Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will (...) be done with the support of intelligent system that can learn, change and adapt to the input document and make a cross-fast search for the content on the local repository and the online repository and link the content of the file with the matching content everywhere found. Furthermore, the supported document type that we will use is word, text and in some cases, the pdf files –where is the text can be extracting from them- and this made possible by using the DLL file from Word application that Microsoft provided on OS. The using of DLL will let us to not constrain on how to get the text from files; and will help us to apply the file on our Delphi project and walk throw our methodology and read the file word by word to grantee the best working scenarios for the calculation. In the result, this process will help in the uprising the documents quality and enhance the writer experience related to his work and will save the copyrights for the official writer of the documents by providing a new alternative tool for plagiarism detection problem for easy and fast use to the concerned Institutions for free. (shrink)

Plagiarism is malpractice, the fabrication of others’ “ideas or work” published without the proper permission or citation of the original contributors. Plagiarism is detected through different software, i.e., Turnitin, before publishing any research data. The present survey study assesses whether academicians, researchers, and scholars around the world perceive this software as a creator or destroyer of new thoughts and ideas. A survey of this research data was conducted with academicians, researchers, and scholars around the globe. The number of (...) respondents is 1100, including 688 teaching professionals, 347 non-teaching, and 65 others. The present study finds that 82.7 per cent of research professionals mentioned that plagiarism could be appropriately citable. 76.7 per cent suggested that plagiarism can be completely avoidable, and 72.4 per cent has been proposed to be punishable. The study also described that plagiarism software is a good, efficient, and effective creator for new ideas. (shrink)

In China, plagiarism among undergraduate students has been a protuberant issue preventing the robust development of tertiary education. The purpose of this Interpretative Phenomenological Analysis (IPA) research was to acquire a profound understanding of the essence of the phenomenon through the process of students’ research writing at Shaoyang University (SYU), a southern Chinese University. Employing a step-wise combination of purposive and random sampling techniques, 11 participants were selected to partake in the study’s online, face-to-face, and one-on-one semi-structured interviews. On (...) completion of data analysis, seven themes emerged: poor literacy about plagiarism; few learning experiences related to plagiarism; disapproval of plagiarism with different tolerance levels; difficulties encountered during academic writing; sophistication in detouring the plagiarism detecting tool; reasons for committing plagiarism; and under-evaluation of disciplinary study. Based upon the rich findings, the study proposed a preliminary holistic solution to mitigate plagiarism, with school administration, policy makers, instructors, and students performing and abiding to their respective roles, and with the literacy education related to plagiarism at the center. (shrink)

This article attempts to comprehend the current issues and hurdles that Indian colleges affiliated with Tamil Nadu State Universities encounter when trying to subscribe to a software that detects plagiarism. The study’s goals are to determine whether colleges employ anti-plagiarism software, whether they ensure that their student-given assignments are free of copyright infringement, whether tutors teach about academic misconduct, and what people seem to think of anti-plagiarism software. We surveyed for this study and distributed the questionnaires among (...) college administrators, principals, and librarians. The study respondents are 15.9 per cent principals, 64.2 per cent library professionals, and 19.9 per cent college administrators. The survey study report shows that 70.9 per cent of the majority of the colleges did not subscribe. 41.7 per cent gave the reason it is too expensive, and 30.5 per cent of respondents thought that for their college, it is unnecessary to subscribe. However, nobody has confirmed whether or not all colleges possess access to plagiarism detection software. Thus, according to this investigation, further Indian states must be involved in this research to understand the specific context fully. This report advises the UGC to enforce the requirement that colleges have plagiarism detection software; they either provide colleges additional money to subscribe to such software, or the university must grant free access to the affiliated colleges. (shrink)

Academic integrity is an essential pillar of any educational system. It is defined as acting in a manner consistent with the values and accepted standards of ethical practices in teaching, learning, and scholarship (Fishman, 2015). Contract cheating, or ghostwriting, is currently one of the most severe violations of academic integrity. It involves students engaging a third party, usually an online essay writing service, to complete their academic works on their behalf (Draper et al., 2021). Some of these services offer pre-written (...) essays, whereas others offer bespoke custom-written essays. According to the academic literature, the advent of the internet and digital technologies underlay this rapid deterioration of academic integrity (Ison, 2020; Lancaster & Clarke, 2014). Different learning environments, such as face-to-face (i.e., a learning environment involving the physical presence of both instructor and students) and online web-based (i.e., teaching mode that takes place partially or entirely over the internet), have been shown to affect academic integrity in different ways (Eshet et al., 2021). While contract cheating is common in both conventional face-to-face (F2F) and online settings, it is more likely to take place in the latter (Lancaster & Clarke, 2014; Slade et al., 2018). There are several possible explanations for why online students engage in contract cheating more often than F2F students. In particular, this includes the problem issue of psychological distance, which adversely affects interpersonal relationships; and the problem issue of moral distancing, because the internet can obscure the line between academically honest and dishonest behavior (Sharma & Maleyeff, 2003). These issues were further exacerbated by the sudden shift from F2F to emergency remote teaching (ERT) in response to the COVID-19 pandemic (Ahsan et al., 2021; Bjelobaba, 2021). Indeed, contract cheating had become a significant COVID-19 side effect for higher education institutions. In contrast to the well-planned F2F or online learning courses, ERTbased courses are not originally designed to be delivered virtually (Fatonia et al., 2020). The chaos brought by the abrupt campus closure and related unexpected transition to ERT provided both the opportunity and the incentive for contract cheating (Hill et al., 2021). Through social media, students have very quickly become fully aware of the possibilities of a wide variety of options to carry out Plagiarism (Bautista et al., 2022). There has been an increase in ways to try to bypass text-matching or text-reuse (i.e., plagiarism) detection systems, for example using micro-spaces, white ink, punctuation, and typos (Abdelhamid et al., 2022). Even though ghostwriters, especially commercial ones, claim their essays are original and therefore cannot be detected using text-matching software, third-party assignments may still contain recycled text (Aitken et al., 2017; Newton & Lang, 2015). Text matching detection software could use these breaches to identify outsourced academic work (Lancaster & Clarke, 2016; Wang & Xu, 2021). This study compared about four thousand term papers written in languages other than Hebrew. (shrink)

As a retired professor, I join in the growing concerns among educators, and others, about plagiarism, especially now that AI tools like ChatGPT are so readily available. However, I feel more caution is needed, regarding temptations to rely on supposed automatic detection tools, like Turnitin, to solve the problems. Students can be unfairly accused if such tools are used unreflectingly. The Toronto Star's online version of this published Op Ed is available at the link shown below. The version (...) attached here is a pre-print, which also includes annotations for my references, which are not displayed in the published version. (shrink)

Many philosophers have argued that large language models (LLMs) subvert the traditional undergraduate philosophy paper. For the enthusiastic, LLMs merely subvert the traditional idea that students ought to write philosophy papers “entirely on their own.” For the more pessimistic, LLMs merely facilitate plagiarism. We believe that these controversies neglect a more basic crisis. We argue that, because one can, with minimal philosophical effort, use LLMs to produce outputs that at least “look like” good papers, many students will complete paper (...) assignments in a way that fails to develop their philosophical abilities. We argue that this problem exists even if students can produce better papers with AI and even if instructors can detect AI-generated content with decent reliability. But LLMs also create a pedagogical opportunity. We propose that instructors shift the emphasis of their assignments from philosophy papers to “LLM dialogues”: philosophical conversations between the student and an LLM. We describe our experience with using these types of assignments over the past several semesters. We argue that, far from undermining quality philosophical instruction, LLMs allow us to teach philosophy more effectively than was possible before. (shrink)

Many philosophers have argued that large language models (LLMs) subvert the traditional undergraduate philosophy paper. For the enthusiastic, LLMs merely subvert the traditional idea that students ought to write philosophy papers “entirely on their own.” For the more pessimistic, LLMs merely facilitate plagiarism. We believe that these controversies neglect a more basic crisis. We argue that, because one can, with minimal philosophical effort, use LLMs to produce outputs that at least “look like” good papers, many students will complete paper (...) assignments in a way that fails to develop their philosophical abilities. We argue that this problem exists even if students can produce better papers with AI and even if instructors can detect AI-generated content with decent reliability. But LLMs also create a pedagogical opportunity. We propose that instructors shift the emphasis of their assignments from philosophy papers to “LLM dialogues”: philosophical conversations between the student and an LLM. We describe our experience with using these types of assignments over the past several semesters. We argue that, far from undermining quality philosophical instruction, LLMs allow us to teach philosophy more effectively than was possible before. (shrink)

The Internet of Things (IoT) connects schemes, programs, data management, and operations, and as they continuously assist in the corporation, they may be a fresh entryway for cyber-attacks. Presently, illegal downloading and virus attacks pose significant threats to IoT security. These risks may acquire confidential material, causing reputational and financial harm. In this paper hybrid optimization mechanism and deep learning,a frame is used to detect the attack prevention in IoT. To develop a cybersecurity warning system in a huge data set, (...) the cybersecurity warning systems index system is first constructed, then the index factors are picked and measured, and finally, the situation evaluation is done.Numerous bio-inspired techniques were used to enhance the productivity of an IDS by lowering the data dimensionality and deleting unnecessary and noisy input. The Grey Wolf Optimization algorithm (GWO) is a developed bio-inspired algorithm that improves the efficacy of the IDS in detecting both regular and abnormal congestion in the network. The smart initialization step integrates the different pre-processing strategies to make sure that informative features are incorporated in the early development stages, has been improved. Researchers pick multi-source material in a big data environment for the identification and verification of index components and present a parallel reduction approach based on the classification significance matrix to decrease data underlying data characteristics. For the simulation of this situation, grey wolf optimization and whale optimization were combined to detect the attack prevention and the deep learning approach was presented. Utilizing system software plagiarism, the TensorFlow deep neural network is intended to classify stolen software. To reduce the noise from the signal and to zoom the significance of each word in the perspective of open-source plagiarism, the tokenization and weighting feature approaches are utilized. Malware specimens have been collected from the Mailing database for testing purposes. The experimental findings show that the suggested technique for measuring cyber security hazards in IoT has superior classification results to existing methods. Hence to detect the attack prevention in IoT process Whale with Grey wolf optimization (WGWO) and deep convolution network is used. (shrink)

A surge in post-publication activity related to editing, including by technical editors and copyeditors, is worthy of some discussion. One of these issues involves the issue of 'tortured phrases', which are bizarre terms and phrases in academic papers that replace standard English expressions or jargon. This phenomenon may reveal an attempt to avoid the detection of textual similarity or to masquerade plagiarism, and yet remain undetected by editors, peer reviewers and text editors. Potentially thousands of cases have already (...) been discovered and reported publicly on the post-publication platform PubPeer. In this opinion paper, 35 cases from ranked scholarly journals are presented, mainly the fields of materials, computer and engineering sciences. This collation serves to expand discussion about this integrity-related phenomenon and to increase educational awareness of the topic. (shrink)

As if 2020 were not a peculiar enough year, its fifth month has seen the relatively quiet publication of a preprint describing the most powerful Natural Language Processing (NLP) system to date, GPT-3 (Generative Pre-trained Transformer-3), by Silicon Valley research firm OpenAI. Though the software implementation of GPT-3 is still in its initial Beta release phase, and its full capabilities are still unknown as of the time of this writing, it has been shown that this Artificial Intelligence can comprehend prompts (...) in natural language, on virtually any topic, and generate relevant, original text content that is indistinguishable from human writing. Moreover, access to these capabilities, in a limited yet worrisome enough extent, is available to the general public as of the time of this writing. This paper presents select examples of original content generated by the author using GPT-3. These examples illustrate some of the capabilities of GPT-3 in comprehending prompts in natural language and generating convincing content in response. We use these examples to raise specific, fundamental questions pertaining to the intellectual property of this content and the potential use of GPT-3 to facilitate plagiarism. Our goal is to instigate not just a sense of urgency, but of a present tardiness on the part of the academic community in addressing these questions. (shrink)

Today, the Internet is a rich source of study materials, and Google Scholar offers free access to a large number of scientific articles. There are excellent research publications available in many more databases. Students have the option of easily copying the material. Reusing, paraphrasing, patchwriting, and ghostwriting without citing the original documents are plagiarism. Plagiarism is increasing in academics, particularly in research. This study aims to study the awareness of plagiarism and to analyze the reasons for (...) class='Hi'>plagiarism. The study samples are the student teachers in India. For this study, we used a survey method, and the author prepared a questionnaire to collect data from the student teachers. Study respondents are the student teachers of the Regional Institute of Education Mysore; Purposive sampling was used to select samples. The total number of study respondents is 207. The findings of the study revealed that over 70 per cent of respondents mentioned reasons for plagiarism as lack of relevant literature studying, lack of preparation and time, difficulty checking every piece of work, do not know the manual citation style, lack of knowledge about bibliographic management software and also they stated that getting easily available materials on the internet is also a reason for plagiarism. The study recommends that teachers teach or conduct awareness programs on plagiarism, avoiding plagiarism, citation style, and software. (shrink)

This article diagnoses the problem of plagiarism in academic books and articles in the disciplines of philosophy and theology. It identifies three impediments to institutional reform. They are: (1) a misplaced desire to preserve personal and institutional reputations; (2) a failure to recognize that attribution in academic writing admits of degrees; and (3) a disproportionate emphasis on the socalled “intention to plagiarize.” A detailed case study provides an illustration of the need for institutional reform in the post-publication processes in (...) the disciplines of philosophy and theology. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

EAP course teaches how the program concerns and provides us with a valuable way of organizing our thinking about conceptual disciplinary within the particular community. The area of EAP is referred with genres. The process of writing academically requires creating a text where the writer takes it for granted the reader is about to recognize. To group texts together, writers utilize language in order to respond to recurring situations and this case is +represented with the term genre.

Issues on plagiarism among pre-service teachers (PSTs) have increased in modular and online learning. To confirm this, the study determined the PSTs’ level of awareness on plagiarism; their knowledge on referencing and citation; and the correlation between their level of awareness on plagiarism and knowledge on referencing and citation, with their academic performance. The study employed a descriptive-correlational research design participated by 235 PSTs randomly sampled through strata. The data were gathered through a web-based survey. Results showed (...) that the PSTs’ level of awareness of plagiarism was moderate, while the majority have fair knowledge in referencing and citation. Also, results showed a significant relationship among the level of awareness on plagiarism, knowledge on referencing and citation, and academic performance. It is recommended that institutions equip librarians and educators to teach PSTs about citation and referencing skills. Besides, the institution should make sure that a policy is implemented to pursue academic integrity. This policy must articulate the various types of plagiarism, plagiarism measurement, and fair and consistent disciplinary actions. (shrink)

Five aspects of visual change detection are reviewed. The first concerns the concept of change itself, in particular the ways it differs from the related notions of motion and difference. The second involves the various methodological approaches that have been developed to study change detection; it is shown that under a variety of conditions observers are often unable to see large changes directly in their field of view. Next, it is argued that this “change blindness” indicates that focused (...) attention is needed to detect change, and that this can help map out the nature of visual attention. The fourth aspect concerns how these results affect our understanding of visual perception—for example, the implication that a sparse, dynamic representation underlies much of our visual experience. Finally, a brief discussion is presented concerning the limits to our current understanding of change detection. (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s (...) prediction are more accurate than either alone, but inaccurate model predictions often decrease participants’ accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants’ performance while mostly not affecting the model’s performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance. -/- . (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...) technique to produce brain tumor detection and classification models using Magnetic Resonance Imaging (MRI) imaging for rapid and easy detection and identification of brain tumor. In this thesis, some ways and mechanisms will be reviewed to use deep learning techniques to produce a model for brain tumor detection. The goal is to find a good and effective way to detect brain tumor based on MRI to help the brain doctor in making decisions easily, accurately and rapidly. A recent report by the World Health Organization in February 2018 showed that the death rate from brain cancer or central nervous system (CNS) is the highest in the Asian continent. It is important to detect cancer early so that many of these lives can be saved. The model has been designed and implemented, including a dataset which consist of 10,000 images for brain tumor detection through the use of Deep learning algorithms based on neural networks. For testing, we have used our model, Inception, VGG16, MobileNet and ResNet models. The f-score accuracy we got for each model was as follows: Our model was 98.28, VGG16 was 99.86%, ResNet50 was 98.14%, MobileNet was 88,98%, and InceptionV3 was 99.88%. (shrink)

The aim of this paper is to raise two questions. The first question is: How is pessimism related to Buddhism (and vice versa)? The second question is: What relation does an immanent philosophy have to pessimism and Buddhism, if any? Using True Detective, an American television crime drama, as my point of departure, first I will outline some of the likenesses between Buddhism and pessimism. At the same time, I will show how the conduct of one of the main characters (...) in True Detective resembles the paths of Buddhism and pessimism, even though he is ethical in a strictly non-pessimistic and non-Buddhist fashion. Last, I will try to place these findings in perspective through the French philosopher Gilles Deleuze’s thoughts. Hereby, I hope to illustrate that joy, not suffering, is basic to human existence, and how human beings may overcome a spiritual pessimism. (shrink)

The aim of this paper is to raise two questions. The first question is: How is pessimism related to Buddhism (and vice versa)? The second question is: What relation does an immanent philosophy have to pessimism and Buddhism, if any? Using True Detective, an American television crime drama, as my point of departure, first I will outline some of the likenesses between Buddhism and pessimism. At the same time, I will show how the conduct of one of the main characters (...) in True Detective resembles the paths of Buddhism and pessimism, even though he is ethical in a strictly non-pessimistic and non-Buddhist fashion. Last, I will try to place these findings in perspective through the French philosopher Gilles Deleuze’s thoughts. Hereby, I hope to illustrate that joy, not suffering, is basic to human existence, and how human beings may overcome a spiritual pessimism. (shrink)

Introspection is a fundamental part of our mental lives. Nevertheless, its reliability and its underlying cognitive architecture have been widely disputed. Here, I propose a principled way to model introspection. By using time-tested principles from signal detection theory (SDT) and extrapolating them from perception to introspection, I offer a new framework for an introspective signal detection theory (iSDT). In SDT, the reliability of perceptual judgments is a function of the strength of an internal perceptual response (signal- to-noise ratio) (...) which is, to a large extent, driven by the intensity of the stimulus. In parallel to perception, iSDT models the reliability of introspective judgments as a function of the strength of an internal introspective response (signal-to-noise ratio) which is, to a large extent, driven by the intensity of conscious experiences. Thus, by modelling introspection after perception, iSDT can calibrate introspection’s reliability across a whole range of contexts. iSDT offers a novel, illuminating way of thinking about introspection and the cognitive processes that support it. (shrink)

The existence of big bang relic neutrinos—exact analogues of the big bang relic photons comprising the cosmic microwave background radiation—is a basic prediction of standard cosmology. The standard big bang theory predicts the existence of 1087 neutrinos per flavour in the visible universe. This is an enormous abundance unrivalled by any other known form of matter, falling second only to the cosmic microwave background (CMB) photon. Yet, unlike the CMB photon which boasts its first (serendipitous) detection in the 1960s (...) and which has since been observed and its properties measured to a high degree of accuracy in a series of airborne/satellite and ground based experiments, the relic neutrino continues to be elusive in the laboratory. The chief reason for this is of course the feebleness of the weak interaction. At present, the observational evidence for their existence rests entirely on cosmological measurements, such as the light elemental abundances, anisotropies in the cosmic microwave background, and the large-scale matter power spectrum. In this paper we argue that Direct Detection of relic neutrino background is indeed impossible by any means, because of two chief reasons: (a) there was no such thing of cosmic singularity, hence the hot big bang/primeval atom model was based on false premises (quantum birth assumption); (b) the neutrino existence itself is not unquestionable, in particular if we consider a realism view of vector potential, A, in classical electrodynamics. (shrink)

In this article I discuss a particular aspect of the Dutch reception of the ideas of René Descartes, namely the use of his Traité de l’homme by Henricus Regius. I analyze the use that Regius made of the theory of the movement of muscles, passions, hunger, and more generally of the neurophysiology expounded by Descartes in his book (not printed until 1662–1664). In my analysis, I reconstruct the internal evolution of Regius’s neurophysiology, I illustrate its sources beyond Descartes (i.e., Jean (...) Fernel and Santorio Santorio), and I show that he was certainly acquainted with some of its contents as early as 1641 (when he used it with the mediation of Descartes), before relying on it—as variously discussed in secondary literature—in his Fundamenta physices (1646), when he appropriated from it without Descartes’s authorization. (shrink)

In pedestrian detection, occlusions are typically treated as an unstructured source of noise and explicit models have lagged behind those for object appearance, which will result in degradation of detection performance. In this paper, a hierarchical co-occurrence model is proposed to enhance the semantic representation of a pedestrian. In our proposed hierarchical model, a latent SVM structure is employed to model the spatial co-occurrence relations among the parent–child pairs of nodes as hidden variables for handling the partial occlusions. (...) Moreover, the visibility statuses of the pedestrian can be generated by learning co-occurrence relations from the positive training data with large numbers of synthetically occluded instances. Finally, based on the proposed hierarchical co-occurrence model, a pedestrian detection algorithm is implemented to incorporate visibility statuses by means of a Random Forest ensemble. The experimental results on three public datasets demonstrate the log-average miss rate of the proposed algorithm has 5% improvement for pedestrians with partial occlusions compared with the state-of-the-arts. (shrink)

Despite the emphasis on dialogue and argumentation in educational settings, still not much is known about how best we can support learners in their interthinking, reasoning, and metadialogic understanding. The goal of this classroom intervention study is to explore the degree of students’ dialogicity and its possible increase during a learning programme implementing dialogic and argument-based teaching goals and principles. In particular, we focus on how students from 5 to 15 years old engage with each other's ideas, and whether/how this (...) engagement is influenced by lesson and classroom setting factors. The participants were 4208 students distributed in preprimary, primary, and secondary classrooms of five countries (UK, Portugal, Germany, Spain, and Cyprus). Findings suggest that there is a consistent increase with age for some high-dialogicity moves, and students behave more dialogically in whole-class discussions rather than small-group activities. (shrink)

Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game addictions (...) that range from (Musculoskeletal issues, Vision problems and Obesity). Moreover, this expert system provides information about the problem and tell us how we can solve it. SL5 Object expert system language was used to design and implement the expert system. (shrink)

This chapter as the whole book are a result of a Globethics conference in March 2018 at the Catholic University of East Africa (CUEA) in Kenya, focused on the integration of Ethics in Higher Education. The book captures the potential for sharing of knowledge, and triggering interdisciplinary collaboration and research across a wide variety of issues ranging from research practice, religion, entrepreneurship, leadership, fundraising and corruption. While some of the chapters focus on the understanding of ethics and its relationship with (...) the various other aspects of life, others concentrate on the methods and strategies of effectively teaching ethics. Our chapter is concerned by the ways research practices and the value of integrity might be at risk, in very limited situations. We have good hope that responsible answers and proportionate reason-based actions in confronting some of these risks - as with plagiarism - can protect the giving virtues necessary for dynamical and effective research processes, which are all ultimately built on the value of trust. (shrink)

A fundamental assumption of theories of decision-making is that we detect mismatches between intention and outcome, adjust our behavior in the face of error, and adapt to changing circumstances. Is this always the case? We investigated the relation between intention, choice, and introspection. Participants made choices between presented face pairs on the basis of attractiveness, while we covertly manipulated the relationship between choice and outcome that they experienced. Participants failed to notice conspicuous mismatches between their intended choice and the outcome (...) they were presented with, while nevertheless offering introspectively derived reasons for why they chose the way they did. We call this effect choice blindness. (shrink)

This paper presents three cases of research ethics violations in the social sciences and humanities that involved major educational institutions in Vietnam. The violations share two common points: the use of sophistry by the accused perpetrators and their sympathisers, and the relative ease with which they succeeded unpunished. The strategies the violators used to avoid punishment could be summarised as: (i) relying on people not paying enough attention when asked to do something relatively quickly, (ii) asking for the benefit of (...) the doubt, (iii) redefining the meaning of ethics, and (iv) defaming the whistleblowers and showing how fighting ethics violations is too costly, slow and, in the end, worthless. We offer suggestions to improve transparency: investment in translation and education about codes of conduct in Vietnam; investment in research ethics and integrity; the use of open online resources and platforms; and educating Vietnamese researchers about international standards. (shrink)

Academic misconduct is a prominent issue at postsecondary institutions. This issue includes the act of plagiarism, which has received considerable attention on campuses. There is a growing body of research examining why students engage in plagiarism, and what they know about plagiarism, but little of this research is guided by a theoretical framework. Although all students may be tempted to plagiarize, students in teacher education programs represent a unique population because they are concerned with developing their own (...) academic performance alongside the skills necessary to manage situations of academic misconduct as future teachers. Therefore, our first aim was to examine preservice teachers’ beliefs about plagiarism. Then, following the principles of Attribution Theory, our second aim was to investigate how beliefs of controllability related to acts of plagiarism impacted participants views on responsibility, emotions, help giving, and reporting. We used a within-person repeated measures design with three levels of controllability manipulated through hypothetical scenarios of plagiarism to collect data from 201 preservice teachers. Overall, preservice teachers had strong beliefs about plagiarism. Moreover, when scenarios included students who engaged in plagiarism that was controllable, participants were more likely to view the student as responsible, feel anger towards them, support punishment, and recommend reporting the student, than when the act of plagiarism was not seen as controllable. We provide recommendations for instructors and administrators for supporting students and highlight limitations and directions for future research. (shrink)

In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is “survey lung (...) cancer”. Model evaluation showed that the ANN model is able to detect the absence or presence of lung cancer with 96.67 % accuracy. (shrink)

Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential mistakes. We demon­strate the methodology by outlining the different types of mistakes that are found when the algorithms are applied to SNOMED-CT. On the basis of the results, we argue that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.

Background: This article addressed one of the issues of research ethics that is called the nature of plagiarism coupled with involvement of intention. By definition, plagiarism is the attribution of others’ works to one’s own. This may be done intentionally and/or unintentionally. Some researchers believe that intention is not involved in the nature of plagiarism and an author who forgets to make references to the used sources has committed plagiarism since this forgetfulness has led to the (...) attribution of others’ work to one’s own. In contrast, some experts call such a person a wrongdoer, not a plagiarist. Conclusion: By likening this problem to the issue of involvement of intention in telling a lie, the author separates two kinds of plagiarism: act-plagiarism and agent-plagiarism. The intention does not involve in the act-plagiarism (to be an act an instance of plagiarism), but it is involved in the agent-plagiarism (to call someone plagiarist). As a result, an author who forgets to make reference is not a plagiarist, but his/her act is an instance of plagiarism. Keywords: Intention, Plagiarism, Intentional Plagiarism, Unintentional Plagiarism. (shrink)

The study aimed to identify the effect of applying detection and prevention tools for career fraud in combating and preventing fraud and reducing its risks through an applied study on Palestinian Ministry of Health in Gaza Strip, Palestine. To achieve the objectives of the study, the researchers used the questionnaire as a main tool to collect data, and the descriptive and analytical approach to conducting the study. The study population consisted of (501) supervisory employees working at MOH in Gaza (...) Strip, Palestine. The researchers used the stratified random sample method and the multiple regression method to measure the effect. The study concluded a set of results, the most important of which is a positive evaluation among respondents about the levels of application of tools to detect and prevent job fraud within MOH, and the presence of a high interest in tools to prevent job fraud during the implementation of its various work. The study recommended the necessity for the Palestinian National Authority to develop and approve laws regulating health sector, so that those laws guarantee the prevention of conflicts of interest, especially for the category of doctors, by preventing job duplication of doctors working in the government sector. Also study recommended the need for MOH to adopt principles of health sector governance and begin immediately to implement them. This process to ensure transparency, disclosure and accountability in the business framework in a manner that realizes the effective protection of stakeholders and does not compromise or discriminate in the application of these principles, which ensures that all forms of job fraud are organized in an organized manner and within fixed legal frameworks. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this (...) end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

General Relativity defines gravity like the metric of a Lorentzian manifold. Einstein formulated spacetime as quality structural of gravity, i.e, circular definition between gravity and spacetime, also Einstein denoted "Space and time are modes by which we think, not conditions under which we live" and “We denote everything but the gravitational field as matter”, therefore, spacetime is nothing and gravity in first approximation an effect of coordinates, and definitely a geometric effect. The mathematical model generates quantitative predictions coincident in high (...) grade with observations without physical meaning. Philosophy intervened: in Substantivalism, spacetime exists in itself while in Relationalism as metrical relations. But, it does not know what spacetime. The outcomes of model have supported during a century, validity of the General Relativity, interpreted arbitrarily. Einstein formulated, from quadrupoles of energy, the formation of ripples in spacetime propagating as gravitational waves abandoned, in 1938, when he said that they do not exist. LIGO announced the first detection of gravitational waves from a pair of merging black holes. They truly are waves of quantum vacuum. (shrink)

Web page phishing is a type of phishing attack that targets websites. In a web page phishing attack, the attacker creates a fake website that looks like a legitimate website, such as a bank or credit card company website. The attacker then sends a fraudulent message to the victim, which contains a link to the fake website. When the victim clicks on the link, they are taken to the fake website and tricked into entering their personal information.Web page phishing attacks (...) are a serious threat to online security. They can be very effective, as they often look very convincing. To protect yourself from web page phishing attacks, you should be suspicious of any emails or messages that ask for your personal information. Do not click on links in emails or messages from unknown senders. If you are unsure whether a website is legitimate, do not enter your personal information. Therefore, in this study, we present a novel approach to detect whether a web page is phishing or legitimate using a neural network model. (shrink)

Political fact-checkers evaluate the truthfulness of politicians’ claims. This paper contributes to an emerging scholarly debate on whether fact-checkers treat political parties differently in a systematic manner depending on their ideology (bias). We first examine the available approaches to analyze bias and then present a new approach in two steps. First, we propose a logistic regression model to analyze the outcomes of fact-checks and calculate how likely each political party will obtain a truth score. We test our model with a (...) sample of fact-checks from Newtral, a major Spanish fact-checker. Our model would signal bias under two assumptions: a) all political parties are on average equally accurate in their statements; b) the verification method gives precise instructions and is implemented systematically. We investigate this second assumption with a series of interviews with Newtral fact-checkers. We show that standard verification protocols are so loosely implemented that fact-checks reflect a set of journalistic decisions, rather than a bias in the statistical sense. We call for a more rigorous definition of verification methods as a pre-requisite for an unbiased assessment of politician’s claims. (shrink)

This sentence G ↔ ¬(F ⊢ G) and its negation G ↔ ~(F ⊢ ¬G) are shown to meet the conventional definition of incompleteness: Incomplete(T) ↔ ∃φ ((T ⊬ φ) ∧ (T ⊬ ¬φ)). They meet conventional definition of incompleteness because neither the sentence nor its negation is provable in F (or any other formal system). -- .

Plagiarism, which Indiana University’s Writing Tutorial Service defines as "using others' ideas and words without clearly acknowledging the source of that information", is often described as a major problem. However, standard definitions such as this one suggest only limited solutions to the problem: acknowledging sources or forbidding reuse. Since all scholarship involves engaging with the ideas of others and academic writing tends to reuse certain expressions, these solutions – though important – are of limited utility. This paper examines a (...) type of plagiarism to which the standard solutions do not apply: the reuse of linguistic models without sufficient attention to the logic or thoughts the texts express. We present two cases of plagiarism, from which we can see that plagiarism shows a gap between the written texts and the thoughts of the author. In order to fill the gap, one needs to know how to integrate not only the texts borrowed from others into one’s writing but also the thoughts expressed by the texts. Thus a satisfactory solution to the plagiarism problem requires not only writing skills but also logical thinking skills. (shrink)

Freeman Dyson has questioned whether any conceivable experiment in the real universe can detect a single graviton. If not, is it meaningful to talk about gravitons as physical entities? We attempt to answer Dyson’s question and find it is possible concoct an idealized thought experiment capable of detecting one graviton; however, when anything remotely resembling realistic physics is taken into account, detection becomes impossible, indicating that Dyson’s conjecture is very likely true. We also point out several mistakes in the (...) literature dealing with graviton detection and production. (shrink)

When brief blank fields are placed between alternating displays of an original and a modified scene, a striking failure of perception is induced: the changes become extremely difficult to notice, even when they are large, presented repeatedly, and the observer expects them to occur (Rensink, O'Regan, & Clark, 1997). To determine the mechanisms behind this induced "change blindness", four experiments examine its dependence on initial preview and on the nature of the interruptions used. Results support the proposal that representations at (...) the early stages of visual processing are highly volatile, and that focused attention is needed to stabilize them sufficiently to support the perception of change. (shrink)

The mental risk poses a high threat to the individuals, especially overseas demographic, including expatriates in comparison to the general Arab demographic. Since Arab countries are renowned for their multicultural environment with half of the population of students and faculties being international, this paper focuses on a comprehensive analysis of mental health problems such as depression, stress, anxiety, isolation, and other unfortunate conditions. The dataset is developed from a web-based survey. The detailed exploratory data analysis is conducted on the dataset (...) collected from Arab countries to study an individual’s mental health and indicative help-seeking pointers based on their responses to specific pre-defined questions in a multicultural society. The proposed model validates the claims mathematically and uses different machine learning classifiers to identify individuals who are either currently or previously diagnosed with depression or demonstrate unintentional “save our souls” (SOS) behaviors for an early prediction to prevent risks of danger in life going forward. The accuracy is measured by comparing with the classifiers using several visualization tools. This analysis provides the claims and authentic sources for further research in the multicultural public medical sector and decision-making rules by the government. (shrink)

Research in the psychology of deception detection implies that Fricker, in making her case for reductionism in the epistemology of testimony, overestimates both the epistemic demerits of the antireductionist policy of trusting speakers blindly and the epistemic merits of the reductionist policy of monitoring speakers for trustworthiness: folk psychological prejudices to the contrary notwithstanding, it turns out that monitoring is on a par (in terms both of the reliability of the process and of the sensitivity of the beliefs that (...) it produces) with blind trust. The consequence is that while (a version of) Fricker’s argument for the necessity of a reduction succeeds, her argument for the availability of reductions fails. This does not, however, condemn us to endorse standard pessimistic reductionism, according to which there is no testimonial knowledge, for recent research concerning the methods used by subjects to discover deception in non-laboratory settings suggests that only a more moderate form of pessimism is in order. (shrink)