Miracle-dz/UniFAR-FTUs huggingface dataset:
Authentication and Authorization of End User in Microservice Architecture

As the market and business continues to expand; the traditional single monolithic architecture is facing more and more challenges. The development of cloud computing and container technology promote microservice architecture became more popular. While the low coupling, fine granularity, scalability, flexibility and independence of the microservice architecture bring convenience, the inherent complexity of the distributed system make the security of microservice architecture important and difficult. This paper aims to study the authentication and authorization of the end user under the microservice architecture. By comparing with the traditional measures and researching on existing technology, this paper put forward a set of authentication and authorization strategies suitable for microservice architecture, such as distributed session, SSO solutions, client-side JSON web token and JWT + API Gateway, and summarize the advantages and disadvantages of each method.
Data Analytics in a Data- and Hardware-Conscious Way

In recent years, we have seen large growth in the volume of data, and users are seeking faster and more accurate answers to their queries. The market for data analytics is also increasing steadily and is projected to reach a hundred billion dollars in the near future. Therefore, there exists a big economic incentive to come up with efficient data analytics systems or algorithms. At the same time, Moore’s law is driving the architectural advances of shared memory multiprocessors. Machines are becoming larger, with many homogeneous cores; machines with heterogeneous cores are already in the market. In fact, several reports suggest that future processors will have cores with programmable logic which can be used as an accelerator. In light of this, it is very important to (re-)visit data analytics problems, taking architectural advances into account, to develop the best-performing solutions. In this thesis, we present the results of work done on several core data-analytics problems, namely, approximate frequent item counting, frequency estimation, stream join, and execution of database join and aggregation. We demonstrate that careful utilization of architectural features on modern multi-core machines and workload characteristics lead to new algorithms with orders of magnitude better performance than state-of-the-art solutions for these problems. To design these new algorithms, we have used three well-known principles that are predominant in dataand hardware-conscious algorithms. These design principles are filtering skewed data, mapping dataflow with pipeline parallelism, and reducing data movement between main memory and caches. This thesis highlights our algorithmic contributions, while pointing out how we have used these design principles to guide our solutions. Data skew is an important workload characteristic. In many cases, skew creates a performance bottleneck for task parallelism, through load imbalance. If the common use cases for a particular problem include skewed distributions, providing a shortcut code path for the skewed items leads to a significant performance improvement. We refer to this design as filtering skewed data. Since both approximate frequent item counting and frequency estimation assume a certain amount of skew in input data, our solutions to these problems, Filter and Augmented Sketch
Rule Based and Supervisory Training Approach to Develop Expert System Tool for Detecting Lung Cancer Disease

Knowledge-based expert systems, or expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Lung cancer is one of the dreaded disease in the modern era. It is responsible for the most cancer deaths in both men and women throughout the world. Early diagnosis and timely treatment are imperative for the cure. Longevity and cure depends on early detection. This paper gives on insight to identify the forget group of people who are suffering or susceptible to suffer lung cancer disease. Seeking proper medical attention con be initiated based on the findings. Expert system tool developed, to find this target group based on the non-clinical parameters. Symptoms and risk factors associated with Lung cancer ore token as the basis of this study. This expert system basically works on the rule based approach to collect the data. Then Supervisory learning approach is used to infer the basic data. Once sufficient knowledge base is generated the system can be made to adopt in unsupervised learning mode.
Quality-Driven Software Development for Maintenance

Software maintenance is sometimes considered as a special kind of activity that is separated from a software development process. Meanwhile, the opposite is true; maintenance should be taken into account from the beginning of the software development process. Because a model-based software development is the prevailing software development paradigm, the maintainability should be considered within models that arise in software development process. We claim that the quality of the models arising in the software development process has a positive influence on their maintainability: the higher quality of the models, the more effective maintainability activity. The background for our consideration is MDA approach, and the scope of the consideration is limited to perfective maintenance only. The set of so called 6C quality characteristics is assumed to define a quality of MDA-models. Our selection of 6C quality characteristics is justified by the fact that they are related to activities performed on models within the maintenance. To assess MDA-models in the context of the maintainability, we define checklists for the 6C characteristics. These checklists are used for derivation of some measures which are useful in checking to what scope a given characteristics is satisfied. The main advantage of the approach is its independence of the knowledge of future changes of user requirements that trigger perfective maintenance. In the chapter, we demonstrate a simple example of how to assess the quality of PIM-models that are the realization of the CIM-model. Additionally, we discuss how to select, for further development, the best PIM-model from the set of possible solution.
A story of an on-going romance

Today, in a world of consumption where almost everything is branded, every consumer has a brand that they love, a so called lovemarks. Nowadays, it takes more than just a commercial to make consumers stay committed to a brand. Consumers need to relate on a more personal level. There lies a deep rooted love, consistent over long periods of time, making the luxury brand consumer’s one the most loyal consumers in the world. Consequently, it is the consumers that decide what a lovemarks is, and why they go back to repurchasing that brand again, a kind of on-going romance between consumer-
Hybrid control for stabilization of a class of cascade nonlinear systems

Presents a hybrid feedback control approach for stabilizing a class of cascade nonlinear systems to an equilibrium. The control architecture is a combination of nonlinear analog feedback and switched (sampled data) feedback, that, in a certain sense, feedback linearizes the closed loop at the analog time scale and at the time scale induced by the switching. Conditions for local asymptotic stability and global asymptotic stability of the equilibrium of the closed loop hybrid system are developed. The results are applied to the construction of hybrid controllers that stabilize a class of underactuated mechanical systems and a class of nonlinear nonminimum phase systems. In particular, a hybrid controller is developed and studied for the model of a rotational and translational actuator.
The Impact of Web Site Familiarity on User Performance When Critical Navigation Links Change

The research in this paper examines the effect of web site familiarity on the impact of small changes in a site’s primary navigation structure on user performance. Ninety-two participants performed multiple tasks on a web site, and then returned to the site either immediately or after a three-week delay to perform one of the original tasks again. Half the users had the critical navigation link on the first task, while half did not. On the second visit, the presence or absence of the link either remained consistent, or was the opposite of the condition experienced during their first visit. The addition of multiple tasks during the user’s first visit to the website was expected to cause the memory of the path to the target to be less salient during subsequent visits, thus reducing the performance increase observed in prior studies. However, results show that web site familiarity did not have a significant effect on user performance in this task. One likely explanation for this finding is that there is a trade-off between the salience created for the correct information path gained by performing a single-task first visit and the familiarity gained through multiple forays through the site as the result of multiple task completion.
Language E-learning based on Learning Analytics in Big Data Era

Language E-learning, an online language learning mode, completely transforms the traditional learning and teaching mode. However, with the coming of Big Data era, it not only enjoys some benefits, but also is confronted with great challenges. The article first concludes the reforms Big Data brought to the world, and then introduces the definition, key elements, the applying model, main analyzing methods and tools of learning analytics. Finally, the article fully shows the implementation of learning analytics to the study of language E-learning. Through the study of learning analytics, the designer of Language E-learning can learn the learners' learning behaviors and provide the efficient learning material, tools and systems.
The Effect of Asynchronous Data on Pilot-Controller The Effect of Asynchronous Data on Pilot-Controller Communication in a Dynamic Environment with Subject-Matter Communication in a Dynamic Environment with Subject-Matter Experts Experts

Integrating Unmanned Aerial System (UAS) into controlled airspace may introduce communication challenges if there are time delays associated with the distribution of a common surveillance source of those UAS. Termed “information asynchrony” by Yuan et al (2012), an earlier, static image study showed large time delays had an observable impact on controller-pilot communication, but the effect was not present for time delays of less than 1 minute. A follow-up study is being conducted using an online ATC-flight simulator with professional pilots and controllers as participants. Effects on communication are being analyzed objectively through measurable characteristics of communication breakdown, and subjectively through trial questionnaire and survey. Limited results to-date showed no observable effects on pilot-controller communication with time delays of less than 100 seconds and illustrated the challenge of identifying measures robust to the inherent variability in working methods and communication styles.
Research Article Forgery Detection in Dynamic Signature Verification by Entailing Principal Component Analysis

Received 21 July 2007; Accepted 6 October 2007The critical analysis of the data glove-based signature identiﬁcation and forgery detec-tion system emphasizes the essentiality of noise-free signals for input. Lucid inputs areexpected for the accuracy enhancement and performance. The raw signals that are cap-tured using 14- and 5-electrode data gloves for this purpose have a noisy and voluminousnature. Reduction of electrodes may reduce the volume but it may also reduce the eﬃ-ciency of the system. The principal component analysis (PCA) technique has been usedfor this purpose to condense the volume and enrich the operational data by noise reduc-tion without aﬀecting the eﬃciency. The advantage of increased discernment in betweenthe original and forged signatures using 14-electrode glove over 5-electrode glove hasbeen discussed here and proved by experiments with many subjects. Calculation of thesum of mean squares of Euclidean distance has been used to project the advantage ofour proposed method. 3.1% and 7.5% of equal error rates for 14 and 5 channels furtherreiterate the eﬀectiveness of this technique.Copyright © 2007 Shohel Sayeed et al. This is an open access article distributed underthe Creative Commons Attribution License, which permits unrestricted use, distribution,and reproduction in any medium, provided the original work is properly cited.
THE RESEACH AND DESIGN OF HONEYPOT SYSTEM IN THE LAN SECURITY

- The purpose of this paper is to design a system that detects the attacker on the system, storing the information about the attack such as the IP address of the attacker, day and date and timing. Also the type of attack we have implemented such as E-mail scan, Socket scanner port scanner. This software we have specially designed for providing security to the LAN. Also we have implemented a client module which will run on the LAN.In e-mail scan we scan mails and deleted the spam mails. In port scanner we scan the ports to check which portsare opened or not. In packet scan we capture the packets.
Avoiding Data Traffic on Smart Grid Communication System

Smart Grid is a recent area where the key feature is shift the present power system approach. But, the challenges of upgrade this present power system are several, such as: how to add reliable links between customers' home and data centers to enable smart meter sending power consumption data? how to avoid big data and bottleneck on backbone to transmission of millions of these customers' devices? On the other hand, smart meter can be treated as a sensor network device. Thus, it can use the same data reduction mechanisms that have been studied in wireless sensor network to decrease its traffic. This paper proposes a data reduction approach based on prediction by simple linear regression to avoid flow of readings between smart meter and smart grid system. Although the approximation performed by linear regression increases the prediction error in some instances, we have implemented an adaptive mechanism (Adaptive Simple Linear Regression - ASLR) that checks if the prediction error or lack of relationship between the modeled samples is harmful to our data reduction approach. Thereby, two ways have been deployed to tune the samples window (amount of readings) for improve own approach. These samples are smart meter readings which are modeled in a linear regression function for recovering data instead of sending it to the datacenter. One mechanism adjusts samples window based on prediction error and another one adjusts samples window based on Pearson's coefficient. Also, some experiments were conducted using the Wavelet as mechanisms for data reduction but the best results were obtained using ASLR, which saves on the data transmission to a controllable level of error. This article contains all steps to reach at a more robust solution, which serves as a guide to others as lessons learned.
ASYNMPU: a fully asynchronous CISC microprocessor

In this paper, the design and implementation of an asynchronous 8/16 bit microprocessor (ASYNMPU) are described. The objective of this work is to investigate the potential of asynchronous computer architecture in small scale low power applications. ASYNMPU is one of the first CISC type microprocessors that is designed with asynchronous technique. Some features have been incorporated in ASYNMPU to handle the complicated structure of a CISC type processor, such as variable instruction length and microprogramming. Furthermore, a new external synchronism is built to provide compatibility to external circuit. ASYNMPU is pin-to-pin compatible with Intel 8/16-bit microprocessor. It can be used to directly replace the Intel 8/16-bit microprocessor in any existing system. It will then be modified to become a Intel 8/16-bit microprocessor based microcontroller for low power process control applications. As a distinct feature of an asynchronous processor, the functionality of ASYNMPU is independent of external system clock frequency. The power dissipation is reduced in idle state which is an inherent benefit of asynchronous design approach.
A 0.7-3 GHz GaAs QPSK/QAM direct modulator

A vector modulator which contains a 90 degrees phase-shifter, two pairs of differential amplifiers, two double balanced FET mixers, and a differential output stage within a single chip is described. The QPSK and 16 QAM (quadrature amplitude modulation) constellations are measured with a vector network analyzer. The output spectrum of the SSB (single sideband) modulation is shown, demonstrating that the carrier suppression and the sideband suppression are better than 40 dBc. Third-order intermodulation tones are less than -40 dBc, while carrier suppression is better than 40 dBc. <<ETX>>
Evidence recommendation in forensics based on cyclic meta-paths in heterogeneous information networks

In this article we propose a novel approach for evidence recommendation in digital forensic applications. The so-called Evidence Graph (EG) is a Heterogeneous Information Network (HIN) constructed from entities and relationships extracted from large collections of low quality video footage, collected by surveillance cameras in relation to a crime. The EG has been developed in the context of the EU-funded project LASIE. It presents multiple types of nodes and edges and a generic network schema in which all types of nodes can be connected. In this work, relevant cyclic meta-paths are identified and an iterative scheme for evidence recommendation is proposed and evaluated on real data.
With Challenge and Support: Integrating Skills, Language and Content in a Literature Unit in EFL for Japanese Learners

This chapter is a case study describing the rationale and design of curriculum materials that were developed to offer both challenge and support for a four-skills integrated literature unit to build high beginner to low intermediate Japanese EFL student’s communicative competence. The unit designed for first year high school students in a Japanese high school’s partial-English immersion course included Baum’s (1900) novel, “The Wonderful Wizard of Oz”, and the film produced by Metro-Goldwyn-Mayer “The Wizard of Oz” (1939). A team of teachers1 sharing the teaching of the four macro-skills built both content and language teaching into the unit curriculum, drawing on social theories of learning and language. The approach to content-based learning using authentic texts is believed to provide a constructive alternative to the modified Japanese Ministry of Education, Sports, Culture, Science and Technology (MEXT) EFL texts, which have limited opportunities for the development of communicative competence.
A Precise Evolutionary Approach to Solve Multivariable Functional Optimization

— Genetic Algorithm (GA) is a stochastic search and optimization method imitating the metaphor of natural biological evolution. GA manages population of solutions instead of a single solution to find an optimal solution to a given problem. Although GA draws attention for functional optimization, it may search same point again due to its probabilistic operations that hinder its performance. In this study, we make a novel approach of standard Genetic Algorithm (sGA) to achieve better performance. The modification of sGA is investigated in selection and recombination stages and proposed Precise Genetic Algorithm (PGA). PGA searches the target space efficiently and it shows several potential advantages over the conventional GA when tested for solving functions having multiple independent variables.
Recent Topics on Subband Adaptive Filtering

In this paper, recent topics on subband adaptive filtering are reviewed. Especially, de1ay1ess structures are considered. In these structure adaptive weights in each subband are computed by the LMS algorithm and then transformed into those in fullband. The conventional subband adaptive五lterhas transmission de1ay and aliasing effects associated with the fi1ter bank. Such defects are comp1ete1y avoided in these schemes. A1so, a characteristic equation is derived to discuss stabi1ity of the adaptation algorithm using the Hadamard transform.
A Native Temporal Relation Database for Haskell

Representation of time-specific data is a widely discussed issue in modern database management systems. After a brief introduction to database basics, this work ex- plains the currently accepted concepts related to time-specific terminology, dier- ences in representation of time, and the storage of temporal data in detail. Further- more, the basics behind functional programming in general and Haskell in particular are briefly discussed. Using both technologies mentioned above, a native temporal database management system for Haskell is introduced. The prototype developed from these specifications is described both from the developer's and the user's point of view. Finally, a critical evaluation of the proposed system and the prototype is given, and possible further work is discussed.
Detection of human papillomavirus types 16 and 18 in oral squamous cell carcinoma samples in Malaysia

Infection of the oral cavity with high-risk human papillomavirus (HPV) has been implicated as one of the risk factors for the development of oral squamous cell carcinoma (OSCC). Among the high-risk HPV types, HPV 16 and 18 are the most common infective agents in oral cancers. This study aimed to compare the presence of high-risk HPV in genetic materials obtained from saliva, blood and tissues of OSCC patients in Malaysia. The genomic DNA was extracted from saliva (n=13), blood (n=59) and tissue (n=63) and subjected to polymerase chain reaction (PCR) amplification of human beta globin gene to confirm the presence and integrity of DNA. Positive amplification was then screened for high-risk HPV by nested PCR using MY11/09 and GP5+/6+ consensus primers, followed by a further confirmation by DNA sequencing of the positive samples. As a result, two saliva samples (2/13; 15.4%) were found to harbour HPV 16 and one tissue sample (1/63; 1.6%) was shown to be positive for HPV 18. However, none of the blood samples were positive for high-risk HPV. Thus, HPV is more likely to be found in the saliva of OSCC patients as compared to blood and tissue samples. The detection of high-risk HPV in OSCC patients is useful in deciding how to manage the patient as HPV-associated OSCC has better prognosis.
Role of Perceived Importance of Information Security: An Exploratory Study of Middle School Children's Information Security Behavior

Information security and privacy on the Internet are critical issues in our society. Importantly, children and adolescents need to understand the potential risk of using the Internet. In this research, we examine factors that motivate students’ Information Security Behavior on the Internet. A pilot survey of middle and junior high school students is the source of the data. This study provides a model that explains students’ behavior pertaining to Information Security. A significant research finding is that students’ perceived importance of Information Security plays a critical role in influencing their Information Security Behavior.
The collocation model based on LDA

LDA is a probabilistic topic model to discover the hidden thematic structure in large archives of documents. LDA-Col model is an extended model based on LDA model. In this paper, we introduced LDA-Col model in detail, including the plate notation, generative process and inference. Finally, we present experiment in topic words discovery to show the discovery performance differences between the LDA model and LDA-Col model.