Predictivism holds that, where evidence E confirms theory T, E confirms T more strongly when E is predicted on the basis of T and subsequently confirmed than when E is known in advance of T's formulation and used, in some sense, in the formulation of T. Predictivism has lately enjoyed some strong supporting arguments from Maher (1988, 1990, 1993) and Kahn, Landsberg, and Stockman (1992). Despite the many virtues of the analyses these authors provide it is my view (...) that they (along with all other authors on this subject) have failed to understand a fundamental truth about predictivism: the existence of a scientist who predicted T prior to the establishment that E is true has epistemic import for T (once E is established) only in connection with information regarding the social milieu in which the T-predictor is located and information regarding how the T-predictor was located. The aim of this paper is to show that predictivism is ultimately a social phenomenon that requires a social level of analysis, a thesis I deem social predictivism. (shrink)

Predictivism asserts that novel confirmations carry special probative weight. Epistemic pluralism asserts that the judgments of agents (about, e.g., the probabilities of theories) carry epistemic import. In this paper, I propose a new theory of predictivism that is tailored to pluralistic evaluators of theories. I replace the orthodox notion of use-novelty with a notion of endorsement-novelty, and argue that the intuition that predictivism is true has two roots. I provide a detailed Bayesian rendering of this theory (...) and argue that pluralistic theory evaluation pervades scientific practice. I compare my account of predictivism with those of Maher and Worrall. Introduction Why construction is a red herring for pluralist evaluators The unvirtuous accommodator Virtuous endorsers and the two roots of predictivism The two roots in Bayesian terms: the priors and background beliefs of endorsers Who are the pluralist evaluators? Two contemporary theories of predictivism 7.1 Maher: Reliable methods of theory construction 7.2 Worrall: The confirmation of core ideas Conclusion. (shrink)

This is a comment on the paper by Barnes and the responses from Scerri and Worrall, debating the thesis that a fact successfully predicted by a theory is stronger evidence than a similar fact known before the prediction was made. Since Barnes and Scerri both use evidence presented in my paper on Mendeleev’s periodic law to support their views, I reiterate my own position on predictivism. I do not argue for or against predictivism in the normative sense that (...) philosophers of science employ, rather I describe how scientists themselves use facts and predictions to support their theories. I find wide variations, and no support for the assumption that scientists use a single ‘Scientific Method’ in deciding whether to accept a proposed new theory.Keywords: Predictivism; Novel predictions; Accommodation; Periodic law; Periodic table; Dmitri Mendeleev. (shrink)

Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of (...) the no miracle argument. So, if the deductivists are right, the most powerful argument for realism collapses. There seems to be an inescapable contradiction between these prima facie plausible arguments of predictivists and deductivists; but this puzzle can be solved by understanding what exactly counts as novelty, if novel predictions must support the no miracle argument, i.e., if they must be explainable only by the truth of theories. Taking my cues from the use-novelty tradition, I argue that (1) the predicted data must not be used essentially in building the theory or choosing the auxiliary assumptions. This is possible if the theory and its auxiliary assumptions are plausible independently of the predicted data, and I analyze the consequences of this requirement in terms of best explanation of diverse bodies of data. Moreover, the predicted data must be (2) a priori improbable, and (3) heterogeneous to the essentially used data. My proposed notion of novelty, therefore, is not historical, but functional. Hence, deductivists are right that confirmation is independent of time and of historical contingencies such as if the theorist knew a datum, used it, or intended to accommodate it. Predictivists, however, are right that not all consequences confirm equally, and confirmation is not purely a logical theory-data relation, as it crucially involves background epistemic conditions and the notion of best explanation. Conditions (1)–(3) make the difference between prediction and accommodation, and account for the confirming power of theoretical virtues such as non ad-hocness, non-fudging, non-overfitting, independence and consilience. I thus show that functional novelty (a) avoids the deductivist objections to predictivism, (b) is a gradual notion, in accordance with the common intuition that confirmation comes in degrees, and (c) supports the no miracle argument, so vindicating scientific realism. (shrink)

사용-참신성 예측주의에 따르면, 가설 구성에 사용된 자료는 증거가 되기 어렵다. DNA 이중 나선 구조의 발견에 대한 사례 연구는 이에 대한 반례를 제공한다. 로잘린드 프랭클린의 DNA X선 회절 사진은 이중 나선 가설의 구성에 사용된 동시에 증거로도 사용되었다. 이 사례에서 증거는 제약에 의한 대안가설의 명시적 제거에 의존하는 증거와 제약들 사이의 정합성 확인에 의존하는 증거로 구분되며, 두 증거 모두 ‘사용-참신한 예측’이라는 조건에는 의존하지 않는다.

Predictivism is the view that successful predictions of “novel” evidence carry more confirmational weight than accommodations of already known evidence. Novelty, in this context, has traditionally been conceived of as temporal novelty. However temporal predictivism has been criticized for lacking a rationale: why should the time order of theory and evidence matter? Instead, it has been proposed, novelty should be construed in terms of use-novelty, according to which evidence is novel if it was not used in (...) the construction of a theory. Only if evidence is use-novel can it fully support the theory entailing it. As I point out in this paper, the writings of the most influential proponent of use-novelty contain a weaker and a stronger version of use-novelty. However both versions, I argue, are problematic. With regard to the appraisal of Mendeleev’ periodic table, the most contentious historical case in the predictivism debate, I argue that temporal predictivism is indeed supported, although in ways not previously appreciated. On the basis of this case, I argue for a form of so-called symptomatic predictivism according to which temporally novel predictions carry more confirmational weight only insofar as they reveal the theory’s presumed coherence of facts as real. (shrink)

We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. (...) Some say that pre-analysis plans are epistemically meritorious while others deny this, and in practice pre-analysis plans are often violated. We resolve this debate with a modest defence of pre-analysis plans. Further, we argue that pre-analysis plans can be epistemically relevant even if the plan is not strictly followed—and suggest that allowing for flexible pre-analysis plans may be the best available policy option. (shrink)

In this paper I comment on a recent paper by [Scerri, E., & Worrall, J. . Prediction and the periodic table. Studies in History and Philosophy of Science, 32, 407–452.] about the role temporally novel and use-novel predictions played in the acceptance of Mendeleev’s periodic table after the proposal of the latter in 1869. Scerri and Worrall allege that whereas temporally novel predictions—despite Brush’s earlier claim to the contrary—did not carry any special epistemic weight, use-novel predictions (...) did indeed contribute to the acceptance of the table. Although I agree with their first claim, I disagree with their second. In order to spell out my disagreement, I not only revisit Scerri and Worrall’s interpretation of crucial historical evidence they have cited in support of the ‘heuristic account’ of use-novel predictions, but I also criticise the latter on general grounds.Keywords: Periodic table; Dmitri Mendeleev; Noble gases; Use-novel predictions; Heuristic account; Ad hoc hypotheses. (shrink)

Many studies have suggested that the motor system is organized in a hierarchical fashion, around the prototypical end location associated with using objects. However, most studies supporting the hierarchical view have used well-known actions and objects that are highly over-learned. Accordingly, at present it is unclear if the hierarchical principle applies to learning the use of novel objects as well. In the present study we found that when learning to use a novel object subjects acquired an action representation (...) of the end location associated with using the object, as evidenced by slower responses in an action observation task, when the object was presented at an incorrect end location. By showing the importance of knowledge about end locations when learning to use a novel object, the present study suggests that end locations are a fundamental organizing feature of the human motor system. (shrink)

Background Our objective was to evaluate whether the description of a machine learning (ML) app or brain imaging technology to predict the onset of schizophrenia or alcohol use disorder (AUD) influences healthcare professionals’ judgments of stigma, empathy, and compassion. Methods We randomized healthcare professionals (N = 310) to one vignette about a person whose clinician seeks to predict schizophrenia or an AUD, using a ML app, brain imaging, or a psychosocial assessment. Participants used scales to measure their judgments of stigma, (...) empathy, and compassion. Results Participants randomized to the ML vignette endorsed less anger and more fear relative to the psychosocial vignette, and the brain imaging vignette elicited higher pity ratings. The brain imaging and ML vignettes evoked lower personal responsibility judgments compared to the psychosocial vignette. Physicians and nurses reported less empathy than clinical psychologists. Conclusions The use of predictive technologies may reinforce essentialist views about mental health and substance use that may increase specific aspects of stigma and reduce others. (shrink)

Helen Neville has gathered ERP data suggesting that accessing an “implicit” memory system produces a qualitatively different kind of ERP wave than does accessing our “explicit” conscious memory system. These results corroborate the hypothesis that an early anterior priming effect indexes activity of a system specialized for words, while a later posterior priming effect indexes access to general, episodic representations of words. Moreover, she saw no effects in the masked paradigms using pseudo-words, further supporting the notion of an early lexicon. (...) However, we might not see any effects because the tasks use stimuli too complicated for an early automatic system to encode rapidly. Hence, masked priming effects for novel stimuli might be seen immediately with very simple input patterns. The following series of experiments was designed to test this hypothesis, as well as to try to differentiate the supposed early lexicon from other sorts of early access memory systems and to characterize more fully the capabilities of these early systems. In particular, ERP waveforms are compared for unmasked and masked priming conditions using simple 5-line visual patterns in experiments requiring subjects to make rapid decisions concerning the physical structure of the shapes. (shrink)

This study investigates the epistemic role and value of prediction in science: do predictions, and what kind of predictions, justify belief in scientific theories? In the philosophy of science, the epistemic role of prediction has been understood mainly in terms of novel prediction. Scientific theories are considered to gain special epistemic support if they predict novel empirical results that were not used in their construction. This view has played a central role in two debates in the field: prediction (...) vs. accommodation and scientific realism vs. anti-realism. In the former debate, predictivists seek to explain why novel predictions confirm the theory more strongly than accommodations, i.e. empirical results that were used in the construction of the theory. In the latter debate, predictivists argue that novel prediction is one of the most important criteria of empirical success that justifies realist commitment to scientific theories. -/- . (shrink)

For synchronization of a class of chaotic systems in the presence of nonvanishing uncertainties, a novel time-varying gain observer-based sliding mode control is proposed. First, a novel time-varying gain disturbance observer is developed to estimate the uncertainties. Then, by using the output of TVGDO to modify sliding mode control, a new TVGDO-based SMC scheme is developed. Although the observation and control precision of conventional fixed gain disturbance observer-based control for chaotic systems can be guaranteed by a high observer (...) gain, the undesirable spike problem may be caused by the high gain if the initial values of estimate and true states are not equal. The most attractive feature of this work is that the newly proposed TVGDO can eliminate the spike problem by developing a time-varying gain scheme. Finally, the effectiveness of the proposed method is demonstrated by the numerical simulation. (shrink)

In this research work a novel two-step system for anomaly detection is presented and tested over several real datasets. In the first step the novel Exploratory Projection Pursuit, Beta Hebbian Learning algorithm, is applied over each dataset, either to reduce the dimensionality of the original dataset or to face nonlinear datasets by generating a new subspace of the original dataset with lower, or even higher, dimensionality selecting the right activation function. Finally, in the second step Principal Component Analysis (...) anomaly detection is applied to the new subspace to detect the anomalies and improve its classification capabilities. This new approach has been tested over several different real datasets, in terms of number of variables, number of samples and number of anomalies. In almost all cases, the novel approach obtained better results in terms of area under the curve with similar standard deviation values. In case of computational cost, this improvement is only remarkable when complexity of the dataset in terms of number of variables is high. (shrink)

Predictivism, the thesis that all things being equal a hypothesis that predicts a piece of evidence is better supported by that evidence than a hypothesis that only accommodates that evidence, comes in strong and weak forms. Interestingly, weak predictivism, which is widely accepted, can be used to formulate a persuasive argument against some forms of external world scepticism. In this article I formulate this predictivist argument and I explain why it deserves serious consideration despite the fact that it (...) only succeeds as a response to some forms of external world scepticism. (shrink)

IntroductionConcussion is a growing public health concern. No uniformly established therapy exists; neurofeedback studies report treatment value. We use infralow frequency neuromodulation to remediate disabling neurological symptoms caused by traumatic brain injury and noted improved outcomes with a novel concussion protocol. Postconcussion symptoms and persistent postconcussion symptoms are designated timelines for protracted neurological complaints following TBI. We performed a retrospective study to explore effectiveness of ILF in PCS/PPCS and investigated the value of using this concussion protocol.MethodPatients with PCS/PPCS seen (...) for their first neurology office visit or received their first neurofeedback session between 1 August 2018 and 31 January 2021 were entered. Outcomes were compared following treatment as usual vs. TAU with ILF neurotherapy. The study cohort was limited to PPCS patients; the TAU+ILF group was restricted further to PPCS patients receiving at least 10 neurotherapy sessions. Within the TAU+ILF group, comparisons were made between those who trained at least 10 sessions using concussion protocol and those who trained for at least 10 sessions of ILF regardless of protocol.ResultsAmong our resultant PPCS cohort leading persistent neurological complaints were headache, memory impairment, and brain fog. PPCS patients in TAU+ILF+CP demonstrated greater net and percent improvement of symptoms compared to PPCS subjects in TAU. PPCS patients in TAU+ILF-CP trended toward significant symptom improvements compared to TAU, and TAU+ILF+CP trended toward greater efficacy than TAU+ILF-CP.ConclusionPPCS patients who received TAU+ILF+CP demonstrated significantly greater improvement as a group when compared to TAU. When used as an integrative modality to treatment as usual in managing patients with PPCS, ILF neuromodulation with use of concussion protocol provided significant symptom improvements. (shrink)

Lower extremity non-contact soft tissue injuries are prevalent in elite futsal. The purpose of this study was to develop robust screening models based on pre-season measures obtained from questionnaires and field-based tests to prospectively predict LE-ST injuries after having applied a range of supervised Machine Learning techniques. One hundred and thirty-nine elite futsal players underwent a pre-season screening evaluation that included individual characteristics; measures related to sleep quality, athlete burnout, psychological characteristics related to sport performance and self-reported perception of chronic (...) ankle instability. A number of neuromuscular performance measures obtained through three field-based tests [isometric hip strength, dynamic postural control and lower extremity joints range of motion ] were also recorded. Injury incidence was monitored over one competitive season. There were 25 LE-ST injuries. Only those groups of measures from two of the field-based tests, as independent data sets, were able to build robust models [area under the receiver operating characteristic curve score ≥0.7] to identify elite futsal players at risk of sustaining a LE-ST injury. Unlike the measures obtained from the five questionnaires selected, the neuromuscular performance measures did build robust prediction models. The inclusion in the same data set of the measures recorded from all the questionnaires and field-based tests did not result in models with significantly higher performance scores. The model generated by the UnderBagging technique with a cost-sensitive SMO as the base classifier and using only four ROM measures reported the best prediction performance scores. The models developed might help coaches, physical trainers and medical practitioners in the decision-making process for injury prevention in futsal. (shrink)

Most of the existing classification techniques concentrate on learning the datasets as a single similar unit, in spite of so many differentiating attributes and complexities involved. However, traditional classification techniques are required to analyze the datasets prior to learning, and if not doing so, they loss their performance in terms of accuracy and AUC. To this end, many of the machine learning problems can be very easily solved just by carefully observing human learning and training nature and then mimicking the (...) same in the machine learning. In response to these issues, we present a comprehensive suite of experiments carefully designed to provide conclusive, reliable, and significant results to the problem of efficient learning. This paper proposes a novel, simple, and effective machine learning paradigm that explicitly exploits this important similar-to-different (S2D) human learning strategy and implements it based on two algorithms (C4.5 and CART) efficiently. The framework not only analyzes the data sets prior to implementation, but also carefully allows classifier to have a systematic study so as to mimic the human training technique designed for efficient learning. Experimental results show that the method outperforms the state-of-the-art methods in terms of learning capability and breaks through the gap between human and machine learning. In fact, the proposed similar-to-different (S2D) strategy may also be useful in efficient learning of real-world complex and high-dimensional data sets, especially which are very typical to learn with traditional classifiers. (shrink)

In this paper a new technique of dual image watermarking is proposed for protection of ownership rights which utilizes salient properties of homomorphic transform (HT), discrete wavelet transform (DWT), singular value decomposition (SVD) and Arnold transform (AT). In embedding algorithm host image is splitted into reflectance and illumination components using HT, DWT is further applied to the reflectance component resulting in frequency subbands (HL and LH) which are transformed by SVD. Two image watermarks are selected for embedding process whereas security (...) of proposed algorithm is strengthen by performing scrambling of second watermark through AT. Both watermarks are transformed with DWT and SVD. Singular values (SVs) of both transformed watermark are embedded into SVs of host image. Simulation results clearly signifies for high robustness and imperceptibility of proposed algorithm as it is examined under various attacks. Superiority of proposed technique is illustrated by comparing it with other reported methods. (shrink)

Emotional design is an important development trend of interaction design. Emotional design in products plays a key role in enhancing user experience and inducing user emotional resonance. In recent years, based on the user's emotional experience, the design concept of strengthening product emotional design has become a new direction for most designers to improve their design thinking. In the emotional interaction design, the machine needs to capture the user's key information in real time, recognize the user's emotional state, and use (...) a variety of clues to finally determine the appropriate user model. Based on this background, this research uses a deep learning mechanism for more accurate and effective emotion recognition, thereby optimizing the design of the interactive system and improving the user experience. First of all, this research discusses how to use user characteristics such as speech, facial expression, video, heartbeat, etc., to make machines more accurately recognize human emotions. Through the analysis of various characteristics, the speech is selected as the experimental material. Second, a speech-based emotion recognition method is proposed. The mel-Frequency cepstral coefficient of the speech signal is used as the input of the improved long and short-term memory network. To ensure the integrity of the information and the accuracy of the output at the next moment, ILSTM makes peephole connections in the forget gate and input gate of LSTM, and adds the unit state as input data to the threshold layer. The emotional features obtained by ILSTM are input into the attention layer, and the self-attention mechanism is used to calculate the weight of each frame of speech signal. The speech features with higher weights are used to distinguish different emotions and complete the emotion recognition of the speech signal. Experiments on the EMO-DB and CASIA datasets verify the effectiveness of the model for emotion recognition. Finally, the feasibility of emotional interaction system design is discussed. (shrink)

Volume 20, Issue 7, July 2020, Page W12-W14.

Many climate scientists have made claims that may suggest that evidence used in tuning or calibrating a climate model cannot be used to evaluate the model. By contrast, the philosophers Katie Steele and Charlotte Werndl have argued that, at least within the context of Bayesian confirmation theory, tuning is simply an instance of hypothesis testing. In this paper I argue for a weak predictivism and in support of a nuanced reading of climate scientists’ concerns about tuning: there are cases, (...) model-tuning among them, in which predictive successes are more highly confirmatory of a model than accommodation of evidence. (shrink)

The aim of this article is to know the role of learning tasks within the pedagogical content knowledge of novel sports coaches in initial stages of sports training of children/young people and their impact on their daily work. Participants are two coaches in their first or second working year. A mixed methodology was used by means of polar coordinates analysis. The results agree with previous studies that established that PCK of novel coaches presents deficits in task selection and (...) modification, motivation is the key factor determining tasks selection process, and they do not know how much time they should dedicate to each task. Even so, better development was found in the PCK of the coaches. (shrink)

With the development of artificial intelligence, it is imperative to combine design methods with new technologies. From the perspective of the personalized design of derived images of art paintings, this study analyzes the new user demand generated by the current situation and background of personalized design, puts forward a new method of derivative design based on AI emotion analysis, verifies the feasibility of the new method by constructing a personalized design system of derived images of art paintings driven by facial (...) emotion features, and explores the method of combining AI emotion recognition, emotion analysis, and personalized design. This study provides new ideas for the design of art derivatives for the future with massive personalized demand. Thinking and practicing from the perspective of the development of new technology will promote the change of design paradigms in the digital age. (shrink)

Whilst certain verbs may appear in both the intransitive inchoative and the transitive causative constructions (The ball rolled/The man rolled the ball), others may appear in only the former (The man laughed/*The joke laughed the man). Some accounts argue that children acquire these restrictions using only (or mainly) statistical learning mechanisms such as entrenchment and pre-emption. Others have argued that verb semantics are also important. To test these competing accounts, adults (Experiment 1) and children aged 5–6 and 9–10 (Experiment 2) (...) were taught novel verbs designed to be construed — on the basis of their semantics — as either intransitive-only or alternating. In support of the latter claim, participants' grammaticality judgments revealed that even the youngest group respected these semantic constraints. Frequency (entrenchment) effects were observed for familiar, but not novel, verbs (Experiment 1). We interpret these findings in the light of a new theoretical account designed to yield effects of both verb semantics and entrenchment/pre-emption. (shrink)

Unsolicited email campaigns remain as one of the biggest threats affecting millions of users per day. During the past years several techniques to detect unsolicited emails have been developed. This work provides means to validate the hypothesis that the identification of the email messages’ intention can be approached by sentiment analysis and personality recognition techniques. These techniques will provide new features that improve current spam classification techniques. We combine personality recognition and sentiment analysis techniques to analyse email content. We enrich (...) a publicly available dataset adding these features, first separately and after in combination, of each message to the dataset, creating new datasets. We apply several combinations of the best email spam classifiers and filters to each dataset in order to compare results. (shrink)

There has been a lively debate in the philosophy of science over _predictivism_: the thesis that successfully predicting a given body of data provides stronger evidence for a theory than merely accommodating the same body of data. I argue for a very strong version of the thesis using statistical results on the so-called “model selection” problem. This is the problem of finding the optimal model (family of hypotheses) given a body of data. The key idea that I will borrow from (...) the statistical literature is that the level of support a hypothesis, _H,_ receives from a body of data, _D,_ is inversely related to the number of adjustable parameters of the model from which _H_ was constructed. I will argue that when _D_ is not essential to the design of _H_ (i.e., when it is predicted), the model to which _H_ belongs has fewer adjustable parameters than when _D_ is essential to the design of _H_ (when it is accommodated)_._ This, I argue, provides us with an argument for a very strong version of predictivism. (shrink)

Predictivism asserts that where evidence E confirms theory T, E provides stronger support for T when E is predicted on the basis of T and then confirmed than when E is known before T's construction and 'used', in some sense, in the construction of T. Among the most interesting attempts to argue that predictivism is a true thesis (under certain conditions) is that of Patrick Maher (1988, 1990, 1993). The purpose of this paper is to investigate the nature (...) of predictivism using Maher's analysis as a starting point. I briefly summarize Maher's primary argument and expand upon it; I explore related issues pertaining to the causal structure of empirical domains and the logic of discovery. (shrink)

Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. Recently, research has focused on extracting semantic relations from word embeddings since they capture relatedness and similarity between words. However, using word embeddings alone poses problems for synonym extraction because it cannot determine whether the relation between words is synonymy or some other semantic relation. In this paper, we present a novel solution for this problem by proposing (...) the SynoExtractor pipeline, which can be used to filter similar word embeddings to retain synonyms based on specified linguistic rules. Our experiments were conducted using KSUCCA and Gigaword embeddings and trained with CBOW and SG models. We evaluated automatically extracted synonyms by comparing them with Alma’any Arabic synonym thesauri. We also arranged for a manual evaluation by two Arabic linguists. The results of experiments we conducted show that using the SynoExtractor pipeline enhances the precision of synonym extraction compared to using the cosine similarity measure alone. SynoExtractor obtained a 0.605 mean average precision for the King Saud University Corpus of Classical Arabic with 21% improvement over the baseline and a 0.748 MAP for the Gigaword corpus with 25% improvement. SynoExtractor outperformed the Sketch Engine thesaurus for synonym extraction by 32% in terms of MAP. Our work shows promising results for synonym extraction suggesting that our method can also be used with other languages. (shrink)

An enduring question in the philosophy of science is the question of whether a scientific theory deserves more credit for its successful predictions than it does for accommodating data that was already known when the theory was developed. In The Paradox of Predictivism, Eric Barnes argues that the successful prediction of evidence testifies to the general credibility of the predictor in a way that evidence does not when the evidence is used in the process of endorsing the theory. He (...) illustrates his argument with an important episode from nineteenth-century chemistry, Mendeleev's Periodic Law and its successful predictions of the existence of various elements. The consequences of this account of predictivism for the realist/anti-realist debate are considerable, and strengthen the status of the 'no miracle' argument for scientific realism. Barnes's important and original contribution to the debate will interest a wide range of readers in philosophy of science. (shrink)

With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis with spatial analysis approach. The proposed model has been verified by (...) using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency. (shrink)

In the case of magnetic resonance imaging (MRI) imaging, image processing is crucial. In the medical industry, MRI images are commonly used to analyze and diagnose tumor growth in the body. A number of successful brain tumor identification and classification procedures have been developed by various experts. Existing approaches face a number of obstacles, including detection time, accuracy, and tumor size. Early detection of brain tumors improves options for treatment and patient survival rates. Manually segmenting brain tumors from a significant (...) number of MRI data for brain tumor diagnosis is a tough and time-consuming task. Automatic image segmentation of brain tumors is required. The objective of this study is to evaluate the degree of accuracy and simplify the medical picture segmentation procedure used to identify the type of brain tumor from MRI results. Additionally, this work suggests a novel method for identifying brain malignancies utilizing the Bagging Ensemble with K-Nearest Neighbor (BKNN) in order to raise the KNN’s accuracy and quality rate. For image segmentation, a U-Net architecture is utilized first, followed by a bagging-based k-NN prediction algorithm for classification. The goal of employing U-Net is to improve the accuracy and uniformity of parameter distribution in the layers. Each decision tree is fitted on a little different training dataset during classification, and the bagged decision trees are effective since each tree has minor differences and generates slightly different skilled predictions. The overall classification accuracy was up to 97.7 percent, confirming the efficiency of the suggested strategy for distinguishing normal and pathological tissues from brain MR images; this is greater than the methods that are already in use. (shrink)

Strong predictivism, the idea that novel predictions per se confirm theories more than accommodations, is based on a “no miracle” argument from novel predictions to the truth of theories (NMAT). Eric Barnes rejects both: he reconstructs the NMAT as seeking an explanation for the entailment relation between a theory and its novel consequences, and argues that it involves a fallacious application of Occam’s razor. However, he accepts a no miracle argument for the truth of background beliefs (...) (NMABB): scientists endorsed a successful theory because they were guided by largely true background beliefs. This in turn raises the probability that the theory is true; so Barnes embraces a form of weak predictivism, according to which predictions are only indirectly relevant to confirmation. To Barnes I reply that we should also explain how the successful theory was constructed, not just endorsed; background beliefs are not enough to explain success, scientific method must also be considered; Barnes can account for some measure of confirmation of our theories, but not for the practical certainty conferred to them by some astonishing predictions; true background beliefs and reliability by themselves cannot explain novel success, the truth of theories is also required. Hence, the NMAT is sound, and strong predictivism is right. In fact, Barnes misinterprets the NMAT, which does not involve Occam’s razor, takes as explanandum the building of a theory which turned out to predict surprising facts, and successfully concludes that the theory is true. This accounts for the practically certain confirmation of our most successful theories, in accordance with strong predictivism. (shrink)

Angle is an important concept in geometry. Young children have difficulty separating angle size from other dimensions such as the length of angle sides, perhaps due to whole-object bias in word learning. The present study used the pre-test–training–post-test design to investigate the effectiveness of two ways of separating angle from angle size in 3–6-year-old Chinese preschoolers. A total of 228 children were given a pre-test and 219 of them failed the crucial test. 168 of the 219 children were present at (...) school during the training phase and were randomly assigned to three groups: the “toma” group, which received training to call the whole angle figure as “toma” and angle size as angle size; the “angle/angle size” group, which received the training of separating “angle” from “angle size”; and the control group, which used “angle size” alone to represent both the overall angle figure and angle size. Results showed that the “toma” group improved significantly more than the other two groups, the latter of which did not differ from each other. These results suggest that it is insufficient to have two separate words/phrases for children to learn to differentiate angle from angle size, perhaps due to their shared usage of the word angle. Instead, the use of a novel term is necessary and sufficient to improve learning. Implications for preschool education are discussed. (shrink)

While many philosophers of science have accorded special evidential significance to tests whose results are "novel facts", there continues to be disagreement over both the definition of novelty and why it should matter. The view of novelty favored by Giere, Lakatos, Worrall and many others is that of use-novelty: An accordance between evidence e and hypothesis h provides a genuine test of h only if e is not used in h's construction. I argue that what lies behind the intuition (...) that novelty matters is the deeper intuition that severe tests matter. I set out a criterion of severity akin to the notion of a test's power in Neyman-Pearson statistics. I argue that tests which are use-novel may fail to be severe, and tests that are severe may fail to be use-novel. I discuss the 1919 eclipse data as a severe test of Einstein's law of gravity. (shrink)

Aging has become a serious social problem in China. Traditional informal long-term care is hard to sustain because of the reduction in family size and elders’ children migration to big cities. The institution offering services for the disabled elders has been a tendency. There exists a strange phenomenon: some nursing homes are difficult to enter for most disabled elders, while the other ones must search for elders to maintain operation. Therefore, for the evaluation of nursing homes, two problems should be (...) considered: selecting suitable nursing homes for disabled elders; obtaining the key factors influencing the selection of elders and helping nursing homes improve their services based on the key factors. First, we propose a new DEMATEL method for PLTSs to solve the second problem. Then, we present a novel PROMETHEE method to rank the alternatives and make a sensitivity analysis for criteria. Finally, we illustrate our proposed methods to an evaluation problem in Zhenjiang City by a case study. Based on the case study, we can obtain that our proposed methods are effective and practicable. (shrink)

Comprehensive analysis of proteins to evaluate their genetic diversity, study their differences, and respond to the tensions is the main subject of an interdisciplinary field of study called proteomics. The main objective of the proteomics is to detect and quantify proteins and study their post-translational modifications and interactions using protein chemistry, bioinformatics, and biology. Any disturbance in proteins interactive network can act as a source for biological disorders and various diseases such as Alzheimer and cancer. Most current computational methods for (...) discovering protein complexes are usually based on specific topological characteristics of protein-protein networks. To identify the protein complexes, in this paper, we, first, present a new encoding method to represent solutions; we then propose a new clustering algorithm based on the genetic algorithm, named PPI-GA, employing a new multiobjective quality function. The proposed algorithm is evaluated on two gold standard and real-world datasets. The result achieved demonstrates that the proposed algorithm can detect important protein complexes, and it provides more accurate results compared with state-of-the-art protein complex identification algorithms. (shrink)

Since 2015, two influential American authors and military consultants have sought to leverage imaginative literature for the cause of national security. On the basis of concepts such as useful fiction and FICINT, a shorthand for fictional intelligence, they have sought to develop a new genre—the national security novel—which blends nonfictional research and predictive threat scenarios with the creative inventions and emotional appeal of fiction. In this article, I trace how the national security novel developed through a process of (...) securitization, which has gradually merged the realm of literature with that of policy and military strategy, and I assess the genre’s current and future impact on national and global security. (shrink)

Over the previous three decades, the area of computer networks has progressed significantly, from traditional static networks to dynamically designed architecture. The primary purpose of software-defined networking is to create an open, programmable network. Conventional network devices, such as routers and switches, may make routing decisions and forward packets; however, SDN divides these components into the Data plane and the Control plane by splitting distinct features away. As a result, switches can only forward packets and cannot make routing decisions; the (...) controller makes routing decisions. OpenFlow is the communication interface between the switches and the controller. It is a protocol that allows the controller to identify the network packet’s path across the switches. This project uses the SDN environment to implement the firefly optimization algorithm to determine the shortest path between two nodes in a network. The firefly optimization algorithm was implemented using Ryu control. The results reveal that using the firefly optimization algorithm improves the selected short path between the source and destination. (shrink)

In the mining industry, smart surveying and exploration operations for the minerals are essential during mining missions. Usually, these missions are performed in remote areas that do not have a wireless communications infrastructure. This paper proposes to use the unmanned aerial vehicle as a relay communication node between the exploration team and the ground control station. UAV can act as a relay node to provide mobile, flexible, and reliable communication links in remote environments and complex topologies. In this work, the (...) pathloss models in millimeter-wave technology are considered because they provide massive data rates for line of sight scenarios. The optimization problem of identifying a 3D location and trajectory of the UAV relay node is formulated to maximize the total team members’ data rate. Because the problem is non-convex, the particle swarm optimization algorithm is used to solve it and determine an efficient location and trajectory of the UAV. (shrink)