Miracle-dz/UniFAR-FTUs huggingface dataset:
Credibility of Celebrity Endorsement and Buying Intentions an Evidence from Students of Islamabad, Pakistan

Celebrity Endorsement has become one of the important tools in advertisement persuading customers. No study has been yet conducted in Pakistan to measure the impact of credibility of celebrity on the buying intentions of customers. This paper investigates the credibility of celebrity endorser influence on consumers buying intention and also whether the experience of celebrity with the usage of endorsed product matters to consumers or not. For this purpose Regression tests are used and questionnaire was distributed to respondents who were university students/scholars. Results show that the in celebrity endorsement, credibility of endorsing celebrity matters for the consumer before the endorsed product also the experience of the celebrity with that product usage. Companies using celebrity endorsement strategy for their promotion must carefully select the endorsing celebrity with relatively high credibility.
A Security Perspective on Code Review: The Case of Chromium

Modern Code Review (MCR) is an established software development process that aims to improve software quality. Although evidence showed that higher levels of review coverage relates to less post-release bugs, it remains unknown the effectiveness of MCR at specifically finding security issues. We present a work we conduct aiming to fill that gap by exploring the MCR process in the Chromium open source project. We manually analyzed large sets of registered (114 cases) and missed (71 cases) security issues by backtracking in the project's issue, review, and code histories. This enabled us to qualify MCR in Chromium from the security perspective from several angles: Are security issues being discussed frequently? What categories of security issues are often missed or found? What characteristics of code reviews appear relevant to the discovery rate? Within the cases we analyzed, MCR in Chromium addresses security issues at a rate of 1% of reviewers' comments. Chromium code reviews mostly tend to miss language-specific issues (eg C++ issues and buffer overflows) and domain-specific ones (eg such as Cross-Site Scripting), when code reviews address issues, mostly they address those that pertain to the latter type. Initial evidence points to reviews conducted by more than 2 reviewers being more successful at finding security issues.
Improvement in lifetime and replication quality of Si micromold using N:DLC:Ni coatings for microfluidic devices

In this paper the effect of surface properties of micromolds on replication process was investigated by using nitrogen (N) and nickel (Ni) doped diamond-like carbon (N:DLC:Ni) coated and uncoated silicon (Si) micromolds. Hot embossing is one of the most popular replication technologies for low cost and mass production. However higher friction and adhesion in hot-embossing process can shorten the lifem. cn
Biometric Fusion System based on IRIS and Fingerprint Recognition using GA along with ANN

: In the authentic world applications, uni-modal biometric systems often face limitations because of appropriate feature, noise, size of data etc. Biometric system for identification and authentication provides automatic recognition of an individual based on certain unique features or characteristics possessed by that individual. Iris recognition is a biometric identification method that uses pattern recognition on the images of the iris of an individual. Fingerprint recognition is used for the verification of the authenticity of the person by the fingerprint. In the proposed work, we have two sections, first section is iris recognition and second section is fingerprint recognition. At the last, Parameters namely, FAR, FRR and Accuracy are used for the evaluation of the work. The work is being designed and developed on the basis of ANN (Artificial Neural Network), HCT (Hough Circular Transform), GA (Genetic Algorithm) and SIFT (Scale invariant feature transform) algorithms. Our investigational results suggest that the ANN method for the recognition at the decision level is the most excellent followed by the different techniques like Sum Rule, SVM, Clustering and KNN. The performance evaluation of proposed technique is reported in terms of FAR, FRR, and accuracy after doing comprehensive tests on the CASIA-Iris databases for iris and the FVC 2004 fingerprint database and we concluded the accuracy of proposed system is more than 96% with a better FAR and FRR value.
A Framework to Detect Presentation Attacks A Framework to Detect Presentation Attacks

Biometric-based authentication systems are becoming the preferred choice to replace password-based authentication systems. Among several variations of biometrics (e.g., face, eye, fingerprint), iris-based authentication is commonly used in every day applications. In iris-based authentication systems, iris images from legitimate users are captured and certain features are extracted to be used for matching during the authentication process. Literature works suggest that iris-based authentication systems can be subject to presentation attacks where an attacker obtains printed copy of the victim’s eye image and displays it in front of an authentication system to gain unauthorized access. Such attacks can be performed by displaying static eye images on mobile devices or iPad (known as screen attacks). As iris features are not changed, once an iris feature is compromised, it is hard to avoid this type of attack. Existing approaches relying on static features of the iris are not suitable to prevent presentation attacks. Feature from live Iris (or liveness detection) is a promising approach. Further, additional layer of security from iris feature can enable hardening the security of authentication system that existing works do not address. To address these limitations, this thesis proposed iris signature generation based on the area between the pupil and the cornea . Our approach relies on capturing iris images using near infrared light. We train two classifiers to capture the area between the pupil and the cornea. The image of iris is then stored in the database. This approach generates a QR code from the iris. The code acts as a password (additional layer of security) and a user is
Using SAS ® OpRisk Global Data to Improve Decision-Making at a Bank

The management of financial losses is crucial as banks are required to set aside regulatory capital to absorb unexpected losses. Banks also need to calculate economic capital to ensure solvency according to their own risk profile. The main financial risks faced by banks are market, credit, and operational risk. Operational risk, the focus here, includes fraud, improper business practices, and so on. Barings Bank’s loss of over USD1 billion due to rogue trading activities is an extreme example of such risk. In order to calculate capital to withstand this risk, the aggregate distribution of expected losses for the next year is determined. The extreme quantiles of this distribution are of specific interest. For instance, a bank should hold capital to survive a one-in-a-thousand-year aggregate operational loss (the 99.9% VaR of the distribution). Companies often have only limited internal data available to accurately model the distribution and therefore use external sources and scenario assessments to supplement their data. Combining the internal data of a given bank with external data is challenging, as such data is collected from differently sized institutions in various regions. This might impact the estimated loss distribution. In this paper, we use SAS® OpRisk Global Data to show how external and internal data can be integrated for use in the capital modeling process. We also suggest measures to challenge experts to adjust scenario assessments based on historical data.
Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point Clouds

In this work, we propose Dilated Point Convolutions (DPC). In a thorough ablation study, we show that the receptive field size is directly related to the performance of 3D point cloud processing tasks, including semantic segmentation and object classification. Point convolutions are widely used to efficiently process 3D data representations such as point clouds or graphs. However, we observe that the receptive field size of recent point convolutional networks is inherently limited. Our dilated point convolutions alleviate this issue, they significantly increase the receptive field size of point convolutions. Importantly, our dilation mechanism can easily be integrated into most existing point convolutional networks. To evaluate the resulting network architectures, we visualize the receptive field and report competitive scores on popular point cloud benchmarks.
Morphological and molecular study of sex determination in Cannabis sativa L.

Cannabis sativa L. is an important plant with various uses in pharmaceutical and paper production industries. Due to the higher priority of female and male Cannabis plants for pharmaceutical uses and fibre industry, respectively, reduction of the quality of products after pollination, and also for detection of better genotypes before pollination for breeding purposes, early determination of sex in Cannabis is one of the major concerns of researchers and farmers. Seeds of 26 accessions from different regions of Iran along with one accession from Afghanistan were planted in the field based on randomized complete block design with 10 replications. Five female and five male plants were sampled from each accession for molecular and morphological analyses. Thirteen ISSR primers and two SCAR markers were used. Also, morphological differences, which possibly related to sex were measured in the Cannabis populations under study. The results showed significant differences among the accessions within female and male plants for plant height, number of days to flowering, days after full bloom and height of the first flowering node. Male plants were generally, but not always, taller than female plants and had a shorter life cycle. The highest expected heterozygosity was found in the ISSR3 primer and the lowest in the UBC825 primer. In total, 143 polymorphic bands and one polymorphic band were amplified using ISSR and SCAR primers, respectively. Out of 143 polymorphic ISSR bands, only 10 markers had significant relations with the gender of this plant. MADC6 SCAR marker was monomorph across the accessions. On the other hand, MADC5 was a polymorphic marker and showed a significant relation with gender. These markers, especially MADC5, have the potential to be used in sex determination of C. sativa.
Análisis bayesiano de barreras al emprendimiento en la universidad Bayesian analysis of barriers towards entrepreneurship at university

The creation of small and medium business is one of the work alternatives available to university graduates in any area of knowledge, as well as a mechanism through which university professors can transfer useful or relevant knowledge to society. Given that entrepreneurship is considered a key element to boost societies and optimize the economic system, the promotion or facilitation of the creation of companies at the university level can be considered desirable. There are multiple strategies designed to sponsor entrepreneurship and some of the most relevant, both theoretical and practical, are based on models of attitudinal changes. Recent theoretical models in the study of entrepreneurship point out that the perception of obstacles by potential entrepreneurs can explain creation and entrepreneurial intention. This work uses inference and Bayesian networks to model the impact of different potential obstacles on the intention and creation of companies between university professors and students. A sample of 2671 professors and 1224 university students (1744 were women and 1917 were men) completed a survey to identify the perceived potential obstacles to business creation. The R bnlearn statistical package was used to estimate structural models of the Bayesian network that modeled creation and entrepreneurial intention based on perceived obstacles. The results show that professors and students differentially perceive potential barriers to entrepreneurship. While professors create companies despite certain perceived obstacles, the intention and creation of companies is inhibited in the students according to the perceived obstacles. These results can be used to improve the university entrepreneurship empowerment programs and to optimize the chances of success in potential entrepreneurs originating at the university.
Motif Density for Selecting Optimal Window Length in Motif Discovery

- Motif discovery is not only a fundamental method for finding repetitive subsequences in a longer time series, but is also used as a sub-routine in higher-level analytics including classification, clustering, visualization, and rule discovery. However, existing motif discovery algorithms depend critically on the knowledge of the correct subsequence length. Therefore, deciding an appropriate window length for subse-quences is required before using those algorithms. In this work, we investigate how to decide an appropriate window length. We propose a novel index called a ‘motif index’ that counts the number of similar subsequence occurrences within the neighborhood in the space of subsequence, while avoiding trivial matches. We also propose a heuristic method to select an appropriate error distance for the neighborhood required as a parameter to define motif density. Furthermore, we show that motif density can decide an optimal window in the simulation data in which motifs are intentionally embedded.
International Journal of Current Research in

Date of Publication: 06 August 2019 Biopolymers are the rarely produced bio products which are used as an alternative for common plastic and some microbes can even digest them. In this study we have confirmed that Bacillus cereus can produce such bio polymers. B. cereus, isolated from sludge soil sample was standalone which showed substantial PHB production (4.2 ±0.25 g/l) after 48 h of fermentation as examined by spectrophotometric analysis. Time-course (24-96 h) analysis for PHB production indicated that PHB was a growth-associated product and its accumulation significantly increased during the exponential phase and reached maximum after 48 h (5.6 ±0.25 g/l). The maximum PHB yield was achieved after 48-72 h of fermentation (6.5±0.18 g/l). The FT-IR analysis, illustrates bands at 3280.92 and 2924.09 cm−1 corresponding to aliphatic ester carbonyl C=O of R COA and C-H stretch, respectively. Other absorption bands at 1633.71 and 1533.09 cm−1, represent the presence of O-H bonding and C-H bond of aliphatic compounds, respectively. The band at 1633.71 cm−1 considered as diagnostic signal for PHB. The band found at 1,380.17 cm−1 is assigned to symmetric wagging of CH3 groups. The 1H-NMR spectra showed the presence of three signals, it’s the characteristic of the polymer of PHB. Keywords
Queuing Theory Based Enhanced Resource Allocations over IAAS Cloud Architectures

: Cloud computing has been an emerging technology in recent years in providing computational and infrastructural resources as a service. Cloud computing greatly reduces the deployment and maintenance of web applications since it provides infrastructure as a service (IaaS) and platform as a service (PaaS) for web applications. This results in increase of number of web applications being deployed over cloud. Hence scheduling of resources and managing the performance of the cloud servers form the important research in cloud computing. This paper proposes an efficient resource allocation technique over cloud based on a (M/M/C):( ∞/FIFO) queuing theory model. The proposed algorithm reduces the user waiting time and gives faster response rate. The performance of the proposed model is analyzed based on different parameters such as the arrival rate of customers and the number and service rate of processing servers etc. Numerical analysis and experimental simulation shows the effectiveness of the proposed model .
CORPORATE SOCIAL RESPONSIBILITY AND FINANCIAL PERFORMANCE: A STUDY OF INDIAN BANKING SECTOR

Corporate social responsibility (CSR) has the potential to make positive contribution to the development of society and businesses. In 2007, the Reserve Bank of India suggested the banks to pay special attention towards integration of social and environment concerns in their business operations to achieve sustainable development. RBI also pointed out to start non financial reporting (NFR) by banks which will cover the work done by banks towards the social, economic and environmental betterment of society. The CSR in Indian banking sector aimed towards addressing the financial inclusion, providing financial services to the untapped areas of the country, the socio-economic development of the country by focusing on the activities like poverty eradication, health and medical care, rural area development, self employment training and financial literacy trainings, infrastructure development, education and environment protection, etc. So the banks are beginning to see the benefits from setting up strategic CSR agendas. The increasing attention to CSR is based on its capability to influence firms’ performance. From a long time several studies have reported unpredictable impact of corporate social responsibility on financial performance. Therefore it is important to study the relationship between social and financial performance of a company. Using a sample of twenty banks, this study has tried to examine the impact of CSR activities on financial performance measured in terms of return on equity and return on assets. The study concluded that financial performance may get affected by CSR to some extent but on the other hand it can be drawn from the results that if the banks start following CSR practice to the desired extent then these may have significant impact on their financial performance.
A Response to “Trade Induced Technical Change: Did Chinese Competition Really increase European Innovation?” by Campbell and Mau

Before getting into details, we want to emphasize what we regard as the contributions of our paper. In BDVR we argued that Chinese import competition has played a role in upgrading European technology by about 15% between 2000 and 2007 (as cited in our abstract). This is based on nine underlying empirical results showing Chinese competition both reallocated activity to higher tech firms and increased technology within firms. On reallocation, Chinese import competition decreased survival rates more for low tech firms measured by the lagged level of (1) TFP, (2) IT intensity and (3) patenting intensity; and it decreased employment more for firms who were low tech as measured again by (4) TFP, (5) IT intensity and (6) patent intensity. In the within firm dimension, companies more exposed to Chinese competition upgraded their technologies by more as measured by changes in (7) TFP, (8) IT intensity and (9) Patenting.
A Multiple Curve Lévy Swap Market Model

ABSTRACT In this paper, we develop an arbitrage-free multiple curve model through the specification of forward swap rates. Two sets of assets are chosen as fundamentals: OIS zero-coupon bonds and forward rate agreements. This is a very natural approach since, on the one hand, OIS bonds represent the class of risk-free discount bonds and, on the other hand, the mid and long maturity part of the interest rate term structure is bootstrapped from quotes of swap rates that can be represented by FRA rates and OIS bond prices in the multiple curve setting. We construct the rates via a backward induction along the tenor structure on the basis of the forward swap measures. Time-inhomogeneous Lévy processes are used as drivers of the dynamics. As an application, we derive an approximative Fourier-based valuation formula for swaptions. The model is implemented and calibrated by using generalized hyperbolic Lévy processes as drivers.
Time After Time: Difference-in-Differences and Interrupted Time Series Models in SAS

Healthcare and other epidemiological researchers are increasingly turning to difference-indifferences(D-I-D) and interrupted time series models (ITS) to analyze preand postchanges in outcomes around an intervention or exposure. These models are often used in quasi-experimental studies with non-randomized exposures using retrospective observational data, and they allow a causal interpretation and adjustment for secular trends in the outcome of interest. D-I-D models compare the rate of change an outcome measure before and after an exposure in exposed and control groups based on a single measure in each period. D-I-D data can be modeled with repeated-measures generalized linear models with an interaction term between time period and the exposure variable. The ITS – an extension of the D-I-D design compares trends in an outcome over multiple preand posttime period measures, allowing for a discontinuity (an “interruption”) in both control and exposure average rates during the study period. Models of this type account for situations where rates of an outcome of interest shift in both exposed and control groups at a specific time point, such as the change from ICD9 to ICD10 diagnosis codes during 2015. We will discuss the statistical basis of these methods and illustrate data structure, modeling methods, power calculations and interpretation of model estimates for both models with data from studies performed in a large integrated healthcare system.
Conjunctivodacryocystorhinostomy using Mateireau tube with endoscopy assistance

DOI:10.14744/bej.2018. 69775 Beyoglu Eye J 2018; 3(3): 142-145 Original Article Ozturk Karabulut et al., Conjunctivodacryocystorhinostomy with mateireau tube 143 planus, Steven–Johnson’s syndrome, systemic chemotherapy (usually docetaxel treatment), radiation therapy, and canalicular dysfunction in facial nerve palsy or as a complication of unsuccessful DCR (2, 7, 8). However, the cause of obstruction is mostly unknown. In this article, our aim was to analyze the surgical outcome of CDCR operation with permanent silicone tube implantation coated with polyvinylpyrrolidone (PVP) (Métaireau tube, France Chirurgie Instrumentation (FCI) S.A. S. France Chirurgie Instrumentation 20–22 rue Louis Armand 75015 PARIS France) with aid of nasal endoscopy and to obtain subjective measure of patient satisfaction.
State of the Art on: Deepfake Detection

Media manipulation exists since the times of the first analog photographs but the switch to digital media, besides bringing great technical benefits, made the manipulation process easier. Although today we can enjoy entire movies synthesized by computer graphics, at the same time threats linked to the misuse of such technologies are frighteningly increasing. It is of crucial importance to always be able to tell apart real images and videos from synthesized ones, but sometimes it can be a hard task. Fake media are computer generated or manipulated images or videos with the precise goal to fool human eye: for this reasons sophisticated computational techniques like Deep Learning exist, and are still being studied, to perform this task with a higher accuracy than humans. Table 1 shows the most prestigious journals and conferences on the research area, according to their H-index1.