“优先序、时度效”理念在新闻报道中的应用研究

文章探讨“优先序、时度效”理念在新闻报道中的应用。首先阐释这一理念的内涵及在新闻工作中的重要性,指出其是检验新闻舆论工作水平的重要标尺。文章深入分析如何在新闻实践中明确“优先序”、把握“时度效”、拿捏分寸和追求效果。在“优先序”方面,强调对重大事件、社会热点和民生关切的把握。在“时度效”方面,探讨如何在保证时效性的同时,确保报道的深度和广度,并使传播效果最大化。通过中央广播电视总台关于杭州第19届亚运会的报道为例,探索该理念在新闻报道中的具体应用策略,阐述如何在大型体育赛事报道中应用“优先序、时度效”理念,体现新闻工作的专业水准。文章指出“优先序”与“时度效”之间的内在联系,二者相辅相成,共同推动新闻报道质量的提升;分析在快速变化的媒体环境中应用这一理念所面临的挑战,如信息爆炸、传播渠道多元化、受众需求变化等,并提出相应的建议,旨在提升新闻报道质量等。

A hybrid algorithm based on ILP and genetic algorithm for time-aware test case prioritization

To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number of covered program entities a d satisfy time constraints is selected by integer linea progamming.Secondly,the individual is encoded according to the cover matrices of entities,and the coverage rate of program entities is used as the fitness function and the genetic algorithm is used to prioritize the selected test cases.Five typical open source projects are selected as benchmark programs.Branch and method are selected as program entities,and time constraint percentages a e 25%and 75%.The experimental results show that the ILP-GA convergence has faster speed and better stability than ILP-additional and IP-total in most cases,which contributes to the detection of software defects as early as possible and reduces the software testing costs.

DIMENSIONALITY REDUCTION FOR HYPERSPECTRAL IMAGERY BASED ON FASTICA

The high dimensions of hyperspectral imagery have caused burden for further processing. A new Fast Independent Component Analysis (FastICA) approach to dimensionality reduction for hyperspectral imagery is presented. The virtual dimensionality is introduced to determine the number of dimensions needed to be preserved. Since there is no prioritization among independent components generated by the FastICA,the mixing matrix of FastICA is initialized by endmembers,which were extracted by using unsupervised maximum distance method. Minimum Noise Fraction (MNF) is used for preprocessing of original data,which can reduce the computational complexity of FastICA significantly. Finally,FastICA is performed on the selected principal components acquired by MNF to generate the expected independent components in accordance with the order of endmembers. Experimental results demonstrate that the proposed method outperforms second-order statistics-based transforms such as principle components analysis.

Application of Fuzzy Discrete Event System in Air Conditioning Energy-saving

Air conditioning (AC) system is the one with asynchronous and uncertain nature. In this paper, the fuzzy discrete event system (FDES) is introduced to the research of AC energy-saving control. A fuzzy automaton modeling is given for AC energy-saving control and effectiveness optimization is made. To facilitate the implement of the control and energy saving, priorities have been assigned to the major control steps based on logical reasoning. Forward-looking tree modeling based on FDES has been simplified to help further optimization, and a simple and concrete example has been put forward illustrating energy-saving control in AC system.

Extraction,Utilization Pattern and Prioritization of Fuel Resources for Conservation in Manali Wildlife Sanctuary,Northwestern Himalaya

Fuelwood is the main source of the energy in mountainous regions.Hence,annual wood consumption is very high.Information on fuelwood resources,and their extraction and availability is very scanty.Therefore,present study was carried out to study the diversity of fuelwood species,annual collection,preference and availability of fuel species in the forests.Thirty four species(25 trees and 9 shrubs) were extracted for fuel by the inhabitants.Total collection and species preference was highest for Picea smithiana,Cedrus deodara,Indigofera heterantha,Pinus wallchiana and Sorbaria tomentosa,respectively.Resource use index indicating use pressure was highest for P.smithiana,C.deodara,I.heterantha and Abies pindrow,respectively.Besides native species,some non-native horticultural and agroforestry species such as Malus pumila,P.domestica,Celtis australis,etc.were also being used as fuel.Preferred species showed their availability in eight forest types whereas,population and regeneration status was poor.Therefore,immediate actions are suggested to sustain current and future demand of fuelwood.The afforestation of degraded,uncultivated and marginal lands through high quality and preferred fuel species might reduce pressure on wild and selective species.

Modeling and Optimisation of Precedence-Constrained Production Sequencing and Scheduling for Multiple Production Lines Using Genetic Algorithms

This paper presents an integrated methodology for the modelling and optimisation of precedence-constrained production sequencing and scheduling for multiple production lines based on Genetic Algorithms （GA）. The problems in this class are NP-hard combinatorial problems, requiring a triple optimisation at the same time： allocation of resources to each line, production sequencing and production scheduling within each production line. They are ubiquitous to production and manufacturing environments. Due to nature of constraints, the length of solutions for the problem can be variable. To cope with this variability, new strategies for encoding chromosomes, crossover and mutation operations have been developed. Robustness of the proposed GA is demonstrated by a complex and realistic case study.

Impacts of Coordinated Traffic Signal Control Strategies and Bus Priority

Delay in signalized intersections may constitute a significant part of bus journey times in urban environment. Providing priority for buses at traffic signals can be an effective measure to reduce this delay. Bus priority in Swedish urban traffic signal systems are normally coordinated with fixed time plan selection. Within this framework local traffic actuated signal timing adjustments are applied based on detector inputs aimed to reduce the number of vehicles in the dilemma zone. Active bus priority is also achieved with the aim to display green signal at the arrival of the bus to the stop line. Due to lack of knowledge of traffic performance impacts of these techniques a major research study was undertaken funded by the Swedish Road Administration. The aim was to evaluate the following control strategies using Stockholm as case study： （1） Fixed time coordination （FTC）; （2） Fixed time coordination with local signal timing adjustment （FTC-LTA）; （3） FTC-LTA with active bus priority （PRIBUSS）; （4） Self-optimizing control （SPOT） with active bus priority. The methodologies for the study included field data collection using mobile and stationary techniques, offiine signal timing calculations with TRANSYT, microscopic simulation modeling using the HUTSIM model. The study obtained the following results： （1） Local traffic adjustment with the manual FTC reduced total delay by 1%. （2） Signal timings determined using TRANSYT reduced the average intersection delay by 9% compared to manual signal settings. （3） Local traffic adjustment reduced total delay by a further 5%. （4） Bus travel time was reduced by 11% using PRIBUSS, and 28% using SPOT. （5） Travel time for all vehicles did not increase using PRIBUSS, and was reduced by 6.5% with SPOT. Results of comparing PRIBUSS and SPOT to FTC-LTA were shown to be statistically significant.

Prioritization of liver MRI for distinguishing focal lesions

Liver cancer is one of the leading causes of cancer-related mortality worldwide.Magnetic resonance imaging(MRI) is a non-invasive imaging technique that is often used by radiologists for diagnosis and surgical planning.Analysis of a large amount of liver MRI data for each patient limits the radiologist's efficiency and may lead to misdiagnoses.The redundant MRI data,especially from dynamic contrast enhanced(DCE) sequences,is also a bottleneck in transmitting the images via the internet or PACS for remote consultancy in a reasonable amount of time.This study included 25 patients(aged between 20 and 70years) with liver cysts(seven cases),hemangiomas(eight cases),or hepatic cell carcinomas(10 cases).DCE T1 WI MRI was performed for all the patients.The diagnosis reference included typical MRI findings and post-surgery pathology.The methods were as follows:(i) MRI sequence pre-processing based on large vessels variation level set method to remove non-liver parts from MRI images;(ii) human visual model features(luminance,motion,and contour) extraction and fusion;(iii) anomaly-based MRI ranking;and(iv) methods assessment with the 25 patients' DCE MRI data.The prioritization methods applied to the DCE images could automatically assimilate and determine the content of the medical images,identifying the liver cysts,hemangiomas,and carcinomas.The average uniformity between radiologists and prioritization with the proposed method was 0.805,0.838,and0.818 for cysts,hemangiomas,and carcinomas,respectively,which indicates that the proposed method is an efficient method for liver DCE image prioritization.

RePizer：a framework for prioritization of software requirements

The standard software development life cycle heavily depends on requirements elicited from stakeholders. Based on those requirements, software development is planned and managed from its inception phase to closure. Due to time and resource constraints, it is imperative to identify the high-priority requirements that need to be considered first during the software development process. Moreover, existing prioritization frameworks lack a store of historical data useful for selecting the most suitable prioritization technique of any similar project domain. In this paper, we propose a framework for prioritization of software requirements, called Re Pizer, to be used in conjunction with a selected prioritization technique to rank software requirements based on defined criteria such as implementation cost. ReP izer assists requirements engineers in a decision-making process by retrieving historical data from a requirements repository. Re Pizer also provides a panoramic view of the entire project to ensure the judicious use of software development resources. We compared the performance of Re Pizer in terms of expected accuracy and ease of use while separately adopting two different prioritization techniques, planning game（PG） and analytical hierarchy process（AHP）. The results showed that Re Pizer performed better when used in conjunction with the PG technique.

Incorporating functional annotation information in prioritizing disease associated SNPs from genome wide association studies

With recent advances in genotyping and sequencing technologies,many disease susceptibility loci have been identified.However,much of the genetic heritability remains unexplained and the replication rate between independent studies is still low.Meanwhile,there have been increasing efforts on functional annotations of the entire human genome,such as the Encyclopedia of DNA Elements(ENCODE)project and other similar projects.It has been shown that incorporating these functional annotations to prioritize genome wide association signals may help identify true association signals.However,to our knowledge,the extent of the improvement when functional annotation data are considered has not been studied in the literature.In this article,we propose a statistical framework to estimate the improvement in replication rate with annotation data,and apply it to Crohn’s disease and DNase I hypersensitive sites.The results show that with cell line specific functional annotations,the expected replication rate is improved,but only at modest level.

Fuzzy-based risk prioritization for a hydrogen refueling facility in Malaysia

Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Before hydrogen fuel and its facilities can be introduced to the public, relevant safety issues and its hazards must be assessed in order to avoid any chance of injury or loss. While a traditional risk assessment has difficulty in prioritizing the risk of failure modes, this paper proposes a new fuzzy-based risk evaluation technique which uses fuzzy value to prioritize the risk of various scenarios. In this study, the final risk of each failure modes was prioritized by using the MATLAB fuzzy logic tool box with a combination of two assessments. The first assessment was concerned with the criteria which affected the actual probability of occurrence. This assessment considered the availability of the standard that was applied to prevent the likelihood of the scenario occurring. On the other hand, the second assessment was focused on evaluating the consequence of the failure by taking into account the availability of detection and the complexity of the failure rather than only the severity of the scenarios. A total of 87 failure scenarios were identified using failure modes and effect analysis (FMEA) procedures on hydrogen refueling station models. Fuzzy-based assessments were performed through risk prioritizing various failure scenarios with a fuzzy value (0 to 1) and risk level (low, medium, and high) while a traditional risk assessment approach presented the risks only in forms of level (low, medium, and/or high). Availability of the fuzzy value enabled further prioritizing on the risk results that fell in the same level of risk. This study concluded that fuzzy-based risk evaluation is able to further prioritize the decisions when compared with a traditional risk assessment method.