1,040 research outputs found

    Polynomial-Time Fence Insertion for Structured Programs

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    To enhance performance, common processors feature relaxed memory models that reorder instructions. However, the correctness of concurrent programs is often dependent on the preservation of the program order of certain instructions. Thus, the instruction set architectures offer memory fences. Using fences is a subtle task with performance and correctness implications: using too few can compromise correctness and using too many can hinder performance. Thus, fence insertion algorithms that given the required program orders can automatically find the optimum fencing can enhance the ease of programming, reliability, and performance of concurrent programs. In this paper, we consider the class of programs with structured branch and loop statements and present a greedy and polynomial-time optimum fence insertion algorithm. The algorithm incrementally reduces fence insertion for a control-flow graph to fence insertion for a set of paths. In addition, we show that the minimum fence insertion problem with multiple types of fence instructions is NP-hard even for straight-line programs

    Enhanced Breast Cancer Classification with Automatic Thresholding Using Support Vector Machine and Harris Corner Detection

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    Image classification and extracting the characteristics of a tumor are the powerful tools in medical science. In case of breast cancer medical treatment, the breast cancer classification methods can be used to classify input images as benign and malignant classes for better diagnoses and earlier detection with breast tumors. However, classification process can be challenging because of the existence of noise in the images, and complicated structures of the image. Manual classification of the images is timeconsuming, and need to be done only by medical experts. Hence using an automated medical image classification tool is useful and necessary. In addition, having a better training data set directly affect the quality of classification process. In this paper, a method is proposed based on supervised learning and automatic thresholding for both generating better training data set, and more accurate classification of the mammogram images into benign/malignant classes. The procedure consists of pre-processing, removing noise, elimination of unwanted objects, features extraction, and classification. A Support Vector Machine (SVM) is used as the supervised model in two phases which are testing and training. Intensity value, auto-correlation matrix value of detected corners, and, energy, are three extracted features used to train the SVM. Experimental results show this method classify images with more accuracy and less execution time compared to the existing method

    The role of earnings management and dividend announcement in explanation of information asymmetry: Evidence from Tehran Stock Exchange

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    This study examines the relationship between earnings management and information asymmetry based on some companies listed in Tehran Stock Exchange over the period of 2005-2010. The study only uses qualified samples by taking into account all limitations and necessary criteria. Based on the results of this survey, we can conclude that there is not a significant relationship between earning management and information asymmetry in Tehran Stock Exchange. There is also not a significant relationship between low or high earning management and information asymmetry. Estimated dividend announcement has information content and it can influence on information asymmetry. Finally, in Tehran Stock Exchange, there is information asymmetry and after dividend announcement, its value is more than before

    Extracting Implicit Social Relation for Social Recommendation Techniques in User Rating Prediction

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    Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users' ratings to items by describing Hellinger distance between users in recommender systems. Then, we propose to incorporate the predicted trust scores into social matrix factorization models. By analyzing social relation extraction from three well-known real-world datasets, which both: trust and recommendation data available, we conclude that using the implicit social relation in social recommendation techniques has almost the same performance compared to the actual trust scores explicitly expressed by users. Hence, we build our method, called Hell-TrustSVD, on top of the state-of-the-art social recommendation technique to incorporate both the extracted implicit social relations and ratings given by users on the prediction of items for an active user. To the best of our knowledge, this is the first work to extend TrustSVD with extracted social trust information. The experimental results support the idea of employing implicit trust into matrix factorization whenever explicit trust is not available, can perform much better than the state-of-the-art approaches in user rating prediction

    Synthesis and Characterization of Hard Cr2O3 and Superhard Cr-Zr-O PVD Coatings

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    Reactive radio-frequency magnetron sputter technique (RF-MS) was used to deposit Cr-O and Cr-Zr-O coatings on silicon, SS316L, WC-Co, and HSS M42 substrates. The effects of deposition temperature, chemical composition, and subsequent heat treatment on microstructural, thermal stability, and mechanical properties of both Cr-O and Cr-Zr-O coatings were investigated. The deposited coatings were characterized using scanning electron microscopy, Xray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, Energy dispersive spectroscopy, nanoindentation, Rockwell “C” indentation, optical profilometer, reciprocating wear testing, electrochemical testing, and inductively coupled plasma analysis. The results showed that appropriate deposition conditions were required in order to obtain hard Cr2O3 coating. A Cr2O3/Cr duplex interlayer was found to be suitable for nucleation of diamond coatings on WC-Co substrates as it restricted graphite formation before diamond nucleation, thus, continuous diamond coatings with good adhesion were successfully deposited on Cr2O3/Cr interlayered WC-Co substrates. Furthermore, hard Cr2O3 coatings were shown to be a potential candidate to improve the mechanical properties and to reduce the toxic ion release rate of orthopedic implants. The coated SS316L substrates illustrated better wear and corrosion resistance and lower friction coefficient compared to bare 316L substrates under a reciprocating sliding condition in saline solution. Furthermore, many fewer Cr ions were released from coated SS316L substrates after immersion tests. Adding zirconium to Cr2O3 coating shifted the onset of crystallization for the Cr2O3 coating to higher temperatures and superhard Cr-Zr-O coatings with a hardness value over 40 GPa could be obtained at a zirconium concentration of around 9.5 at. % and a substrate temperature of 300°C. The obtained superhardness could be attributed to the formation of a nanocomposite structure

    An Iconographic Study of Sultan Mohammad Naqash's Painting Called "Masti Lahouti - Nasuti "

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    The painting called “Lahouti (divine) and Nassotti (worldly) Intoxication”, has been drawn on a page in Divan Hafez by Sam Mirza, whose painter was Sultan Mohammad Naqash, a Tabriz Safavid School painter, who is regarded as one of the shining examples of pictorial icons for the creation of a mystical, symbolic, and theatrical atmosphere as well as visual attractions. The present study is a theoretical one and has been conducted through a descriptive-analytical method, analyzing the iconography used in the above-mentioned painting by collecting images and information using the library method. By utilizing a historical and semantic approach to Hafiz's poetry as well as the artistic style of Sultan Mohammad, this study aims at decrypting the mystical and narrative concepts in this painting. The main research question raised here is: "What are the philosophical, mystical, lyrical and mythological concepts behind the relationship between icons and the visual atmosphere dominating the image?" Review of literature was conducted on Hafez's life as well as semantics and stylistics used in his odes as well as the history of the Turkmen and Tabriz Safavid Painting Schools and the style of Sultan Mohammad Naqash, recorded in articles and books by Iranian and foreign authors. The above-mentioned resources were studied, and it was concluded that Sultan Mohammad’s exaggerated, and humorous style matches Hafiz's quick-witted outlook and it is appropriate to divide the painting into three distinctive parts from top to bottom and consider the appropriate icons for each of the sections through a mystical and separating perspective as Nassott, Malakut and Lahout. Kajian Ikonografi Lukisan Sultan Muhammad Naqash Berjudul "Masti Lahouti - Nasuti" Abstrak Lukisan yang berjudul “Lahouti (divine) and Nassotti (worldly) Intoxication”, digambar pada sebuah halaman di Divan Hafez oleh Sam Mirza, di mana pelukisnya adalah Sultan Mohammad Naqash, seorang pelukis Sekolah Tabriz Safawi, yang dianggap sebagai salah satu contoh cemerlang ikon bergambar untuk penciptaan suasana mistis, simbolis dan teatrikal serta atraksi visual. Penelitian ini bersifat teoretis dan dilakukan melalui metode deskriptif-analitik, menganalisis ikonografi yang digunakan dalam lukisan tersebut dengan mengumpulkan gambar dan informasi menggunakan metode kepustakaan. Dengan memanfaatkan pendekatan historis dan semantik pada puisi-puisi Hafez serta gaya artistik Sultan Mohammad, kajian ini bertujuan untuk mendekripsi konsep mistik dan naratif pada lukisan. Pertanyaan penelitian utama yang diangkat yaitu: "Apa konsep filosofis, mistis, liris, dan mitologis dibalik hubungan antara ikon dan suasana visual yang mendominasi gambar?" Tinjauan literatur dilakukan pada kehidupan Hafez serta semantik dan gaya yang digunakan dalam syairnya serta sejarah Sekolah Lukisan Safawi Turkmenistan dan Tabriz dan gaya Sultan Mohammad Naqash, yang dicatat dalam artikel dan buku oleh penulis Iran dan asing. Melalui sumber yang didapat maka disimpulkan bahwa gaya Sultan Mohammad yang berlebihan dan humoris cocok dengan pandangan Hafez yang cerdas dan pantas untuk membagi lukisan menjadi tiga bagian yang berbeda dari atas ke bawah dan mempertimbangkan ikon yang sesuai untuk masing-masing bagian melalui perspektif mistis dan terpisah sebagai Nassott, Malakut dan Lahout

    The Theory of Non-organic Viruses in Psymentology

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    AbstractOne of the most indispensable theories in Psymentology is the “Non-organic Viruses Theory”. According to this theory, mankind is encountered with viruses that could affect his mind, body and psyche; infiltrate in man's diverse existing components and data files, having them contaminated with parasites and derangements. When such parasites occupy the Mind data files, they consequently would bring about all kinds of hallucinations, abnormal behaviours and unusual drives. In Psymentology there is a specific approach toward these types of disorders and the treatment for such cases lies within a special branch of treatment called “Defensive Radiation”. In other words, through resolving the symptoms of this contamination as well as purifying the patient from Non-organic Viruses, we are able to get rid of them and the subsequent complications. During the past few decades numerous successful experiences have been carried out proving the afore-mentioned theory

    The Use of Compensation Strategies in the Iranian EFL Learners’ Speaking and its Relationship with Their Foreign Language

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    Compensation Strategies (CpSs) are strategies which a language user employs in order to achieve his intended meaning when precise linguistic forms are for some reasons not available at that point of communication. Different factors may influence the use of CpSs, among which the level of language proficiency is one of the most important ones. The present study attempts to investigate the relationship between compensation strategies use and the level of language proficiency and gender. In order to explore this relationship, four distinct groups of learners – advanced male, advanced female, intermediate male, and intermediate female, each containing 12 members– participated in the study. The participants were interviewed individually and their performances were tape-recorded and then transcribed. The findings of the study indicates that "self-repetition", "direct appeal for help", and "approximation" are the most frequently used strategies; there is a significant relationship between the frequency of compensation strategies use and proficiency i.e. the frequency of compensation strategies use increases as the level of language proficiency develops whereas no significant relationship was observed between strategy frequency and gender. Keywords: Compensation Strategies, Approximation, Circumlocution, Fillers, Repetition, Language Proficiency