In many countries, ImpactFactor (IF) is one of the criteria applied to evaluate not only the status of scientific journals, but also the publication output of scientists. In these evaluation exercises, ImpactFactor is frequently considered as an indicator of research quality and scientific excellence. Sometimes, publication in mainstream journals or impact journals defined as those with an IF, i.e. those covered by the Journal Citation Reports used as the only evaluation criteria in such a way that scientific tribunals pay more attention to the IF of the journal than to the quality of the scientific contribution itself. Impactfactor in simple terms indicates the rating of journal articles. It has been defined by different experts since 1960s. Dr. Eugene Garfield who was the founder of the Institute for Scientific Information, currently the chairman Emeritus of Thomson Scientific, Philadelphia first mentioned the idea of an ImpactFactor in Science in 1955. Presently, Leo Egghe interprets the impactfactor of a journal as the average of a number of independent and identically distributed random variables. Each random variable represents the number of citations of one of the articles published in the journal. Impact factors are
A boycott of high-impact journals. Nobelist and eLife Editor- in-Chief Randy Schekman has recently criticized the monopoly of what he calls “luxury journals” in an editorial published in the British newspaper The Guardian. Schekman has vowed not to publish hereafter in Nature, Cell, and Science, stating that the dis- proportionate rewards associated with publishing in those jour- nals distorts science in a manner akin to the effects of large bo- nuses on the banking industry (53). Although such efforts are well-intentioned, we are skeptical that boycotting the impact fac- tor or the “luxury journals” will be effective, because the econom- ics of current science dictate that scientists who succeed in pub- lishing in such journals will accrue disproportionate rewards. This will continue to be an irresistible attraction. Even if the journal impactfactor were to disappear tomorrow, the prestige associated with certain journals would persist, and authors would continue to try to publish there. Most scientists do not actually know the impactfactor of individual journals— only that publication in such journals is highly sought after and respected. For instance, it is not widely known that Science is actually only ranked 20th among all journals in impactfactor, lower than journals such as CA—A Cancer Journal for Clinicians and Advanced Physics. Simi- larly, we fear that boycotts of specific prestigious journals may hurt the trainees of those laboratories by depriving them of high- visibility venues for their work. In lieu of Science, Nature, or Cell, Schekman has recommended that authors submit their best pa- pers to eLife. However, the managing executive editor has de- scribed eLife as “a very selective journal,” further noting that “it’s likely that the rejection rate will be quite high” (54). As long as a critical mass of scientists continues to submit their best work to highly selective journals, impactfactor mania, or its equivalent, is likely to persist.
Even the scholars in medical sciences (that have a very high IF) question the validity of the journal impactfactor as a measure of relevance of individual articles or scholars . Some scholars hold that the rise of the Journal ImpactFactor is a result of the perceived value of quantification measures in the contemporary society and the restructuring of capitalism. A key implication of this acceptance is an increase in global academic dependency . It may be noted that in India we have hardly any journal that has an impactfactor greater than one. For example, even the IDEAS (which is especially indexing economics and some statistics journals) index only six Indian journals in economics and the highest IF is less than one; interestingly, the Indian Economic Review, of the reputed Department of Economics, Delhi School of Economics has an impactfactor only about 0.24. For physical and life sciences journals too, the conditions are not much better.
Like the argument from ignorance, the argument from expert opinion and the ad hominem argument are not always bad arguments. Their quality varies as a function of how informative the authority status, or the personal attributes of the instance endorsing them, is for the problem at hand. Policy decisions are routinely based on the advice of experts, and there seems to be agreement that this is a good thing to do, as long as the experts are really considered experts in their field and their advice is not biased (Harris et al., 2016; c.f. Sloman and Fernbach, 2017). Dismissing an argument because of personal attributes of a person endorsing it is often more difficult, because it has to be made plausible that those attributes are relevant to the quality of the argument. For example, that one does not need to be a mother to be qualified for being prime minister seems obvious, whereas a case of a person applying to a position against gender discrimination, who in his private life beats his wife, is likely to be more controversial. In the case of the JIF, we would have to justify why we think that a low impactfactor indicates that a particular journal is of low quality, and why this low quality can be transferred to a particular paper within it. Such a judgment requires further information about the journal and about the paper at hand to be justified, which is usually not provided and difficult to obtain since it might e.g., not be clear if review processes in lower JIF journals are less able to detect errors (Brembs, 2018). Thus, whereas a high impactfactor may add to the reputation of a journal, a low impactfactor does not warrant a bad reputation, but rather provides insufficient information about reputation (see Table 1 for examples of the inductive and deductive fallacies as discussed here).
Despite these limitations, citation counts provide a con- venient and objective method of ranking articles and jour- nals. It is therefore important to use the most appropriate and transparent way of communicating this information, particularly if such rankings are used to define quality. The criticism of the impactfactor itself has grown as its influence increases. Articles such as editorials, letters and news items are classified as "non-source" items and as such does not count towards the total number of articles used to calculate the impactfactor. However, such items may attract numerous citations which are counted towards a journal's impactfactor. Journals may increase the number of non-source items to artificially increase impact factors. It is also suggested that the calculation provides a method for comparing journals regardless of their size. However journal size may be a confounding factor- journals publishing more articles tend to have higher impact factors per se. Small journals may be disadvantaged by this bias. Most importantly impact fac- tor does not communicate any information about the citation distribution to the reader.
This proposal also applies to other journal performance indicators that may be used. For example, the immediacy index is the number of citations received by a journal in the last complete year, divided by the number of articles published by that journal in that year. It therefore gives a measure of how quickly articles from a journal are cited. Like the journal impactfactor, it avoids any advantage to larger journals, but it may advantage those that publish more frequently. This measure has more uncertainty asso- ciated with it than for the journal impactfactor (data not shown) because it is based on a shorter time period. Even if only broad banding of journal immediacy index ranks are used, most journals outside the top ones could not confidently identify whether they were ranked in the top or bottom halves of the table.
Journal ImpactFactor (JIF) means average number of citations to articles published in journals, books, thesis, project reports, news papers, conference/ seminar proceedings, documents published in internet, notes and any other approved documents. It is calculated in yearly/half- yearly/ Quarterly/Monthly for the journals that are indexed in Journal Reference Reports (JRR).Objective: We analyzed to what extent impactfactor affects the quality of journal & is that the only factor which affects the quality of journal. Method: Factors affecting quality of research papers considered, analyzed and correlation with journal impactfactor will be established. Conclusion: Factors affecting quality of journals have no impact on Journal’s ImpactFactor. Implications: Analyzing journals through impactfactor, does not ensure researcher to get quality data for references and hence dependency on journal impactfactor is questionable.
The initial estimates which are prepared should be maximum in accordance to the project and it is necessary as it can directly affect the fund requirements in the execution of project. It is necessary to identify the necessity of VE in any project. The VE can only be applied on projects which can have considerable cost benefit. Hence it is useful if we apply value Table 14 Impactfactor and cost reduction final analysis
(b) What a decision-maker can do if there are several rankings but he/she needs just one? Thus, we began with analysis of correlations between the rankings based on seven popular indicators, which are impactfactor (IF), 5-year impactfactor (IF-5), immediacy index (II), article influence score (AI), h-index (Hirsch), SNIP and SJR. This had already been done in a number of comparative studies, which were focused either on indicators from different databases (Archambault et al., 2009; Delgado & Repiso, 2013; Leydesdorff, 2009), or on citation, network and usage metrics (Bollen et al., 2009). The reviews of Waltman (2016), Rousseau (2002) and Glänzel (2003) may serve as an introduction to the vast literature on citation indicators. In agreement with the previous results, we confirmed that all rankings are
scheduling among VMs. In this paper, we present the experimental research on performance interference in parallel processing of CPU-intensive and network-intensive workloads on Xen virtual machine monitor (VMM). Based on our study, we conclude with five key findings which are critical for effective performance management and tuning in virtualized clouds. First, colocating network- intensive workloads in isolated VMs incurs high overheads of switches and events in Dom0 and VMM. Second, colocating CPU-intensive workloads in isolated VMs incurs high CPU contention due to fast I/O processing in I/O channel. Third, running CPU-intensive and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. Fourth, performance of network-intensive workload is insensitive to CPU assignment among VMs, whereas adaptive CPU assignment among VMs is critical to CPU-intensive workload. The more CPUs pinned on Dom0 the worse performance is achieved by CPU-intensive workload. Last, due to fast I/O processing in I/O channel, limitation on grant table is a potential bottleneck in Xen. We argue that identifying the factors that impact the total demand of exchanged memory pages is important to the in-depth understanding of interference costs in Dom0 and VMM.
In this paper work we have proposed the partial product perforation technique to produce approximate hardware multipliers. The proposed technique eliminates a number of partial products and thus enabling power and high area saving at the same time retaining high accuracy. Under rigorous error analysis, we have analytically characterized the induced error metrics and thereby proving that the error is bounded and predictable. We also proposed two error correction methods that help in trading a small increase in power for high error reduction. We also explored product perforation on a large set of multiplier architectures and evaluated its impact on different architectures and error bounds. While comparing to the state-of the-art approximation techniques, we showcased that the proposed approach can achieve significant gains in area, power and quality metrics of image processing and data analytics algorithms. Finally, we proved that our technique is scalable and can offer better results when the multiplier‟s bit width increases.
applications. In this introductory chapter we will briefly review the history of wireless networks, from the smoke signals of the Pre-industrial age to the cellular, satellite, and other wireless networks of today. We then discuss the wireless vision in more detail, including the technical challenges that must be overcome to make this vision a reality. We will also describe the current wireless systems in operation today as well as emerging systems and standards. The huge gap between the performance of current systems and the vision for future systems indicates that much research remains to be done to make the wireless vision a reality. The technical problems that must be solved to make the wireless vision a reality extend across all levels of the system design. At the hardware level the terminal must have multiple modes of operation to support the different applications and media. Desktop computers currently have the capability to process voice, image, text, and video data, but breakthroughs in circuit design are required to implement multimode operation in a small, lightweight, handheld device. Since most people don’t want to carry around a twenty pound battery, the signal processing and communications hardware of the portable terminal must consume very little power, which will impact higher levels of the system design. Many of the signal processing techniques required for efficient spectral utilization and networking demand much processing power, precluding the use of low power devices. Hardware advances for low power circuits with