Miracle-dz/UniFAR-FTUs huggingface dataset:
A Secure Key for Cloud using Threshold Cryptography in Kerberos

In IT industry now a days there is a need for several new resources and storage requirement for terabyte of data generated every day. Cloud Computing is a solution for this in a cost effective manner. Cloud Computing provides on demand resources as services to client. Cloud is highly scalable, flexible and platform in dependable. Although it is benefiting the clients in several ways but as data is stored remotely it has many security loopholes like attacks, data loss, other authentication and security issues. In this paper an authentication model is proposed for cloud computing based on Kerberos protocol using threshold cryptography to provide more security and to increase the availability of key. This model can also benefit by filtering the unauthorized access and to reduce the burden of computation and memory usage of cloud provider against authentication checks for each client. It acts as a third party between cloud server and clients to allow authorized and secure access to cloud services. In this paper we will take a review of related work for cloud security issues and attacks. In next section we will discuss the proposed architecture and its working. Next we will see how it can provide better security and availability to key used for
The Commercial Banks Operational Risk Evaluation Based on EAHP and Gray Correlation

How to manage operational risk effectively has become a crucial point in commercial bank risk management. Based on the operational risk definition and supervision requirements in Basel capital accord ¿, adopted expanded AHP, this paper has constructed an operational risk evaluation indicator system which covers the influential factors inside and outside of banks. The specific evaluation steps are illustrated in the gray correlation evaluation model.
Report Technical 71 Advanced Event Correlation in Security Information and Event Management Systems

In this report, several open problems in current enterprise Security Information and Event Management systems, specifically with respect to their event correlation are discussed. An advanced event correlation using a special kind of soft pattern matching in conjunction with ontological background knowledge, Description Logic inference and a probabilistic post processing by Conditional Random Fields is proposed to address these problems. It is shown that this approach improves the detection accuracy by detecting even unknown incidents in contrast to currently applied rule-based correlations.
Preliminary results of a study of the completeness and clarity of structured abstracts

CONTEXT: Systematic literature reviews largely rely upon using the titles and abstracts of primary studies as the basis for determining their relevance. However, our experience indicates that the abstracts for software engineering papers are frequently of such poor quality they cannot be used to determine the relevance of papers. Both medicine and psychology recommend the use of structured abstracts to improve the quality of abstracts. AIM: This study investigates whether structured abstracts are more complete and easier to understand than non-structured abstracts for software engineering papers that describe experiments. METHOD: We constructed structured abstracts for a random selection of 25 papers describing software engineering experiments. The original abstract was assessed for clarity (assessed subjectively on a scale of 1 to 10) and completeness (measured with a questionnaire of 18 items) by the researcher who constructed the structured version. The structured abstract was reviewed for clarity and completeness by another member of the research team. We used a paired 't' test to compare the word length, clarity and completeness of the original and structured abstracts. RESULTS: The structured abstracts were significantly longer than the original abstracts (size difference =106.4 words with 95% confidence interval 78.1 to 134.7). However, the structured abstracts had a higher clarity score (clarity difference= 1.47 with 95% confidence interval 0.47 to 2.41) and were more complete (completeness difference=3.39 with 95% confidence intervals 4.76 to 7.56). CONCLUSIONS: The results of this study are consistent with previous research on structured abstracts. However, in this study, the subjective estimates of completeness and clarity were made by the research team. Future work will solicit assessments of the structured and original abstracts from independent sources (students and researchers).
A queueing analytical model for service mashup in mobile cloud computing

In this paper, we present a modeling technique of using Jackson's network theorem to characterize the performance of mashup multiple servers in cloud computing environments. The key challenge in providing new mashup mobile applications in cloud computing, such as the real-time location-based services, is to evaluate the overall delay resulting from integrating multiple cloud servers. Furthermore, the number of virtual machines (VM) will affect the quality of service (QoS) for mobile applications with various traffic loads. However, an effective analytical model to characterize both the effects of integrating multiple cloud servers and scalable VMs is rarely seen in the literature. The proposed multi-cloud mashup analytical model can calculate the service waiting time for various numbers of VMs and different arrival rates. Through simulations and analysis, we show that for various numbers of VMs and traffic loads, the proposed model can accurately predict the breakpoint where the waiting time in mashup cloud servers will sharply increase. Hence, the proposed mashup multi-cloud analytical model can facilitate the management of resource in future cloud data centers.
Personality Traits, Perceived Risk, Uncertainty, and Investment Performance in Vietnam

The study explored the impact of personality traits, perceived risk, and perceived uncertainty on investment performance of individual investors trading on the Vietnam stock market. The study conducted in-depth interviews, a pilot study, and a survey distributed to 430 individual investors. Results showed that Conscientiousness and perceived uncertainty directly affected investment performance. Openness, Extraversion, and Neuroticism indirectly influenced investment performance through the mediation of perceived uncertainty. This study suggested that individual investors should perceive uncertain situations when they invest in securities. Especially, investors who are prone to Openness, Extraversion, and Neuroticism must pay attention to uncertainty before they make investing decisions. Since Agreeableness did not affect investment performance, those who are dominant to this trait should have prudent considerations for equity investment decisions.
Qce: a Simulator for Quantum Computer Hardware *

The Quantum Computer Emulator (QCE) described in this paper consists of a simulator of a generic, general purpose quantum computer and a graphical user interface. The latter is used to control the sim-ulator, to define the hardware of the quantum computer and to debug and execute quantum algorithms. QCE runs in a Windows 98/NT/2000/ME/XP environment. It can be used to validate designs of physically realizable quantum processors and as an interactive educational tool to learn about quantum computers and quantum algorithms. A detailed exposition is given of the implementation of the CNOT and the Toffoli gate, the quantum Fourier transform, Grover's database search algorithm, an order finding algorithm, Shor's algorithm, a three-input adder and a number partitioning algorithm. We also review the results of simulations of an NMR-like quantum computer.
Cross-generation Elites Guided Particle Swarm Optimization for large scale optimization

Elites have been widely used in many evolutionary algorithms. However, only elites in current generation are utilized to guide the learning/updating of particles/individuals in existing algorithms. Usually, elites in different generations are different and elites in the past generations may contain experienced knowledge and thus may be helpful for guiding particles/individuals to promising areas. Inspired from this, we propose a Cross-generation Elites Guided Particle Swarm Optimizer in this paper. Specifically, the swarm in current generation is divided into two separate sets: the elite set containing the top best particles and the non-elite set consisting of the rest particles. Since these elite particles are the most promising ones in the current generation, we remain these elites unchanged and let them directly enter next generation. Then the rest non-elite particles are updated through learning from elites in both the current generation and the last generation. Through this, a potential balance between exploration and exploitation can be achieved. Particularly, the proposed algorithm is applied to deal with large scale optimization, which is very challenging and difficult and has received a lot of attention in recent years. Extensive experiments are conducted on two sets of large scale benchmark functions and experimental results verify the competitive effectiveness and efficiency of the proposed algorithm in comparison with several state-of-the-art large scale evolutionary algorithms.
Analytical Modeling of Switching Energy of Silicon Carbide Schottky Diodes as Functions of dI $_{\bf DS}$/dt and Temperature

SiC Schottky Barrier diodes (SiC SBD) are known to oscillate/ring in the output terminal when used as free-wheeling diodes in voltage-source converters. This ringing is due to RLC resonance among the diode capacitance, parasitic resistance, and circuit stray inductance. In this paper, a model has been developed for calculating the switching energy of SiC diodes as a function of the switching rate (dIDS/dt of the commutating SiC MOSFET) and temperature. It is shown that the damping of the oscillations increases with decreasing temperature and decreasing dIDS/dt. This in turn determines the switching energy of the diode, which initially decreases with decreasing dIDS/dt and subsequently increases with decreasing dIDS/dt thereby indicating an optimal dIDS/dt for minimum switching energy. The total switching energy of the diode can be subdivided into three phases namely the current switching phase, the voltage switching phase, and the ringing phase. Although the switching energy in the current switching phase decreases with increasing switching rate, the switching energy of the voltage and ringing phase increases with the switching rate. The model developed characterizes the dependence of diode's switching energy on temperature and dIDS/dt, hence, can be used to predict the behavior of the SiC SBD.
Involving People with Lived Experience of Homelessness in Electronic Health Records Research

ABSTRACTObjectivesWe held a public engagement workshop to involve people with lived experiences of homelessness and social exclusion, experts by experience (EBE), in our research. The purpose of the workshop was to provide context to the findings of a review series on Inclusion Health and to inform future research using electronic health records (EHRs) of homeless and socially excluded people. ApproachParticipants included 16 volunteers and one staff member from Groundswell (a registered charity that promotes inclusive solutions to homelessness), four academics, one clinical provider, and two note-takers/photographers. The full-day workshop was held at University College London. We used innovative participatory activities specifically designed for use with hidden and marginalised populations to stimulate open dialogue. Methods included general discussion, conceptual mapping, modelling, electronic voting, brainstorming, ranking, graphing, stakeholder analysis, and evaluation surveys. Activities were fast-paced and conducted in small groups, as the whole group, individually, or in pairs. The meaning of Inclusion Health, barriers that lead to exclusion, and values and actions that promote inclusion were discussed. Health statistics on homeless and other socially excluded groups were presented and informed conversations about EHR research, including data collection (new data versus collation of administrative data), data linkage, consent, anonymisation, data security, and ‘the surveillance society. ’ ResultsNotes from the workshop and the evaluation surveys indicated that the workshop was engaging, inclusive, and successful. When clearly explained, EBE were positive towards research using EHRs to improve Inclusion Health, including data linkage of sensitive health and social data. EBE expressed that housing, advocacy, and psychosocial therapies were the most important interventions for improving health of people who are homeless; however, we found limited evidence for these interventions in our review. Overall, findings demonstrate the value of involving the people who have been socially excluded to develop research priorities and to interpret findings. ConclusionUsing a participatory and dynamic approach to involve people with lived experience of homelessness and exclusion is an effective public engagement methodology for complex topics such as EHR research and data linkage. Information provided in the workshop was useful for interpreting findings, identifying strengths and gaps in health and social services, and developing research and practice recommendations.
An alternative voltage and frequency monitoring scheme for SCADA based communication in power system using data compression

Conventionally in SCADA based system used in power system, voltage & frequency is monitored sequentially at regular intervals by employing suitable communication schemes. By suitable data compression techniques, it is possible to compress the measured voltage & frequency data to a reduced single string which is then transmitted to monitoring / control room. At the receiving end, the necessary data can be extracted from the transmitted string by using the respective decompression technique. A MATLAB based system is developed which can produce the compressed string corresponds to input voltage & frequency which can be decoded to obtain the voltage & frequency at the receiving end.
From 1984 to Birch: The Politics of Cultural and Traditional Arts/Games in the Plays of Kee Thuan Chye

Malaysian playwright Kee Thuan Chye's plays such as 1984 Here and Now, The Big Purge and We Could **** You, Mr. Birch have always placed Malaysian politics as their centre stage discourse. Through his plays, Kee provides an intimate glimpse of Malaysian politics and the individual who struggles to make meaning out of the drudgery of the power struggle between the state and the individual. While Kee's focus, as Gilbert and Lo suggest in their 'Introduction to 1984 Here and Now', has been on how 'existing hegemonic power structures perpetuate gross inequalities in the Malaysian society', he has also touched on the social relations between communal groups that were discriminated against by race-based policies of the National Economic Policy (NEP). This paper takes a deeper look at the meaning of cultural/traditional recreational activities depicted in three of Kee's political plays, arguing that activities are not mere social activities but a manifestation of a deeper network of symbolisms and the politics of representation and dissent against the hegemony of the political state.
The Princeton Variability Survey

The Princeton Variability Survey (PVS) is a robotic survey that makes use of readily available “off‐the‐shelf” type hardware products, in conjunction with a powerful set of commercial software products, in order to monitor and discover variable objects in the night sky. The main goal of the PVS has been to devise an automated telescope and data reduction system requiring only moderate technical and financial resources to assemble, which may be easily replicated by the dedicated amateur, a student group, or a professional and used to study and discover a variety of variable objects, such as stars. This paper describes the hardware and software components of the PVS device as well as observational results from the initial season of the PVS, including the discovery of a new bright variable star.
An A* Based Semantic Tokenizer for Increasing the Performance of Semantic Applications

Semantic Applications (SAs) makes use of ontologies and their performance can depend on the syntactic labels of the modeled entities, even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A based search algorithm, the A functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.
Disability and Sport: (Non)Coverage of an Athletic Paradox

In sit volleyball, the players pivot and lunge, dive and spike, many of them with legless torsos supported by strong. agile arms. There's also wheelchair rugby, which sounds like a controdiction in terms until you see it. It's the down-and-dirty wheelchair sport, the roughest and most aggressive of them all. The players-all quadriplegics-crash and smash it up in the rugby tradition, though the game is played in a gym. Think rugby by way of bumper cars. -Sportsjones.com (2001, August 24, para. I)
A New Edge Detection Method Based on Threshold Binarization

The most fundamental features of a digital image are the edges of objects. The edge detection method’s reliability and accuracy will affect directly on the comprehension machine vision system. Several edge detectors have been developed in the past decades as Sobel and Canny. Although no single edge detector has been developed satisfactorily enough for all applications. In this paper, a new edge detection method is proposed based on the threshold binarization using multiple methods as BP_MLP neural network and Boolean algebra. Based on this method, the edge patterns of binary images are classified into 16 possible types of visual patterns. Experimentally results demonstrate improving in the computations mass and mathematical complexity in comparison with the traditional edge detection methods.
Sensitivity of cancellation algorithm to transmitted waveform in noise radar system

The sensitivity of clutter cancellation algorithm to transmitted signal waveform, which mainly focus on the noise frequency-modulated continuous-wave (FM-CW) and noise frequency-modulated pulse-wave (FM-PW) in noise radar system is investigated in this paper. Based on the concept of cross-ambiguity function, the consequence of clutter cancellation can be observed visually. Comparing FM-CW and FM-PW, the former and the latter have similar convergence speed and cancellation ratio for fixed cancellation algorithm. However, they are both sensitive to different cancellation algorithms, like frequency-domain least-mean-square (FBLMS), adaptive lattice filter algorithm. Concerning the convergence speed and cancellation ratio, the corresponding simulation experiments are implemented. The characteristic obtained from this paper can be applied to other FM-CW and FM-PW pseudo-random sequence.
Modeling, design & characterization of a novel Passive Variable Stiffness Joint (pVSJ)

In this paper we present the design and characterization of a novel Passive Variable Stiffness Joint (pVSJ). pVSJ is the proof of concept of a passive revolute joint with controllable variable stiffness. The current design is intended to be a bench-test for future development towards applications in haptic teleoperation purposed exoskeletons. The main feature of the pVSJ is its capability of varying the stiffness with infinite range based on a simple mechanical system. Moreover, the joint can rotate freely at the zero stiffness case without any limitation. The stiffness varying mechanism consists of two torsional springs, mounted with an offset from the pVSJ rotation center and coupled with the joint shaft by an idle roller. The position of the roller between the pVSJ rotation center and the spring's center is controlled by a linear sliding actuator fitted on the chassis of the joint. The variation of the output stiffness is obtained by changing the distance from the roller-springs contact point to the joint rotation center (effective arm). If this effective arm is null, the stiffness of the joint will be zero. The stiffness increases to reach high stiffness values when the effective arm approaches its maximum value, bringing the roller close to the torsional springs' center. The experimental results matched with the physical-based modeling of the pVSJ in terms of stiffness variation curve, stiffness dependency upon the springs' elasticity, joint deflection and the spring's deflection.
A view-dependent, polyhedral 3D display

In this paper, we present the design and construction of a simple and inexpensive 3D display made up of polygonal elements. We use a per-pixel transformation of image and depth to produce accurate picture and depth map on an arbitrary planar display facet from any viewpoint. Though the facets are rendered independently, the image and depth for rays from the eye-point through the facet pixels is produced by our method. Thus, there are no artifacts on a facet or at facet boundaries. Our method can be extended to any polygonal display surface as demonstrated using synthetic setups. We also show a real display constructed using off-the-shelf LCD panels and computers. The display uses a simple calibration procedure and can be setup in minutes. Frame-sequential and anaglyphic stereo modes can be supported for any eye-orientation and at high resolutions.
Predicting Transcription Factor Complexes Using Similarities in Genomic Motifs

With the completion of the Human Genome Project in 2001, researchers believed this revolutionary effort would rapidly lead to a deluge of biomedical advances. However, our improvements in understanding complex disease mechanisms and inventing new therapeutics have been limited, falling short of lofty expectations. It has become increasingly clear that knowing only the sequence of one’s DNA is insufficient to capture the underlying biology. Every cell in the human body has the same genomic DNA, but each cell utilizes a different subset of the DNA to perform different functions across the body. As such, understanding gene regulation, or how cells select different parts of the genome to use, is key to understanding human developmental biology and human diseases[1]. Gene regulation is known to be an interplay of accessible DNA sequences with regulatory proteins, known as transcription factors (TFs)[2]. In particular, the identity and function of a cell is very reliant on enhancers and promoters, which are regions of regulatory DNA that do not code for proteins but influence the expression of other genes. Promoters initiate transcription of downstream genes whereas enhancers stimulate the rate of transcription, and the two work together in concert to regulate gene transcription. Specifically, these DNA elements influence nearby genes by binding TFs which then act as repressor or activator switches on nearby genes. This binding is specific because of sequence patterns, known as DNA motifs, which are selective for specific regulatory proteins. As such, there is a combinatorial logic encoded in DNA sequences which give hints as to which TFs and in what combinations lead to downstream effects on a cell. In other words, gene regulation is based on proteins forming complexes based on the DNA sequence they’re binding to, which then leads to tissue-specific function. The interactions between promoters and enhancers have a natural and intuitive network representation, where regulatory elements are nodes, and an undirected edge exists if the elements share