Miracle-dz/UniFAR-FTUs huggingface dataset:
Bringing the Concepts of Virtualization to Gate-based Quantum Computing

Quantum computing is a promising paradigm to solve certain computational problems that are intractable for classical computers. Quantum computers manipulate bits of quantum information called qubits. Their development has gained momentum in recent years. Cloud providers offered the first quantum computers for commercial use via the cloud and continue to expand their quantum computing service offerings. Classical computing in the cloud uses virtualization to abstract from the physical computing resources to virtual resources. It enables resource sharing among multiple clients and dynamic allocation of resources to clients and applications. To this end, physical resources can be aggregated and partitioned to create customized virtual resources. In contrast, the logical execution of a quantum circuit that illustrates the computation is still tightly bound to the physical quantum device. Cloud users need to select a suitable physical quantum computer for their computations. If the calculation requires more qubits than the quantum computer has, the device cannot execute it. Otherwise, the execution of the quantum circuit blocks the entire quantum machine regardless of the qubit capacity used. This work develops a virtualization concept for quantum computing to separate the logical quantum computation from the underlying hardware. Aggregation and partitioning of quantum circuits decouple the one-to-one relationship between the computation of a quantum circuit and the execution hardware. The goal is to automate the mapping between the quantum circuits and appropriate physical quantum execution resources, including their aggregation and partitioning. The concept is implemented in a prototype and evaluated with modern quantum computers.
ASSOCIATION OF LIPIDS' METABOLISM DISORDERS WITH ALDOSTERONE SYNTHASE CYP11B2 (-344C/T) GENE POLYMORPHISM IN HYPERTENSIVE PATIENTS DEPENDING ON GLOMERULAR FILTRATION RATE

The cytochrome 11B2 aldosterone synthase gene (CYP11B2) one of the possible encoding genes that relates to changes of aldosterone and blood pressure regulation. The aim is to analyse the lipids profile changes in arterial hypertensive patients (EAH) depending on glomerular filtration rate (GFR) and gene CYP11B2 (-344C/T) polymorphism. One-hundred hypertensive patients with hypertensive-mediated target-organ damaging (2nd stage), moderate, high or very high cardiovascular risk were enrolled in the case-control study. Mean age 59.87±8.02 y.o. Chronic Kidney Disease (CKD) was diagnosed in 29 persons according to the National Kidney Foundation recommendations (2012) after glomerular filtration rate (GFR) decline <60 ml/min/1,73m for ≥3 months (measured by CKD-EPI equations). Lipids profile assessed by total cholesterol level (TC), triglycerides (TG) and low / high density level cholesterol (LDL-C, HDL-C) in serum. Also, calculated waist-hip ratio (WHR) for abdominal obesity evaluation. Control group included 48 practically healthy persons of relevant age. Gene's nucleotide polymorphism CYP11B2 (-344C/T) was examined by polymerase chain reaction. TC, LDL-C level in hypertensive patients do not relate directly to polymorphic variants of CYP11B2 (rs1799998) gene. Though, dyslipidemia is more intensively manifested in the Т-allele carriers by elevation of TG and atherogenic index (AI) 22.61-56.21% (р<0.01) as much, with lower HDL-C concentration – by 12.23% (р=0.043) and 12.95% (р=0.039), respectively, particularly in men by 25.84 (р=0.031) and 35.76% (р=0.042) higher than in women. CKD evolution in hypertensive patients follows by higher TC, TG and LDL-C that causes an atherogenic index increase (AI) by 13.54% (р=0.028). Polymorphic site of CYP11B2 (rs1799998) gene is associated with TG and AI elevation in general population (F=13.98 and F=13.25; p<0.001), both in women (F=22.99 and F=15.21; p<0.001) and men particularly (F=5.09; p=0.018 and F=4.44; p=0.027) and reduced HDL-C content (F=5.28; p=0.007), especially in men (F=9.57; p=0.001). Furthermore, it associates with WHR increase (F=13.09; p=0.003), especially in the ТТ-genotype carriers' men (F=12.74; p<0.001). Polymorphic site of CYP11B2 (rs1799998) gene associates with dyslipidemia: TG and AI elevation, as well as WHR increase in general population, particularly in ТТ-genotype carriers' men. CKD in hypertensive patients is more related to lipids misbalance, than polymorphic site of CYP11B2 (rs1799998) gene.
Exponential-Gamma (3, θ) Distribution and its Applications

Lifetime distributions for many components usually have a bathtub shape for its failure rate function in practice. However, there are a very few distribution have bathtub shaped failure rate function. Models with bathtub-shaped failure rate functions are useful in reliability analysis, particularly in reliability related decision making, cost analysis and burn-in analysis. When considering a failure mechanism, the failure of units in system may be due to random failure occurred by change in temperature, voltage, jurking etc or due to ageing. This paper study on a distribution, which is a mixture of Exponential and Gamma (3) distribution, which have bathtub shaped failure rate function. Moments, skewness, kurtosis, moment generating function, characteristic function are derived. Renyi entroy, Lorenz curve and Gini index are obtained. Reliability of stress-strength model is derived. Distribution of maximum and minimum order statistics are obtained. We have obtained maximum likelihood estimators. A simulation study is conducted to illustrate the performance of the accuracy of the estimation method used. Application is illustrated using real data.
Productization and Product Structure: Extending The Perspective to Software Business

: Productization and product structure can be beneﬁcial for companies in various product-related considerations. The focus on software business and software products, however, has been deﬁcient. This study takes a speciﬁc software perspective to provide a software business perspective to productization discussion. Productization of software is considered by bringing different perspectives on the software product. Constructive, qualitative approach is used in studying the productization and software product structure of a case company. The empirical study reveals software-related challenges and shows how productization and product structure are beneﬁcial also with software business, including the Software as a Service (SaaS) business model. The results indicate that further focus on product structure and consistent productization logic is also necessary for software business. The basic principles of productization of physical products or services may remain the same, but some software business speciﬁcs must be addressed. Hence, software context may inﬂuence productization and product structure logic. Companies involved in the software business can beneﬁt from the improved understanding in managing their software offerings. Well productized software offering enables maintaining the scope of the software being developed and the operations of what is being sold, delivered, and invoiced. This study is among the ﬁrst to consider the productization concept, including product structure in the software business context to indicate the context speciﬁcs.
Hierarchical Fuzzy Method of Comparing Bank Products with Complex Tariff Packages

The article considers a method for solving an information asymmetry problem that is relevant for the banking sector. The authors compare bank products and services in which tariff packages are consist of different informational components. The principal feature of the proposed method is to focus on obtaining a subjective evaluation of the attractiveness of the Bank’s offers for specific target groups. This makes the proposed method relevant for Central and commercial banks, as well as for consumers of banking products. Since complex tariff packages of different banks contain not only many indicators but also different sets, it is impossible to directly compare them. The proposed method allows solving the main informational problems of traditional methods for comparing banking products. Using the Fuzzy Inference System (FIS) allows a flexible approach to the aggregation of singular indicators of tariff packages and simplifies the expert procedures. To make rules for fuzzy inference, linguistic constructions close to the natural language can be used. This makes it easier to fill the knowledge base. To solve the set tasks, a methodology for constructing hierarchical FIS is used. In comparison with non-hierarchical FIS it can reduce the requirements to the number of rules in fuzzy inference rule base and system implementation time. The experiments with the fuzzy inference system, which implements a corporate credit cards tariff packages comparison of four Ukrainian banks, showed the effectiveness of the proposed approach. The obtained numerical results are adequately interpreted for the highlighted groups of banking product consumers
IOT Based Smart Energy Meter for Domestic Use

: Internet of Things (IoT) has opened a myriad of applications in many areas, including medical and healthcare networks, smart home control, and environmental surveillance. IoT is supposed to bring about a large amount of progress within the ubiquitous computing sector. IoT-based energy management programs may allow a big contribution to energy conservation. Therefore, this paper focuses on the planning and implementation of an online of Things based household electricity energy monitoring and electric bulb remote for the reduction of electrical wastage using ESP 32-bit microcontroller. The ESP 32 microcontroller was used as the brain of the whole system which processes the energy consumption . The ESP32 microcontroller also handles the web connectivity via its inbuilt WIFI module so as to transmit the real-time energy consumption, and electric bulb remote control over the internet. A UBIDOS app was designed to serve as user interface for monitoring the household electricity energy consumption and electric bulb remote via UBIDOS cloud server from Math Works and also monitors the electricity consumed by the pressing iron and therefore the hand blower . Whenever, the electricity consumption exceeds the set threshold on the UBIDOS app, a notification is sent to the user’s Email. The system might be used for reducing the wastage of electricity within the house by proper scheduling and monitoring of the appliances.
For Some, Luck Matters More: the Impact of the Great Recession on the Early Careers of Graduates from Different Socio-Economic Backgrounds

*This work is based on data from the Destination of Leavers from Higher Education Survey and Higher Education Student Records held by the Higher Education Statistics Agency (HESA), the Labour Force Survey, Local Labour Market Statistics, and the Index of Multiple Deprivation produced by the UK Ofﬁce for National Statistics. The data are crown copyright and reproduced with the permission of the controller of the HMSO and Queen’s Printer for Scotland as well as the Higher Education Statistics Agency Limited. The use of the data in this work does not imply the endorsement of any of the organizations cited above in relation to the analysis or the interpretation of the results. Abstract This article uses variation in unemployment caused by the 2008 UK recession to analyse socio-economic gaps in graduate outcomes. Our data come from a survey that collects information on several cohorts of students from all English universities and reports their destinations at 6 months after graduation. The results show that, when graduating in a recession, students from less advantaged family backgrounds are more likely to become unemployed, to work part-time, and to earn less than students from more advantaged families. There is evidence that professional networks established while at university are important in explaining some of these socio-economic gaps in outcomes. JEL classiﬁcations: I24, I26, J23, J24
PUBLIC DEBT SUSTAINABILITY AND FISCAL CYCLICALITY IN BRAZIL: FACING THE FRACTIONAL INTEGRATION APPROACH Área 4: Macroeconomia, Economia Monetária e Finanças

This article contributed to the literature on fiscal rules applied to Brazil, as we found empirical evidence regarded as robust to long-memory in time series, in contrast with the most part of the published studies, which have adopted conventional unit root tests. We found evidence of a procyclical fiscal rule in Brazil, mainly after 2014, so that it diverged from the public debt sustainability principle developed by Bohn (1995; 2005). Moreover, using GMM regressions and an interaction term for the period marked by a higher fiscal stress, we also obtained evidence of expected inflationary effects as a result of lower fiscal cyclicality in Brazil.
Implementing Joint Scheduling Approach in Cloud Computing for Energy Optimization

—Cloud computing technologies have empowered a new-fangled paradigm for progressive product advancement by the establishment and contribution of services in a multi-tenant disseminated simulation environment. A joint scheduling and computation offloading (JSCO) is implemented to create mechanisms for generating optimal decision and forecasting[16]. A systematic framework for monitoring, analysing and improving system performance is proposed in this research. Resource augmentation provides computation resources for Users. Thus, offloading method in the private cloud involves only energy consumption during data transfer. On the other hand, offloading onto the public clouds involves energy consumption during data transfer and incurring monetary cost during resource utilization as well as data transfer. This approach adds the service occupier for matching virtual machines and allocates the same to physical host machines using heuristic approach. The Performance analysis of this offloading task determines the effectiveness of best-fit heuristic approach through virtual machines allocation to hosts by utilizing their capacity.
Moderating Effect of Organizational Culture on Relationship between Transformational Leadership and Human Capital: An Empirical Study on Public Sector of UAE

The importance of acquiring knowledge is to encourage creativity and innovation among employees which will not only result in changes in individuals and their behaviors, but also in organizations performance. In addition, leaders who invest in knowledge and training for their employees will have their skill level improved and raise their productivity than those who are less skilled. The study aims at evaluating the role of organizational culture between transformational leadership and human capital in the public sector in the UAE. Transformational leadership is the independent construct which is a second-order construct of idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. The dependent construct is human capital as a second-order construct of skills, whereas collectivism represents the organizational culture as a moderating variable. This study employs structural equations modeling via PLS to analyze the 307 valid questionnaires in order to assess the proposed model. Our work has improved our insight into the importance of transformational leadership and organizational culture. Results indicated that the independent variable significantly predicted human capital, in addition to collectivism having a significant moderating role between transformational leadership and human capital. Fifty three percent of variance is proposed by the current model in case of human capital.
F AST B INARIZED N EURAL N ETWORK T RAINING WITH P ARTIAL P RE - TRAINING

Binarized neural networks, networks with weights and activations constrained to lie in a 2-element set, allow for more timeand resource-efficient inference than standard floating-point networks. However, binarized neural networks typically take more training to plateau in accuracy than their floating-point counterparts, in terms of both iteration count and wall clock time. We demonstrate a technique, partial pre-training, that allows for faster from-scratch training of binarized neural networks by first training the network as a standard floating-point network for a short amount of time, then converting the network to a binarized neural network and continuing to train from there. Without tuning any hyperparameters across four networks on three different datasets, partial pre-training is able to train binarized neural networks between 1.26× and 1.61× faster than when training a binarized network from scratch using standard low-precision training.
Extraction of Text from an Image and its Language Translation Using OCR

:- — In our day to day life the people are facing many problems in understand the languages. For example, if the people move from one state to the other they don’t understand their language at that time this Mobile Application will help them. Existing system, having a separate application for each and every process like camera, Google translator and Optical Character Recognition(OCR) text scanner. But, people expect the application consists of all the three facilities together. So this proposed application provides a new idea to the people to translate the other language text into their known language. This application contains three steps. 1.Take a photo image of the unknown language text which you want to translate(either handwritten or printed material), 2.Tessaract is an open source Optical Character Recognition (OCR) technology, which is used to extract the text from the image then Google API and Bing API is used for translation of language. 3.The translated text is generated in PDF format.
I nvestigating the scarce data and resources problem for speech recognition using transfer learning and data augmentation

: We investigate the e ﬀ ect of the transfer learning procedure on e2e Automatic Speech Recognition systems using a limited amount of data. We use a DeepSpeech inspired base-line in our experiments and based on di ﬀ erent transfer learning techniques. Our experimental results indicate the beneﬁt of the augmented progressive transfer method in minimizing the over-ﬁtting and improving the accuracy.
Effects of Dialogue Meetings-Pre-analysis plan Phase 1*

Sickness absence entails large individual and societal costs. Dialogue Meetings (DMs) where the absentee, the employer, and often the physician, discuss arrangements for full or partial work resumption have been in place in Norway since 2007. In collaboration with the Norwegian Labour and Welfare Administration (NAV) we are conducting a large scale randomized natural field experiment to investigate if and for whom DMs have effects. The experiment is still ongoing and is conducted in several phases to test for mechanisms iteratively. While the experiment is still ongoing, it is possible to analyze data on the individuals that have already been involved in the experiment so far (early sample). To do so we proceeded as follows: first, we randomly divided the early sample into an early training sample and an early test sample. NAV then merged the early training sample with outcome data and covariates and handed the data over to us. Based on the results in the early training sample, we here register some key decisions that will be followed in analyzing the rest of the data (the analysis sample, which comprises the late sample and the early test sample). The results from the early training sample are presented in a companion document and will be subject to a direct replication using the early test sample. Based on the findings in the early test sample we will decide whether and how to change the intervention. Such changes will be pre-registered at a later stage.
A New Landmark Detection Approach for Slam Algorithm Applied in Mobile Robot

Simultaneous Localization and Mapping is a key technique for mobile robot applications and has received much research effort over the last three decades. A precondition for a robust and life-long landmark-based SLAM algorithm is the stable and reliable landmark detector. However, traditional methods are based on laserbased data which are believed very unstable, especially in dynamic-changing environments. In this work, we introduce a new landmark detection approach using vision-based data. Based on this approach, we exploit a deep neural network for processing images from a stereo camera system installed on mobile robots. Two deep neural network models named YOLOv3 and PSMNet were re-trained and used to perform the landmark detection and landmark localization, respectively. The landmark’s information is associated with the landmark data through tracking and filtering algorithm. The obtained results show that our method can detect and localize landmarks with high stability and accuracy, which are validated by laser-based measurement data. This approach has opened a new research direction toward a robust and life-long SLAM algorithm.
Auditee Satisfaction and Compliance: The Mediating Role of Perceived Service Quality concerning Malaysian SMEs

Audit firms must meet the needs of their auditees to achieve sustainable development. The paper aims to analyze the role of auditee satisfaction perceived service quality to affect the compliance variable in auditing service provided by SMPs to SMEs in Malaysia. Data collected via structured questionnaires through email communication. The collected data were analyzed first using descriptive statistics, followed by correlation analysis to establish the mediating effects of perceived service quality between the dependent and independent variables. Lastly, a regression analysis was borne on the model to test the hypotheses. The study found that auditee satisfaction correlates with perceived service quality, while both perceived service quality and auditee satisfaction were a significant relationship towards compliance. The study also showed that perceived service quality as a mediating role between auditee satisfaction and compliance was significantly based on SEM PLS analysis. The research findings are also imperative to scholars, academics, scientists, and researchers by adding to the body of current knowledge on internal audit and risk management. Nonetheless, its sample size limits the study. Therefore, the results do not represent the whole business organization because they determine Malaysian Smalls and Medium Enterprise, focusing only on retails and wholesales.