In [20] Krajíček and Pudlák discovered connections between problems in computational complexity and the lengths of first-order proofs of finite consistency statements. Later Pudlák [25] studied more statements that connect provability with computational complexity and conjectured that they are true. All these conjectures are at least as strong as $\mathsf {P}\neq \mathsf {NP}$ [23–25].One of the problems concerning these conjectures is to find out how tightly they are connected with statements about computational complexity classes. Results of this kind had been (...) proved in [20, 22].In this paper, we generalize and strengthen these results. Another question that we address concerns the dependence between these conjectures. We construct two oracles that enable us to answer questions about relativized separations asked in [19, 25] (i.e., for the pairs of conjectures mentioned in the questions, we construct oracles such that one conjecture from the pair is true in the relativized world and the other is false and vice versa). We also show several new connections between the studied conjectures. In particular, we show that the relation between the finite reflection principle and proof systems for existentially quantified Boolean formulas is similar to the one for finite consistency statements and proof systems for non-quantified propositional tautologies. (shrink)

Speed is one of the major factors by which the traffic safety is affected. If the speed limit traffic signs on the road are recognised and displayed to a driver, this will be a motivation to keep the vehicle's speed within the permitted range. The purpose of this paper is to investigate Eigen-based traffic sign recognition which can aid in the development of Intelligent Speed Adaptation. This system is based on invoking the PCA technique to detect the unknown speed limit (...) traffic sign and computes its best effective Eigen vectors. The traffic sign is then recognized and classified by using the shortest Euclidean distance to the different speed limit traffic sign classes. The system was trained using 24 037 images which were collected in different light conditions. To check the robustness of this system, it was tested against 1429 images and it was found that the accuracy of recognition was 97.5% which indicates clearly the high robustness targeted by this system. (shrink)

. NormalBoost is a new boosting algorithm which is capable of classifying a multi-dimensional binary class dataset. It adaptively combines several weak classifiers to form a strong classifier. Unlike many boosting algorithms which have high computation and memory complexities, NormalBoost is capable of classification with low complexity. The purpose of this paper is to present NormalBoost as a framework which establishes a platform to solve classification problems. The approach was tested with a dataset which was extracted automatically from real-world traffic (...) sign images. The dataset contains both images of traffic sign borders and speed limit pictograms. This framework involves the computation of Haar-like features of these images and then employs the NormalBoost classifier to classify these traffic signs. The total number of images which were classified was 6500 binary images. A -fold validation was invoked to check the validity of the classification which resulted in a classification rate of 98.4% and 98.9% being achieved for these two databases. This framework is distinguished by its invariance to in-plane rotation of the images under consideration. Experiments show that the classification rate remains almost constant when traffic sign images with different angles of rotations were tested. (shrink)

. This paper presents a new approach to segment low quality fingerprint images which are collected by low quality fingerprint readers. Images collected using such readers are easy to collect but difficult to segment. The proposed approach is based on combining global and local processing to achieve segmentation of fingerprint images. On the global level, the fingerprint is located and extracted from the rest of the image by using a global thresholding followed by dilation and edge detection of the largest (...) object in the image. On the local level, fingerprint's foreground and its border image are treated using different fuzzy rules. These rules are based on the mean and variance of the block under consideration. The approach is implemented in three stages: pre-processing, segmentation, and post-processing. Segmentation of 100 images was performed and compared with manual examinations by human experts. The experiments showed that 96% of images under test are correctly segmented. The results from the quality of segmentation test revealed that the average error in block segmentation was 2.84% and the false positive and false negatives were approximately 1.4%. This indicates the high robustness of the proposed approach. (shrink)

This survey was conducted in 2017 to investigate factors influencing social risk perception of biotechnologists and plant breeders in training toward GM food based on a conceptual model. A random sample of 210 biotechnologists and plant breeders in training was studied. Confirmatory factor analysis and the reliability tests have been used to verify the uni-dimensionality of the measurement scale, SEM also was carried out to determine the most parsimonious models with the best fit for social risk perception of GM foods (...) and path analysis was conducted to understand the exogenous variables introduced in the research model. The findings revealed that the engineers in training had moderate social risk perception regarding GM foods. Moreover, the results of structural equation modeling showed the capability of the model in predicting the social risk perceptions of engineers in training. The psychological attributes of risks, social benefit perception, attitude toward using technology, level of religiosity, and moral and ethical beliefs emerged as the most powerful predictors of the social risk perception. The social benefit perception and attitude toward using technology also mediated the effects of psychological attributes of risks, level of religiosity, and moral and ethical beliefs. The social benefit perception also had an indirect influence on the engineers in training’s social risk perception of GM foods. Finally, we recommend the application of the model developed by this study for better understanding of social risk perception of stakeholders to have a more informed view of the development and promotion of GM foods. (shrink)

While there has been a number of consumers’ studies looking at factors that influence individuals’ attitudes and behavior toward GM foods, few studies have considered agricultural professionals’ intentions in this regard. This study illuminates agricultural professionals’ insights toward GM foods in Southwest Iran. A random sample of 262 respondents was studied. The results indicated that the majority of the respondents had little knowledge about GM foods. They perceived few benefits or risks of GM foods. Their perceived benefits and trust in (...) individuals and institutions had positive impacts on the behavioral intentions of the agricultural professionals. The results also revealed that the low knowledge level of the respondents had a negative impact on the behavioral intentions toward GM foods. This state of affairs is problematic, either GM foods have serious problems or the knowledge conveyed to the Iranian agricultural experts is inappropriate. We recommend a well defined communication strategy to provide information in such a way that allows individuals to feel adequately informed about GM foods. Furthermore, the development of trust and knowledge regarding GM foods can be greater when risk analysis frameworks are transparent, risk assessment methodologies are objective, all stakeholders are engaged in the risk management process, and risk communication focuses on consumers. (shrink)

One of the mathematical programming techniques is data envelopment analysis, which is used for evaluating the efficiency of a set of similar decision-making units. Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights. All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to (...) each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a numerical example. (shrink)

We give a counterexample to the claim that every provably total function of Basic Arithmetic is a polynomially bounded primitive recursive function.

ABSTRACT As a culture-specific phenomenon, academic dishonesty remains an under-researched domain. The purpose of this study was to voice teachers’ perceptions of: the influential factors contributing to AD, the consequences of AD for the quality of teacher–student relationships, and the specific strategies for regulating TSR. Using a qualitative phenomenological design, we attempted to present a detailed description of teachers’ lived experiences regarding the above aims. The participants were English language and Mathematics teachers with different personal and professional characteristics working in (...) public high schools of Iran. Data was collected through intensive semi-structured interviewing and analyzed by a five-step approach applied to phenomenology in psychological research. Data analysis revealed three general themes regarding teachers’ perceptions with several components. We found that the lack of attention and intrinsic motivation were the prominent perceived factors with consequences for TSR. Also, personal talk and active supervision were the common techniques that teachers utilized with students who commit AD to manage and control the TSR quality. The results were discussed with reference to teachers’ academic discipline, gender, and teaching experience. (shrink)

The outbreak of the COVID-19 pandemic has resulted in many emotional consequences for teachers, including feelings of isolation, loneliness, and hopelessness. However, evidence on the prevalence of hopelessness and the associated factors in teachers during the pandemic is limited. The purpose of this research was to examine the prevalence of hopelessness in public school teachers and identify risk factors associated with it. A sample of 168 teachers aged 25–49 years participated in the study by completing the Socio-Demographic Questionnaire, the Beck (...) Hopelessness Scale, and the Multi-Dimensional Scale of Perceived Social Support. The results revealed a moderate level of experienced hopelessness in teachers. Hopelessness prevalence was also significantly different across teacher gender, age groups, socioeconomic status, educational level, professional experience, and perceived social support. The results of a logistic regression analysis confirmed the effects of these demographic and occupational attributes on hopelessness by explaining ~71% of the variance in hopelessness feelings. Higher odds ratios were associated with age, socioeconomic status, and perceived social support, signifying the prominence of these factors in predicting hopelessness. The study contributes to identifying and screening teachers at risk of hopelessness in public schools and recommends promoting collegial/superior support as well as a positive school climate as the protective factors against hopelessness. (shrink)

This paper presents a new boosting algorithm called NormalBoost which is capable of classifying a multi-dimensional binary class dataset. It adaptively combines several weak classifiers to form a strong classifier. Unlike many boosting algorithms which have high computation and memory complexities, NormalBoost is capable of classification with low complexity. Since NormalBoost assumes the dataset to be continuous, it is also noise resistant because it only deals with the means and standard deviations of each dimension. Experiments conducted to evaluate its performance (...) shows that NormalBoost performs almost the same as AdaBoost in the classification rate. However, NormalBoost performs 189 times faster than AdaBoost and employs a very little amount of memory when a dataset of 2 million samples with 50 dimensions is invoked. (shrink)

BackgroundResearch misconduct is a global concern in biomedical science. There are no comprehensive data regarding the perception and situation of scientific misconduct among the Iranian medical faculty members. We conducted a nationwide survey to assess the research misconduct among the medical faculty members in Iran.MethodsWe used the Persian version of the research misconduct questionnaire on the Google Forms platform. We sent the survey link to a systematic random sample of medical faculty members in Iran. Descriptive analyses were performed on the (...) individual items of the PRMQ, with frequencies and percentages for categorical and Likert-type response items, and means and standard deviation for continuous variables. Chi-square analysis was conducted to test hypotheses examining differences in the frequency of responses related to factors influencing misconduct. We also defined four tenure categories based on the working years of the participants as tenured faculty members. All the analyses were performed using R 3.6.0.ResultsThe response rate was 13.8%. Nearly 70% of the respondents agreed that their publication output would be of higher quality if there were no publication pressure. Approximately three-quarters of the respondents had been aware of some instances of research misconduct during the previous year according to their understanding of misconduct. Among the participants, 18.5% perceived the effectiveness of their associated organisation’s rules for reducing research misconduct to be high or very high. Pressure for tenure was identified as the item most frequently perceived with a strong behavioural influence on engaging in research misconduct.ConclusionsThis study confirms that research misconduct needs to be actively addressed among the medical faculty members. Making policies with a focus on boosting awareness regarding the occasions of scientific misconduct and its management seems to be indispensable in the future in Iran. (shrink)

Background: Lower limb spasticity after stroke is common that can affect the balance, increase the risk of falling, and reduces the quality of life.Objective: First, evaluate the effects of spasticity severity of ankle plantar flexors on balance of patients after stroke. Second, to determine the relationship between the spasticity severity with ankle proprioception, passive ankle dorsiflexion range of motion, and balance confidence.Methods: Twenty-eight patients with stroke based on the Modified Modified Ashworth Scale were divided into two groups: High Spasticity Group (...) or a Low Spasticity Group. The MMAS scores, Activities-Specific Balance Confidence Questionnaire, postural sway of both affected and non-affected limbs under the eyes open and eyes closed conditions, timed up and go test, passive ankle dorsiflexion ROM, and ankle joint proprioception were measured.Results: The ankle joint proprioception was significantly better in the LSG compared to the HSG. No significant differences were found between the LSG and HSG on all other outcome measures. There were no significant relationships between the spasticity severity and passive ankle dorsiflexion ROM, and balance confidence.Conclusion: The severity of ankle plantar flexor spasticity had no effects on balance of patients with stroke. However, the ankle joint proprioception was better in patients with low spasticity. Our findings suggest that the balance is affected regardless of the severity of the ankle plantar flexor spasticity in this group of participants with stroke. (shrink)

Product acceptance determination using similarity measure index by neutrosophic statistics / Muhammad Aslam and Rehan Ahmed Khan Sherwani -- New concepts of strongly edge irregular interval-valued neutrosophic graphs / A.A.Talebi, Hossein Rashmanlou and Masoomeh Ghasemi -- The link between neutrosophy and learning : through the related concepts of representation and compression / Philippe Schweizer -- Neutrosophic soft cubic M-subalgebras of B-algebras / Mohsin Khalid, Neha Andaleeb Khalid and Hasan Khalid -- Alpha, beta and gamma product of neutrosophic graphs / (...) Nasir Shah, Said Broumi, Abdul Raheem and Tahir Imran -- Neutrosophic cubic normal ideal and neutrosophic cubic closed normal ideal of PS-algebra / Mohsin Khalid, Hasan khalid and Neha Andaleeb Khalid -- Neutrosophic multisets : an overview / Vakkas Uluçay -- Neutrosophy as a model for knowledge : the influence of representative models on thinking / Philippe Schweizer -- When neutrosophic theory meets three-way decisions / Rui Ren, Chao Zhang and Deyu Li -- Neutrosophic economic order quantity model with more than one price breaks / R. Surya, M. Mullai and G. Madhan Kumar -- General non-square systems of linear equations in single-valued triangular neutrosophic number environment / S.A. Edalatpanah -- Hesitant neutrosophic soft set relations / Abhijit Saha -- Computer application of neutrosophic set operations / S. Saranya, M. Vigneshwaran, Said Broumi -- Triangular bipolar neutrosophic based transportation problem / Avishek Chakraborty -- Studying neutrosophic variables / Rafif Alhabib and Ahmad Salama -- Decision making for logistics center location selection in trapezoidal neutrosophic environment / Kalyan Mondal and Surapati Pramanik -- Weighted similarity measure and decision making model for clinical application of single valued neutrosophic set / R.Binu and P. Isaac -- Rough neutrosophic set : an overview / Surapati Pramanik -- Some new concepts on normalized SVTN-number and multiple criteria decision making / İrfan Deli and Emel Kırmızı Öztürk. (shrink)