Miracle-dz/UniFAR-FTUs huggingface dataset:
A STUDY OF FREEZE-FRAME FILE SYSTEM WITH TAMPER-RESISTANT FRAMEWORK

: In recent days, different applications process data sources in due course, arguing that existing solutions do not fulfill the criteria and introduce our newly developed Cornell University Freeze-Frame File System (FFFS). The tool is swift and secure: we store all background improvements to a memory mapping disk, recently download cache data for repeat readings, and we use a robust mix of real-time and logical clock for managing read querying that are both briefly accurate and causal. When RDMA is accessible, the writing and reading bandwidth of a single client is approximate to 2.6GB / s in writing, and 5GB / s in reading, similar as the RDMA equipment limit (about 6GB /s). Data security will be a big issue for the Hadoop private data storage. A plethora of modules are still secure and chosen to resolve ambiguities for high productivity of FFFS by data duplication and reproduction of fault tolerances and redundancy methods. This assumption may be unfounded with risks and intrusions. An attacker can harm many copies of a service that trigger a mistaken sense of security. The kernel-based approaches have proved effective, but they only fail if code improvements are necessary. In this paper, we suggest a robust user space set of process management techniques that can monitor user space daemons objectively having no major impact on performance. A device that attempts to execute such a task should be tamper-resistant.
P4 Language and Programmable Data Planes

To support the ever-growing application demands for high bandwidth, low latency, and high availability, the underlying network architecture has gone through several changes. For instance, in the 5G context [1], we have access-edge networks providing services at the edge and the edges are connected over core networks to talk to their counterparts in the cloud. If we go a bit low-level, the infrastructure behind these novel architectures is also changing fundamentally. Increasingly, many network functionalities are disaggregated and the functions that were traditionally running on special-purpose proprietary hardware targets are now running on generalpurpose commodity hardware such as CPUs, SmartNICs [2], [3], [4], [5], [6], and high-speed programmable whitebox switches [7].
Correlates of Expressed Emotions Among Caregivers of Patients With Bipolar Disorder: A Cross Sectional Study

Bipolar disorder is a disabling psychiatric illness with a high rate of recurrence, persistent symptoms, and impairment in functioning. The shift from institutional care to community-based care has resulted in the transferring of day-to-day care of patients to their family members, resulting in a psychosocial burden over the caregivers. Hence, Bipolar disorder not only affects the patient but also has a huge impact on the lives of the persons caring for them. This study has been undertaken to correlate Expressed Emotions among caregivers of patients with Bipolar Disorder for which cross-sectional study was conducted at a tertiary care teaching hospital in north India. The study sample comprised of 100 patients with BD. Convenient sampling was used for the selection of patients with Bipolar disorder and their caregivers and statistical analysis. Bivariate and Multivariate analysis analysis was used. The result of the present study indicate that higher use of maladaptive coping has a significant impact on the Expressed Emotion. Accordingly, psychosocial interventions need to focus on caregivers to reduce Effective Emotion.
Pre-print Statement for 1 “ Fe 5 S 2 identified as a host for sulfur in Earth and 2 planetary cores ” 3

Claire C. Zurkowski , Barbara Lavina, Abigail Case, Kellie Swadba, Stella Chariton, 4 Vitali B. Prakapenka, Andrew J. Campbell 5 6 The University of Chicago, Department of the Geophysical Sciences, 5734 S Ellis Ave, Chicago, IL 60637, USA 7 Center for Advanced Radiation Sources, The University of Chicago, 9700 South Cass Avenue, Lemont, IL 60439, 8 USA 9 X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, IL 60439, USA 10 Now at Earth and Planets Laboratory, Carnegie Institution for Science, 5251 Broad Branch Road, NW, 11 Washington, DC 20015, USA 12 13 14 Corresponding Author: Claire Zurkowski, czurkowski@carnegiescience.edu 15 16 Dear Earth Arxiv, 17 This manuscript is a non-peer reviewed preprint submitted to EarthArXiv. It has been 18 submitted for peer review at Earth and Planetary Science Letters. 19 20 21 Sincerely, 22 Claire Zurkowski 23
ENSEMBLE SELECTION AND COMBINATION BASED ON COST FUNCTION FOR UCI DATASETS

It is well-known that the classification performance of any single classifier is outperformed by a multiple classifier approach or an ensemble process that incorporates results from different base classifiers. However, even though they have the potential to achieve greater classification precision, their vast number of base classifiers has greatly influenced ensemble methods. In the ensemble process, the selection and combination of appropriate and varied classifiers is a daunting task. In the previous work, we, therefore, suggested a new soft ensemble selection and combination approach (SSSC) to identify the best subset of heterogeneous ensemble team of classifiers and demonstrated the potential of our proposed algorithm to minimise a large number of classifiers while at the same time generating the highest predictive precision for consumer churn data sets. This paper extended the earlier work with the goal of evaluating whether the proposed SSSC model works well with the other UCI repository benchmark data sets. The findings of the experiments demonstrated that the developed model resulted in the improvement of the chosen UCI data sets' prediction accuracy. Based on the results of the experiments, it indicates that the prediction accuracy of the proposed SSSC outperformed other single classifiers and ensemble methods for Liver Disorder, Hepatitis and Breast Cancer data sets. This work has shown that the proposed SSSC is able to search for a minimal number of classifiers in the repository of the ensemble while at the same time enhancing the precision of the classification of the chosen UCI data sets.
FACTORS AFFECTING CUSTOMERS’ SATISFACTION BASED ON ATM CARD PAYMENT SERVICES: A CASE STUDY OF VIETCOMBANK

Nowadays, digital technology development and cash in payments are decreasing gradually and replacing electronic payments such as Automated Teller Machine (ATM). ATM is a new payment method; electronic payment has the power to develop relatively quickly in many different ways. The introduction of an electronic payment method reduces the pressure on the circulation of cash in the market, making payments and transactions more convenient, saving costs and time for people and the economy. The authors surveyed 450 customers related to electronic payment service from January 2020 to May 2020. The research results showed that seven factors affect customers' satisfaction based on ATM card payment services at Vietcombank in Dong Nai province. Research results are crucial scientific evidence for banking service managers to improve electronic payment services, especially ATM cards.
T-TSP: Transient-Temperature Based Safe Power Budgeting in Multi-/Many-Core Processors

Power budgeting techniques allow thermally safe operation in multi-/many-core processors while still allowing for efficient exploitation of available thermal headroom. Core-level power budgeting techniques like Thermal Safe Power (TSP) have allowed for more efficient operations than chip-level power budgeting techniques like Thermal Design Power (TDP) since the liner granularity permits operations closer to the threshold temperature without thermal violations.State-of-the-art TSP bases its power budgeting calculations on the long-term steady-state temperature of cores while ignoring trends in their short-term transient temperature. In this paper, we propose a new power budgeting technique called T-TSP (Transient-Temperature-based Safe Power) that bases its calculation on the current temperature of the core, a detail ignored by TSP. T-TSP provides a dynamic power budget to a core, which inversely correlates with the core’s thermal headroom. Dynamic power budgeting with T-TSP allows cores to reach the threshold temperature faster than TSP and operate safely close to it in perpetuity. Therefore, it provides the same thermal guarantees as TSP but enables even more efficient exploitation of thermal headroom.We integrate T-TSP with a state-of-the-art thermal interval simulation toolchain. Our detailed evaluations show that benchmarks execute faster by up to 17.94% and 8.37% on average when we do power budgeting with T-TSP instead of the state-of- the-art TSP. Finally, we make T-TSP publicly available in both its integrated and stand-alone forms.
A NOTE ON SAMPLING ERRORS IN THE RAINFALL AND RUNOFF DATA COLLECTED USING TIPPING BUCKET TECHNOLOGY

Data precision for rainfall intensity and runoff rate using tipping bucket technology is controlled by the bucket volume, V, the catchment area, A, and the sampling interval, t. The maximum absolute error is less than V(A.t)–1 and the standard error is given by V(v _ 6 A.t)–1, both of which are independent of the magnitude of rainfall intensity and runoff rate being measured. Therefore, the relative error can be quite large during events with low rainfall intensity or runoff rate. The magnitude of the sampling error given above can be used to assist in experiment and equipment design and in data analysis.
Political connections and strategic choices of emerging market Political connections and strategic choices of emerging market firms: Case study of Russia’s pharmaceutical industry firms: Case study of Russia’s pharmaceutical industry

Title: Abstract Purpose – Investigation of the importance of political connections in the emerging market context. Design/methodology/approach – Case study analysis of three Russian pharmaceutical firms is analyzed to uncover how they performed through the Russian transition–the institutional upheaval of the 1990s and the ongoing state-led industrialization. Findings – In the early years of transition, firms heavily rely on political networking to gain legitimacy and fill institutional voids. As institutions strengthen, the need for political networking is being substituted by arms-length networking. Strengthening of institutions also results in a more stable business environment, evolving firms’ strategies from short-term core competency concentration to long-term innovative visions. Research implications – Firms operating in the Russian, Commonwealth of Independent States (CIS) and some other Eastern European state domains must be wary of complex ties that are prevalent in these countries and often can assist or hinder firm performance. Although formal institutions strengthen arms-length networks, close cooperation between strategic firms and the state remains. Originality/value – The paper proposes two phases of the Russian transition and provides a taxonomy of strategic choices of Russian firms during the transition. Further, the paper describes the key institutional developments in the two phases of the Russian transition. Finally, a framework of political connections and their role in business operations in the two phases of the transition is provided.
Multi-View Representation Learning via Total Correlation Objective

Multi-View Representation Learning (MVRL) aims to discover a shared representation of observations from different views with the complex underlying correlation. In this paper, we propose a variational approach which casts MVRL as maximizing the amount of total correlation reduced by the representation, aiming to learn a shared latent representation that is informative yet succinct to capture the correlation among multiple views. To this end, we introduce a tractable surrogate objective function under the proposed framework, which allows our method to fuse and calibrate the observations in the representation space. From the information theoretic perspective, we show that our framework subsumes existing multi-view generative models. Lastly, we show that our approach straightforwardly extends to the Partial MVRL (PMVRL) setting, where the observations are missing without any regular pattern. We demonstrate the effectiveness of our approach in the multi-view translation and classiﬁcation tasks, outperforming strong baseline methods.
Bi-objective Trade-off with Dynamic Barrier Gradient Descent

Many machine learning tasks have to make a trade-off between two loss functions, typically the main data-ﬁtness loss and an auxiliary loss. The most widely used approach is to optimize the linear combination of the objectives, which, however, requires manual tuning of the combination coefﬁcient and is theoretically unsuitable for non-convex functions. In this work, we consider constrained optimization as a more principled approach for trading off two losses, with a special emphasis on lexicographic (lexico) optimization , a degenerated limit of constrained optimization which optimizes a secondary loss inside the optimal set of the main loss. We propose a dynamic barrier gradient descent algorithm which provides a uni-ﬁed solution of both constrained and lexicographic optimization. We establish the convergence of the method for general non-convex functions. Through a number of experiments on real-world deep learning tasks, we show that 1) lexico optimization provides a tuning-free approach to incorporating side loss functions without hurting the main objective, and 2) constrained and lexico optimization combined provide an automatic approach to proﬁling Pareto sets, especially in non-convex problems on which linear combination methods fail.
Reducing the high frequency transformer losses in an FB ZVT PWM converter

This paper proposes a full bridge zero voltage transition (FB ZVT) PWM DC-DC converter, which uses a saturable reactor, instead of two additional switches to achieve zero voltage switching. A conventional, high frequency, phase shifted, FB ZVT PWM DC-DC converter has a disadvantage, in that a circulating current flows through the high frequency transformer and switching devices during the free-wheeling interval. Due to this circulating current, the conduction loss increases. To reduce this loss, the proposed circuit reduces the circulating current. The operation principles are explained in detail and several interesting simulation and experimental results verify the validity of the proposed circuit.
Controllable Paraphrase Generation with Multiple Types of Constraints

One of the current challenges in paraphrase generation is the ability to enforce linguistic constraints on the desired output. These constraints may relate to the length of the output sentence, its syntactic structure, the presence of speciﬁc words, etc. While recent works focus on these constraints in isolation, this paper studies a variety of constraints imposed separately or in combination with one another. These constraints include different linguistic factors (surface words, syntax and semantics) of the input sequence or output sequence or both, and different data shapes (scalar value, sequence and tree). These constraints are integrated in a paraphrase generation process using an attention-based encoder-decoder model trained and experimented on the ParaNMT-50M corpus. The results show that the constraints are well respected by the models and that they allow to improve the quality of the produced paraphrases. This multiple constraint-driven model opens a new window for controllable paraphrase generation. The code is publicly available 2 .
ENHANCED TEXT LINE SEGMENTATION AND SKEW ESTIMATION FOR HANDWRITTEN KANNADA DOCUMENT

Abstract. When Handwritten Kannada document undergoes text line segmentation, the process is referred to as Text line segmentation and skew correction. This is quite essential for the HCRS (Human Character Recognition System). The process of text line segmentation and skew estimation tends to be quiet challenging during document analysis. The proposed system presents improvised text-line segmentation along with skew estimation for which the handwritten Kannada document forms the dataset. Following are the three methods for carrying out preprocessing, namely: (i) filtering (ii) gray scale conversion and (ii) Binarization. The ESLD (Enhanced Supervised Learning Distance) algorithm is being adopted for the assessment of distance amidst text lines and G_Clustering aids in grouping of words or the Connected Components. Also, by computing skew angle with respect to the gap, Skew estimation can be performed. It’s elucidated from the output that the proposed system exhibits higher performance.
Pharmacotherapeutic Strategies to Treat or Prevent OFF Episodes in Adults with Parkinson's disease

Parkinson’s disease is a chronic, neurodegenerative disease which manifests with a mixture of motor, cognitive and behavioral symptoms. Levodopa is the most effective antiparkinsonian treatment to date, although chronic use engenders a mixture of complications in a substantial proportion of patients. Amongst these is the occurrence of episodes of worsening symptoms‘off’ phenomenon. Although preventative measures are poorly evidenced, methods to improve Levodopa bioavailability and delivery to the brain are currently available and of value in addressing these episodes once they have become established. This review summarizes the clinical manifestations of ‘off’ phenomena and the current approaches to treat them. Although we briefly discuss clinical advances on the horizon, the predominant focus is on existing, established treatments.
Entrepreneurial Intention and the Moderating Role of Gender Evidence From Ipmi International Business School In Jakarta

Despite having the highest contribution to Indonesia GDP, the ratio of an entrepreneur to total population is only 1,7% compared to our neighbor countries Women entrepreneurs make up the majority of the founders of medium-small and enterprises, and there is a clear gap between the younger (under 35) and older generations (over 35). The study aims to investigate the intention to become an entrepreneur in the young generation in higher education and to analyze the re of gender in the relationship between entrepreneurial intention and personal attitude, subjective norms, and perceived behavioral control. This study develops a framework cross-sectional time frame in IPMI International Business School. The result demonstrates that the mean value of entrepreneurial intention was high, and there is a positive and significant effect between perceived behavioral control, personal attitude, and entrepreneurial intention. Surprisingly the subjective norms did not have a positive significant impact on entrepreneurial intention. The result indicates that students’ intention is high and gender moderated the relationships between entrepreneurial intention and persona attitude, and subjective norms, however, there is no significant effect between subjective norms and entrepreneurial intention This study fills a gap in the entrepreneurship body of knowledge by providing evidence gender moderates the relationship between personal attitude and entrepreneurial intention and between perceived behavioral control and entrepreneurial intention. This study is an empirical study that uses a SmartPLS3 with data taken from the Entrepreneurial Intention And . 706 p-ISSN : 2685-9106 e-ISSN : 2686-0384 ADI International Conference Series survey of 74 students in IPMI Business School in Jakarta. The study suggests that students in universities have high intention to become an entrepreneur, and the school can gain the highest entrepreneurial intention by introducing the innovative method in teaching entrepreneurship, especially to women.
Investigation of voltage-mode controller for cascade boost converter

The regulation of a 2-stage cascade boost converter using a voltage-mode controller is investigated. The approximate stability analysis of the voltage-controlled cascade boost converter is performed by using the state-space average model of the converter and some stability results are obtained. A comparative study of the conventional proportional and integral controller and the proposed voltage-mode controller shows that the latter is suitable for the regulation of the cascade converter. Experimental results showing the features of the controller in the presence of the load and the reference voltage changes are also provided.
Minimal hepatic encephalopathy – diagnosis and treatment

Hepatic encephalopathy is a dysfunction of the central nervous system caused by chronic and acute liver disease. It presents a wide spectrum of symptoms from undetectable in a standard clinical examination to hepatic coma. The mildest form of hepatic encephalopathy is minimal hepatic encephalopathy. It significantly influences the quality of life, prognosis, and the incidence of complications. A wide range of psychometric and neurophysiological tests are used in the diagnostics. Treatment is based on the same principles as in overt encephalopathy. The most commonly used drugs include rifaximin, ornithine aspartate, and LOLA.
Characteristics Analysis of Short Flux-path 4/3 SRM

Abstract – This paper presents a design and characteristics analysis of novel 2-phase 4/3 switched reluctance motor (SRM) with short flux path for an air-blower application. The desired air-blower is unidirectional application, and requires a wide positive torque region without torque dead-zone. In order to get a wide positive torque region without torque dead-zone during phase commutation, asymmetric inductance characteristic with non-uniform air-gap is considered. The proposed motor could be started at any rotor position with high efficiency drive. The proposed 2-phase 4/3 SRM is verified by finite element method analysis. Keywords: Switched reluctance m otor,Short magnetic flux -path , Twophase4/3poleSRM 1. Introduction Recently, high speed drives are much interested in the industrial applications to reduce the system size and to increase the drive efficiency. Especially, blowers, compressors, pump and spindle drives are suitable for the high speed motor drives, and the demand for the high speed motor system is much increased according to the industrial market. Some types of electric motor such as DC, permanent magnet and reluctance motor have been researched. SRM has simple structure and inherent mechanical strength without rotor winding and permanent magnet. These mechanical structures are suitable for harsh environments and high temperature and high speed applications
A new impedance sensor for wind instruments

Our aim was to build a low cost but accurate portable impedance sensor. The adopted technique is the one using a source with a back cavity. A first elctret microphone on the front of the source measures the pressure at the input of the instrument weather a second one measures the pressure in the cavity, which is proportional to the volume flow supplied by the source. By choosing a sufficiently small sealed cavity and a small piezoelectric source the system do not exhibit any cut‐off frequency in the measurement range. The calibration is then simplified and only few parameters are needed to model the three complex calibration functions. This calibration is performed with three nonresonant calibration loads. Moreover, it is shown that the geometry of the sensor being known, the measurement with a rigid wall is sufficient to calibrate the sensor. Results show that it is possible to achieve a measurement with an accuracy lower than 1dB in the range 50‐4000 Hz.