priorities. The paper uses examples to illustrate the application of Nida’s four priorities in the practice of English Chinese and Chinese English translation and concludes that we can apply the system to help the receptors of second language and source language to have the closest response.

Multi-phase bus signal priority strategy at isolated intersections

To satisfy the multiple priority requests from buses that arrive at different phases within a small time window, a multi-phase bus signal priority （MPBSP） strategy is developed. The proximity principle is brought forward to settle the conflicts among multiple priority requests and arrange the optimal priority sequence. To avoid over saturation of the intersection, a conditional MPBSP algorithm that adopts early green and green extension strategies is developed to give priority to the bus with the highest priority level when green time that each phase runs makes its saturation degree not larger than 0. 95. Finally, the algorithm is tested in the VISSIM environment and compared with the normal signal timing algorithm. Sensitive analysis of the number of priority phases, bus demand, and volume to capacity ratios are conducted to quantify their impacts on the benefits of the MPBSP. Results show that the MPBSP strategy can effectively reduce bus delays, and with the increase in the number of priority phases, the reduction range of bus delays also increases.

On Priority of “Meaning” in Translation

In this paper the author expounded the term "meaning" from the perspectives of semantics,semiotics and pragmatics and talked about the importance and priority of "meaning" in translation.

RESEARCH ON WEIGHTED PRIORITY OF EXEMPLAR-BASED IMAGE INPAINTING

The priority of the filled patch play a key role in the exemplar-based image inpainting, and it should be determined firstly to optimize the process of image inpainting. A modified image inpainting algorithm is proposed by weighted-priority based on the Criminisi algorithm. The improved algorithm demonstrates better relationship between the data term and the confidence term for the optimization of the priority than the classical Criminisi algorithm. By comparing the effect of the inpainted images with different structure, conclusion can be drawn that the optimal priority should be chosen properly for different images with different structures.

New approach to determine the priorities from interval fuzzy preference relations

An approach is proposed to solve the problem how to obtain the priorities from interval fuzzy preference relations. Firstly, another expression of interval numbers is given. Then, some basic definitions on consistency and weak transitivity of real and interval fuzzy preference relations are described. Based on these definitions, a two-phase process for determining the priorities from interval fuzzy preference relations is presented. Finally, two exam- ples are used to illustrate the use of the proposed approach.

Dynamic channel reservation scheme based on priorities in LEO satellite systems

According to low earth orbit（LEO） satellite systems with users of different levels, a dynamic channel reservation scheme based on priorities is proposed. Dynamic calculation of the thresholds for reserved channels is the key of this strategy. In order to obtain the optimal thresholds, the traffic is predicted based on the high-speed deterministic movement property of LEO satellites firstly. Then, a channel allocation model based on Markov is established. Finally, the solution of the model is obtained based on the genetic algorithm. Without user location, this strategy effectively reduces handover failures and improves channel utilization by adjusting dynamically the thresholds according to traffic conditions. The simulation results show that the system＇s overall quality of service can be improved by this strategy.