Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Analytics and Management with Big Multidimensional Data

Big data majorly is referred as extensive amount of data that is used for ideation in current times. The rapid evolution and adoption of big data by industry has enforced the academics, researchers, and industry to investigate on its intricacies. This paper provides an overview on issues and achievements in the field of analytics over big data. The paper’s primary focus is on the analytic methods used for big data. The study explores the views on analytics over big multidimensional data as well, by highlighting open problems and actual research trends. The current study explores several novel research directions in big data which plays a leading role in next-generation Data Warehousing and OLAP research.
THE ROLE OF CORPORATE DIVERSIFICATION IN TAX AVOIDANCE IN COMPANIES LISTED IN THE TEHRAN STOCK EXCHANGE

Purpose of the Study: Tax avoidance means the use of gaps in tax laws for non-payment or late payment of taxes for companies, which is affected by different factors. The present study investigates the impact of diversification on tax avoidance in companies. To this end, the financial information of 384 firms during the period of 2011- 2016 in the Tehran Stock Exchange was examined. Methodology: In this research, the required financial information was summarized, classified, and calculated in Excel software and the data were analyzed by using E-views software. The dependent variables were effective tax rate and book-tax difference, while the independent variable was corporate diversification, which shows how to divide the market between business sectors (units) in a company. Control variables include size, financial leverage, company’s loss-making, ROA, capital expenditures, R&D, market to book value, CEO ownership, and management of ownership. Conclusions/Results: The findings obtained from this study demonstrate that at a 95% confidence level, there is no significant relationship between diversification and effective tax rates in companies listed in the Tehran Stock Exchange. However, at a 90% confidence level, diversification reduces the effective tax rate. Furthermore, no reliable evidence was found regarding the effect of diversification on book-tax difference at a 95% confidence level. Novelty: Tax is a charge imposed by the government on all organizational profits. Various enterprises have complex operations due to their institutional structure, which makes it possible to increase tax avoidance in these companies. The production or sale of a variety of products (diversification) is bigger and has more complex organizational structures that increase the cost of management and non-management decisions, making it difficult for companies to coordinate their policies. Thematic classification: G10, M41
Training Deep Residual Network with Funnel Online Hard Examples Mining Method on Object Detector

The image sets always contains most of the simple samples and a small number of difficult samples. If the network can automatically select difficult samples, the performance will be improved. In the field of object detection, R-CNN, Fast-RCNN (FRCN) and Faster R-CNN (FRCNN) are regarded as the leader of the detection network architectures. They focus on solving the time efficiency problem, but did not automatically choose difficult samples. The recent Online Hard Examples Mining (OHEM) method is a good solution to this problem. But for small sample sets, the effectiveness is not good enough. In this paper, the feature extraction layer as well as the difficult mining method are designed and applied on Faster-RCNN detector. The network proposed here achieved 78.3% mAP on the PASCAL VOC2007 test set, which are 5.1 point higher than that of FRCNN (VOC2007, 73.2%).
Efficient ID-Based Password Authenticated Key Exchange Using Multiple Server

: Password Authenticated Key Agreement is a relational method for two or more entities to establish cryptographic key exchange based on one or more entity’s ability of the password. PAKE protocol that are designed to be safe even session key based on shared human memorable password. The main objective of these protocols is security against password dictionary attacks. A exact answer of this protocol involves segmenting the password between the multiple servers. If a single server is accord by an attacker, the password is required to remain secure. If a two servers are accord by an attacker, the secure password is not obtained. To avoid this problem, It introduce identity based multiple server password authentication key exchange protocol. By the authority, It can generate id based multiple server PAKE protocols which achieve fixed authentication. As far as the elemental two-party PAKE protocol and identity based signature scheme have confirmable security without arbitrary oracles.
Corporate Governance as a Strategic Management Tool

The objective of the study is to determine the effectiveness of corporate governance as a strategic tool in improving performance of listed manufacturing company in Nigeria. The specific objective is to examine the relationship between corporate governance mechanisms and performance of manufacturing firms in Nigeria. This study adopted quantitative research; the population for the study is seventy four, which is the total number of listed manufacturing companies in Nigeria. Twenty manufacturing companies were purposively selected from the seventy four manufacturing companies listed on the Nigeria stock exchange that formed the population of the study. The study is based on content analysis of the selected firms’ annual reports for ten years, from year 2008- 2017. Time series data were collected to determine corporate governance and profitability performance of the selected companies. Five (5) aspects of corporate governance were investigated; these include board size, gender, independence, meeting and audit committee size. The data collected were analyzed using panel data analysis. Findings revealed that heterogeneity effect across firms and over time are incorporated into the model via the error term, Board Size (BOS) and Board Gender Disparity (BGD) had negative impact on the financial performance of manufacturing firms in Nigeria. It is recommended that organizations should use corporate governance as a strategic tool to achieve corporate objectives especially by ensuring the board meets regularly to monitor and control. Keywords: Audit Committee Size, Board Gender Disparity, Board Independence, Board Meeting, Board Size, Corporate Governance, Corporate Performance, Strategic Management DOI : 10.7176/RJFA/10-14-11 Publication date :July 31 st 2019
The Use of Pronominal Case Information in Sentence Interpretation

Cross-linguistic research in the Competition Model framework (MacWhinney & Bates, 1989) has shown that sentence interpretation is driven by surface grammatical markers in accord with their relative cue strength. For example, word order is the strongest cue in English sentence processing, because it is also the most reliable and available cue in English corpora. On the other hand, word order is not a strong cue in Spanish and Japanese, because the reliability of this cue in those languages is comparatively low (Kail, 1989, Kilborn & Ito, 1989, Sasaki, 1991). Studies have repeatedly shown that subjects rely the most on cues that have high statistically validity in their language (McDonald, 1987). Bates and MacWhinney (1989) have reported that word order is the strongest cue in English, and that subject-verb agreement and animacy are much weaker. However, prior research has not yet determined the relative strength of the case-marking cue for English, since case-marking is only available for pronouns in English. Given the high reliance on case-marking that is found in languages such as Hungarian and Japanese, evidence about eventual domination of case over word order in Dutch, and the high reliability of case-marking, we might expect that casemarking could dominate over word order in English. On the other hand, word order is much more generally available than pronominal case. If availability is a factor determining the relative strength of two reliable cues, then we might expect word order to dominate over case. To date, no study has examined this theoretically important issue in cue competition.
Missing entrepreneurs

Purpose Compared with other emerging and former command economies, Russia has low levels of entrepreneurial activity and exceptionally low levels of reported entrepreneurial intentions. Drawing on the theory of planned behaviour (TPB), this paper aims to examine the determinants of entrepreneurial intentions in Russia. Design/methodology/approach Using individual level data from two waves (2013 and 2018) of the Global Entrepreneurship Monitor (GEM) survey, the paper presents a range of semi-nonparametric logistic regressions estimating the determinants of reported entrepreneurial intention among the Russian adult population not already engaged in entrepreneurial activity. These data allow for the first empirical exploration of the TPB in the Russian context. Findings The results provide evidence in support of two (“attitudes” and “perceived behavioural control”), from three, origins of the theory of planned behaviour. Firstly, positive attitudes towards entrepreneurship, in the form of employment seeking and direct (own experience) or indirect (experience through social networks) entrepreneurial knowledge are both positively associated with intention. Secondly, individuals who consider their environment to be conducive to entrepreneurship and who believe they have the knowledge and skills required to be entrepreneurs are more likely to intend entrepreneurial action. Originality/value In view of the limited entrepreneurial activity and low levels of reported entrepreneurial intention in Russia, it is important to understand the drivers of these intentions if the appropriate policy responses are to be identified and adopted. This research represents the first substantive efforts to comprehensively examine the determinants of entrepreneurial intentions for Russia and allows us to propose several policy relevant conclusions.
Post-Processing of VIS, NIR, and SWIR Multispectral Images of Paintings. New Discovery on the The Drunkenness of Noah, Painted by Andrea Sacchi, Stored at Palazzo Chigi (Ariccia, Rome)

IR Reflectography applied to the identification of hidden details of paintings is extremely useful for authentication purposes and for revealing technical hidden features. Recently, multispectral imaging has replaced traditional imaging techniques thanks to the possibility to select specific spectral ranges bringing out interesting details of the paintings. VIS–NIR–SWIR images of one of the The Drunkenness of Noah versions painted by Andrea Sacchi, acquired with a modified reflex and InGaAs cameras, are presented in this research. Starting from multispectral images we performed post-processing analysis, using visible and infrared false-color images and principal component analysis (PCA) in order to highlight pentimenti and underdrawings. Radiography was performed in some areas to better investigate the inner pictorial layers. This study represents the first published scientific investigation of The Drunkenness of Noah’s artistic production, painted by Andrea Sacchi.
Energy Harvesting Employing a Drive Similar as a Clock Unit

Abstract An energy harvesting device for frequencies of less than 2 Hz with amplitudes of several cm was developed. A pendulum is driving a gear mechanism similar as a clock unit which is driving a wheel carrying 36 magnets. Next to the magnets there are mounted 18 coils generating voltage. This way, a maximum voltage and power of 21.5 V and 114 mW are achieved at 1.25 Hz and 57 mm amplitude.
Comparative Analysis of Hybrid K-Mean Algorithms on Data Clustering

: Data clustering is a process of organizing data into certain groups such that the objects in the one cluster are highly similar but dissimilar to the data objects in other clusters. K-means algorithm is one of the popular algorithms used for clustering but k-means algorithm have limitations like it is sensitive to noise ,outliers and also it does not provides global optimum results. To overcome its limitations various hybrid k-means optimization algorithms are presented till now. In hybrid k-means algorithms the optimization techniques are combined with k-means algorithm to get global optimum results. The paper analyses various hybrid k-means algorithms i.e. Firefly, Bat with k-means algorithm, ABCGA etc. The Comparative analysis is performed using different data sets obtained from UCI machine learning repository. The performance of these hybrid k-mean algorithms is compared on the basis of output parameters like CPU time, purity etc. The result of Comparison shows that which k-means hybrid algorithm is better in obtaining cluster with less CPU time and also with high accuracy.
On the Relation between the Comprehension Ability and the NeocortexVerbal Areas

General description of the human neocortex verbal areas and exploration of the manner in which the synaptic neurolinguistic structure that develops in these areas after birth establishes our comprehension ability. Description of the manner in which the neurolinguistic subjective model of reality that develops in these areas can be made to evolve towards objective representation.
DARK MATTER IN THE CLASSICAL DWARF SPHEROIDAL GALAXIES: A ROBUST CONSTRAINT ON THE ASTROPHYSICAL FACTOR FOR γ-RAY FLUX CALCULATIONS

We present a new analysis of the relative detectability of dark matter annihilation in the Milky Way's eight “classical” dwarf spheroidal (dSph) satellite galaxies. Ours is similar to previous analyses in that we use Markov-Chain Monte Carlo techniques to fit dark matter halo parameters to empirical velocity dispersion profiles via the spherical Jeans equation, but more general in the sense that we do not adopt priors derived from cosmological simulations. We show that even without strong constraints on the shapes of dSph dark matter density profiles (we require only that the inner profile satisfies −limr → 0dln ρ/dln r ⩽ 1), we obtain a robust and accurate constraint on the astrophysical component of a prospective dark matter annihilation signal, provided that the integration angle is approximately twice the projected half-light radius of the dSph divided by distance to the observer, αint ∼ 2rh/d. Using this integration angle, which represents a compromise between maximizing prospective flux and minimizing uncertainty in the dSph's dark matter distribution, we calculate the relative detectability of the classical dSphs by ground- and space-based γ-ray observatories.
Improved Power-Throughput Blowfish Algorithm on FPGA

It is well-known that advanced encryption standard (AES) algorithm is used for protection against various classes of wireless attacks in wireless communication standard such as Wi-Fi, Wi-MAX, Zig-bee and Bluetooth. However, the AES is a complex algorithm that consumes a larger design core, time, and power source. Hence, this paper presents a development of an improved power-throughput Blowfish algorithm on Zynq-7000 field-programmable gate array (FPGA) as an alternative security algorithm. The proposed memory-based method is used to optimize the performance of Blowfish. The performance is analyzed in terms of its architecture, throughput, and power consumption. Index Terms: advanced encryption standard, Blowfish, security, power-throughput, field-programmable gate array.
Logging System for Cloud Computing Forensic Environments

Cloud computing represents a rather new technology and a different paradigm in the field of distributed computing that involves more and more researchers. We can see in this context the need to know exactly where, when and how a piece of data is processed or stored. Compared with classic digital forensic, the field of cloud forensic poses a lot of difficulties since data is not stored on a single storage unit and furthermore it involves the use of virtualization technologies. In this paper we will present in detail a new and novel way of monitoring activity in cloud environments and datacenters using a secure cloud forensic framework. We talk about the architecture of such framework and how can it be applied on top of new or existing cloud computing deployments. Also, for testing and results collecting we have implemented this solution to our previous developed cloud computing system.
ASSEMBLE: <underline>A</underline>ttribute, <underline>S</underline>tructure and <underline>S</underline>emantics Based S<underline>e</underline>rvice <underline>M</underline>apping Approach for Collaborative <underline>B</underline>usiness Process Deve<underline>l</underline>opm<underline>e</underl

Development of a Business Process (BP) is a challenging task for small and medium enterprises (SMEs) which often do not have adequate resources for design, coding, and management of their BPs. Knowledge of existing BPs of related organizations can be exploited for collaborative BP development. However, syntactic and semantic heterogeneity among the Web service operations of BPs across organizations is a major obstacle to such collaborative BP development. In this paper, we propose an approach for collaborative BP development that exploits the attribute and structural similarity of related BPs as well as the semantic information including preconditions and postconditions of operations, to compute a mapping between the available service operations of the user organization and the BP operations of other organizations. We experimentally evaluate the approach with real world data from e-commerce sales BPs and demonstrate its effectiveness.
Extracting and identifying concrete structural defects in GPR images

Traditionally most GPR data interpretations are performed manually. With the advancement of computing technologies, how to automate GPR data interpretation to achieve high efficiency and accuracy has become an active research subject. In this paper, analytical characterizations of major defects in concrete structures, including delamination, air void and moisture in GPR images, are performed. In the study, the image features of different defects are compared. Algorithms are developed for defect feature extraction and identification. For validations, both simulation results and field test data are utilized.
Super-resolution using a light inception layer in convolutional neural network

Recently, several models based on CNN architecture have achieved great result on Single Image Super-Resolution (SISR) problem. In this paper, we propose an image super-resolution method (SR) using a light inception layer in convolutional network (LICN). Due to the strong representation ability of our well-designed inception layer that can learn richer representation with less parameters, we can build our model with shallow architecture that can reduce the effect of vanishing gradients problem and save computational costs. Our model strike a balance between computational speed and the quality of the result. Compared with state-of-the-art result, we produce comparable or better results with faster computational speed.
Leveraging supplementary transcriptions and transliterations via re-ranking

Grapheme-to-phoneme conversion (G2P) and machine transliteration are important tasks in natural language processing. Supplemental data can often help resolve difficult ambiguities: existing transliterations of the same word can help choose among a G2P system’s candidate output transcriptions; similarly, transliterations from other languages can help choose among candidate transliterations in a given language. Transcriptions can be leveraged in this way as well. In this thesis, I investigate the problem of applying supplemental data to improve G2P and machine transliteration results. I present a unified method for leveraging related transliteration or transcription data to improve the performance of a base G2P or machine transliteration system. My approach constructs features with the supplemental data, which are then used in an SVM re-ranker. This re-ranking approach is shown to work across multiple base systems and achieves error reductions ranging from 8% to 43% over state-of-the-art base systems in cases where supplemental
Semantic Interpretation and the Resolution of Ambiguity

When there are many people who don't need to expect something more than the benefits to take, we will suggest you to have willing to reach all benefits. Be sure and surely do to take this semantic interpretation and the resolution of ambiguity that gives the best reasons to read. When you really need to get the reason why, this semantic interpretation and the resolution of ambiguity book will probably make you feel curious.
Electrical Test of Resistive and Capacitive Open Defects at Data Bus in 3D Memory IC

We propose an electrical test method of resistive and capacitive open defects occurring at data bus lines between dies, and between dies and I/O pins in 3D memory ICs. The test method is based on supply current of an IC. The number of test vectors for a 3D memory IC made of ND memory dies in the test method is 10∙ND and small. Also, defective interconnects are located by the test method. Feasibility of the tests is examined by some experiments for a circuit made of an SRAM IC on a printed circuit board. The experimental results show that capacitive open defects and resistive open ones whose resistance values are greater than 200Ω can be detected by the test method.
Lomber Disk Hernisi Olan Hastaların Sağlıklı Yaşam Biçimi Davranışlarının ve Öz-Bakım Gücünün Belirlenmesi

Amac: Tanimlayici ve kesitsel tipte olan calisma, lomber disk hernisi olan hastalarin saglikli yasam bicimi davranislarini ve oz-bakim gucunu incelemek amaciyla yapildi. Y ontem: Bir universite hastanesinin Beyin ve Sinir Cerrahisi Anabilim Dali’nda lomber disk hernisi tanisi ile yatan 240 hasta calismaya dahil edildi. Arastirmanin verileri Kisisel Bilgi Formu, Saglikli Yasam Bicimi Davranislari Olcegi II (SYBDO) ve Oz- Bakim Gucu Olcegi (OBGO) kullanilarak toplandi. Verilerin analizinde PASW 18 paket programi kullanildi. Bulgular: Arastirmaya katilan h astalarin yas ortalamasi 50.88±14.05 yil, %73.8’i kadindi. Katilimcilarin lomber disk hernisi tanisi konulma zamani ortalama 5.8 yildi ve %39.02’si bel agrisi sikayeti ile hastaneye basvurdu. Lomber disk hernili bireylerin Saglikli Yasam Bicimi Davranislari Olcegi puan ortalamasi 125.09±21.05 ve Oz-Bakim Gucu Olcegi puan ortalamasi 73.32±24.36 olarak belirlendi. Yas, beden kitle indeksi, sosyoekonomik durum ve kronik hastalik varliginin saglikli yasam bicimi davranislarini etkiledigi goruldu. Kirk yasin altinda, calisan ve lomber disk hernisi ile ilgili onceden tedavi goren hastalarin oz- bakim gucunun daha yuksek oldugu saptandi. Sonuc : Hastalarin oz-bakim gucunun ve saglikli yasam bicimi davranislarinin orta duzeyde oldugu belirlendi. Lomber disk hernisinin fiziksel aktivite seviyelerini olumsuz yonde etkiledigi goruldu.
Une ressource pédagogique pour l'enseignement par simulation : cas des panneaux photovoltaïques

L'objectif de cet article est de presenter une approche pedagogique dediee a l'enseignement des panneaux photovoltaiques (PV) aux differents niveaux d'etudes (lycee, bac+2, bac+3, bac+5), ca pour les ecoles qui ont un probleme de manque de materiels ou qui n'ont pas les moyens pour les acheter, ceci en utilisant des logiciels de prototypage et de modelisation/simulation a cout reduit (PSIM et MATLAB/SIMULINK), en plus cet article montre aussi comment utiliser ces logiciels afin d'atteindre approximativement l'objectif de la formation pour chaque niveau d'etude. Cet article pourra etre aussi un tutorial sur lequel les chercheurs debutants dans le domaine des panneaux photovoltaiques peuvent se baser pour simuler un panneau PV avec differentes facons. Mots-cles—Approche pedagogique; tutoriel; Panneaux PV; Psim; Matlab/Simulink