Miracle-dz/UniFAR-FTUs huggingface dataset:
A GQM-based open research data technology evalution method in open research context

Open Research Data is gaining popularity nowadays, and various research units and individuals are interested to join this trend. However, due to variety of Open Research Data technologies, they have found it is difficult to select proper ones for their specific requirements. Thus, a method for evaluating of Open Research Data related technologies is developed in this study for researchers to select proper ones. Firstly, the theoretical knowledge of research data sharing and reusing barriers is resulted from a structured literature review. As a result, from the 19 primary studies, 96 instances of existing barriers are identified and classified to seven categories, where four of them are research data sharing barriers and rest of them are reusing barriers. This knowledge is regarded as an important resource for understanding researchers’ requirements on Open Research Data technologies, and utilized to develop the technology evaluation method. Additionally, the Open Research Data Technology Evaluation Method (ORDTEM) is developed basing on the Goal/Question/Metric (GQM) approach and resulted research data sharing and reusing barriers. To develop this method, the GQM approach is adopted as the main skeleton to transform these barriers to measurable criterion. Consequently, the ORDTEM, which is consisting of six GQM evaluation questions and 14 metrics, is developed for researchers to evaluate Open Research Data technologies. Furthermore, to validate the GQM-based ORDTEM, a focus groups study is conducted in a workshop. In the workshop, nine researchers who has the need to participate Open Research Data related activities are recruited to form a focus group to discuss the resulted ORDTEM. And by analysing the content of the discussion, 16 critical opinions are addressed which resulted eight improvements including one refinement on an existing metric and seven new metrics to ORDTEM. Lastly, a testing process of applying ORDTEM to evaluate four selected Open Research Data technologies is implemented also for validating whether it can be used in solving real-world evaluation tasks. And more than the validation, this experiment also results the materials about usage of ORDTEM, which is useful for future adopters. However, more than developing the solution to eliminate the difficulty of selecting technologies for participating Open Research Data movements, this study also provides two additional contributions. For one thing, resulted research data sharing and reusing barriers also direct the future effort to prompt Open Research Data and Open Science. Moreover, the experience of utilizing the GQM approach to transform existing requirements to evaluation criterion is possible to be studied for developing other requirement-specific evaluation.
Green Corrosion Inhibitory Potentials of Cassava Plant (Manihot esculenta Crantz) Extract Nanoparticles (CPENPs) in Coatings for Oil and Gas Pipeline

Internal and external corrosion affects oil and gas pipelines and were discussed in this chapter. Corrosion inhibitors are one of the methods that can be used to achieve corrosion control and prevention. The main discussion in this chapter was the use of cassava plant ( Manihot esculenta Crantz) extract nanoparticles (CPENPs) as an additive in coatings to serve as a green corrosion inhibitor for oil and gas pipeline. Trace elements, such as O, Si, Ca, K, Fe and S, which are hetero-atoms, have been identified in CPENPs. Elements like Si and Ca would also improve the strength of coatings as well as reduce corrosion rate of coated metals. It has also been revealed that CPENPs is composed of the following compounds SiO 2 , CaCO 3 , Ca 2 (SO 4 ) 2 H 2 O and CaC 2 O 4 (H 2 O), which would help in improving the mechanical properties of alloys, composites and coatings. SiO 2 if added to coatings will improve the coating hardness, while the presence of CaCO 3 in coatings will form a precipitate that will serve as a protective film on the surface of the metal, thereby protecting the metal from corrosion. The nature of bond and organic compounds that exist in the CPENPs was also discussed.
Computer Graphics, Artistic Production, and Social Processes

This is a case study of a class of university students who learned to use paint system software. The results indicate that any descriptions of computers as either controlling student production processes and ideas for imagery or as just another art medium are incomplete. Specifically, the research indicated that: (a) there was a general shift during the learning process from a focus on production to ideation in the students' responses about their image development; (b) students' images developed interactively in both production and ideation, indicating that the students controlled the computer and the computer influenced changes in their images; and (c) social interactions among the students were important to their computer graphic development and to their learning about aesthetic possibilities and decision-making.
Efficient Image Annotation Process Using Tag Ranking Scheme

Now a day’s number of computerized pictures are expanding which are accessible in online media . for picture matching and recovery image explanation applications are playing key part . yet existing procedures like substance based image retrieval and additionally tag based image recovery techniques are taking more opportunity to physically mark the image and having restrictions. Multilabel arrangement is likewise fundamental issue . it requires endless pictures with spotless and complete comments keeping the deciding objective to take in a reliable model for tag prediction. Proposing a novel methodology of tag ranking with matrix recovery which positions the tag and put those tags in descending request taking into account importance to the given picture. For tag prediction A Ranking based Multi-connection Tensor Factorization model is proposed. The matrix is shaped by conglomerating expectation models with various tags. At last proposed structure is best for tag ranking and which beats the multilabel classification issue.
Microwave-Assisted Solvent-Free Synthesis of Substituted 2-Quinolones.

A rapid and efficient method for the preparation of a variety of substituted 2-quinolones has been developed through the reactions of o-aminoarylketones with ester compounds containing a reactive α-methylene moiety in the presence of a catalytic amount of cerium chloride heptahydrate under solvent-free conditions in high yields. The rate and yield of the reaction are considerably improved by employing microwave irradiation.
Improved configuration for symmetric and asymmetric multilevel inverters with reduced number of circuit devices

ABSTRACT In this paper, a topology developed for multilevel voltage source inverters is proposed. The suggested modular configuration consists of several series-connected units, which can be applied as symmetric and asymmetric inverters. In the asymmetric mode, different solutions are suggested to generate an increased number of output voltage levels. In multilevel inverters, the number of required circuit elements determines the total cost, circuit size, installation area, complexity of control scheme and reliability of the inverters. The comparison study among the proposed inverter by considering all the presented algorithms for it, cascaded H-bridge (CHB) inverter and recently proposed converters, confirms that the proposed inverter uses a reduced number of circuit elements. In order to show the practicability of the proposed converter, a prototype of the proposed structure is implemented and tested. The simulation and experimental results are in good agreement with each other, indicating the effectiveness of the proposed inverter.
An Optimized Scheme to Resist Primary User Emulation Attacks

The problem of cognitive radio (CR) network security has become an important problem in cognitive radio technology. One of the most common attacks is primary user emulation attacks (PUEA), where some malicious users simulate CR users to prevent them from accessing the vacant frequency. Here, a cooperative spectrum sensing (CSS) method with optimal weight coefficient based on improved energy detection is proposed. In the proposed scheme, we combine sensing information using the optimal weight coefficient at a fusion center and apply the improved energy detection, which effectively prevent the PUEA. Simulation results show that the method outperforms the traditional energy detection with optimal weight coefficient in detection performance. Keywords-cognitive radio; cooperative spectrum sensing; primary user emulation attack; energy detection; optimal weight coefficient
Search Tools for Scaling Expert Code Review to the Global Classroom

This thesis aims to answer the question “How can teachers of online classrooms give more qualitative feedback to students? ” We narrow the scope of this question to an online software engineering class in which a major component is code review. We built two search tools that give teachers better coverage of student code. The first tool, Comment Search, allows students and staff to reuse any comment they previously wrote when reviewing another student’s code. Staff can reuse any comment written by any staff member as well. After deploying Comment Search in a classroom for a full semester, we found that students and staff used this tool to write higher quality comments. We also found that many reused comments were about similar patterns in code. This inspired the second tool, Code Search, which allows teachers to search for sections of student code that contain a desired pattern. Preliminary results of Code Search are promising: for the queries that Code Search is built for, Code Search returns nearly all relevant results. Together, Comment Search and Code Search offer teachers the ability to give meaningful comments to many more students than otherwise possible. Thesis Supervisor: Robert C. Miller Title: Professor
Research on Anchorperson Detection Method in News Video

News video analysis is an important field of video analysis. In this paper a knowledge based analysis method for news video——a two stage template matching method to detect the anchorperson shot of news video is presented, which is a fundamental step for segmenting news video units. The method is both generic and real time, and can be used in automatic news video analyzing and indexing systems.
Une approche pour l’opérationnalisation d’ontologies fondée sur les graphes conceptuels

Résumé — L’opérationnalisation d’ontologies consiste a exprimée une ontologie dans un langage opérationnel (computationnel), afin de pouvoir effectué des raisonnements et des inférences. Dans cet article nous proposons notre approche d’opérationnalisation d’ontologies basée sur les graphes conceptuels. Notre approche permet la création d’ontologies basées sur les graphes conceptuels ainsi que l’importation et la transformation d’ontologies existantes décrites en OWL. Une fois l’ontologie opérationnelle obtenue, celle-ci peut être vue comme une base de connaissances à laquelle nous ajoutons un mécanisme d’inférence permettant un raisonnement déductif.
An Energy Efficient Data Aggregation for Random Sensor Networks

Energy-efficient computing is the thrust area of research in an energy-constrained Wireless Sensor Network (WSN). Comb Needle Model (CNM) exists in literature for energy efficient data aggregation in regular (grid-based) WSNs. Clustering concept is added to CNM to reduce the energy consumption further. Besides, basic CNM is extended for randomly deployed WSNs. In this paper, the extended CNM for random WSNs is augmented with clustering mechanism. When clustering is added to the Extended CNM, it will aggregate the data at Cluster Head and minimizes the number of data transmissions, and thereby extends the network life span. The CNM uses the push-pull data distribution approach. It may overload certain sensor nodes, and lead to hotspots, which causes excess amount of energy loss. We extend the CNM with clustering in random network to overcome these issues and perform energy efficient processing. This paper makes the simulation based comparative analysis of the Extended CNM with clustering with that of without clustering. The performance metrics considered are energy consumption, communication cost, delay, packet loss, packet delivery ratio, and throughput. It is empirically observed that the network life span is improved substantially.
Leaf Cell And Hierarchical Compaction Techniques

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Quadruped robot harmonious control based on RBF-Q learning

This paper designed a kind of foot end tracking the ideal trajectory of motor coordination method by using adaptive RBF network and Q learning algorithm through the analysis of quadruped robot movement coordinated realization method.The simulation results show that the method can control the foot end of the quadruped robot to accurately track the trajectory of a given speed and displacement,and achieve quadruped robot motor coordination.
Real-time Face Detection and Tracking in Video Sequences

Object detection and tracking in video sequences is becoming one of the research focuses in the field of remote collaborative system. This paper presents a real-time face detection and tracking method that can be applied in CSCW system. According to skin-color distribution in the color space, this method develops a statistical skin-color model through interactive sample training. With this model, all candidate regions are segmented. The presence or absence of a face in each region is verified by means of feature matching. Real-time detection and tracking can be achieved by using this method in video sequences. In order to speed up tracking, the traditional method is improved by adding motion prediction, which uses the rules of continuity and works efficiently when several disturbing objects appear simultaneously. Experiment results show the proposed method has not only high speed and efficiency, but also robust performance to head rotation.
Multivariable Feedback Control Analysis And Design

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Principals Supporting Teachers in Providing Language Instruction to English Learners in Elementary School.

The purpose of the study was to examine the systems of support that principals establish at their school sites to support teachers with the academic achievement of the English learner population. Two schools from a single district were selected. Specific strategies, structures, and processes that support teachers and principals of English learners were explored. Based on the finding in this qualitative case study, major themes that emerged included (1) the implementation of a culture of high expectations and trust, (2) principals holding teachers and themselves accountable by supporting teachers with lesson development and monitoring daily instruction during a structured English Language Development (ELD) time as well as in other content areas, (3) principals providing various collaboration structures to support data analysis, targeted planning and instruction, and (4) principals supporting teachers with practicing the strategies learned in professional development sessions. In conclusion, the author proposes recommendations a principal must have in place to support teachers of English language learners.
Catalytic electrooxidation of formic acid by noble metal nanoparticle catalysts on reduced graphene oxide

Abstract The noble metals (Pt and Pd) loaded on polydopamine (PDA) modified graphene oxide (GO) as catalysts were prepared by a reduction. The catalysts were characterized by Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). The reduced graphene oxide (rGO) was prepared for use as a matrix to integrate alloyed metal catalysts. The results show that the dispersed small-catalyst nanoparticles are loaded on both GO and rGO supports and the PtxPdy catalysts on rGO are smaller than the PtxPdy catalysts on GO. Both cyclic voltammetry (CV) and chronoamperometry (CA) results reveal that bimetallic PtxPdy/PDA-GO catalysts have superior activity, CO tolerance, electron transfer and stability towards formic acid oxidation, compared to PtxPdy/GO and the commercial PtRu/C catalyst. The bimetallic PtxPdy and PDA loaded on GO could be capable of enhanced oxidation and hopefully used in direct formic acid fuel cells. Graphical Abstract
Valid inequalities for mixed-integer linear programming problems

OF THE DISSERTATION Valid Inequalities for Mixed-integer Linear Programming Problems by Emre Yamangil Dissertation Director: Endre Boros In this work we focus on various cutting-plane methods for Mixed-integer Linear Programming (MILP) problems. It is well-known that MILP is a fundamental hard problem and many famous combinatorial optimization problems can be modeled using MILP formulations. It is also well-known that MILP formulations are very useful in many real life applications. Our first, rather theoretical, contribution is a new family of superadditive valid inequalities that are obtained from value functions of special surrogate optimization problems. Superadditive functions hold particular interest in MILP as they are fundamental in building integer programming duality, and all “deepest valid inequalities” are known to arise from superadditive functions. We propose a new family of superadditive functions that generate inequalities that are at least as strong as Chvatal-Gomory (CG-) inequalities. A special subfamily provides a new characterization of CG-cuts. Value functions of optimization problems are known to be super additive. We look at special surrogate optimization problems, and measure their complexity in terms of the number of integer variables in them. It turns out that the lowest possible nontrivial complexity class here includes all CG-cuts, and provides some stronger ones, as well. Our next contribution is a practically efficient, polynomial time method to produce
The Software Reliability Evaluation of a Nuclear Controller Software Using a Fault Detection Coverage Based on the Fault Weight

The software used in the nuclear safety field has been ensured through the development, validation, safety analysis, and quality assurance activities throughout the entire process life cycle from the planning phase to the installation phase. However, this evaluation through the development and validation process needs a lot of time and money, and there are limitations to ensure that the quality is improved enough. Therefore, the effort to calculate the reliability of the software continues for a quantitative evaluation instead of a qualitative evaluation. In this paper, we propose a reliability evaluation method for the software to be used for a specific operation of the digital controller in a nuclear power plant. After injecting weighted faults in the internal space of a developed controller and calculating the ability to detect the injected faults using diagnostic software, we can evaluate the software reliability of a digital controller in a nuclear power plant.
Distributed Online Optimization on time-varying networks

This thesis introduces two classes of discrete-time distributed online optimization algorithms, with a group of agents which communicate over a network. At each time, a private convex objective function is revealed to each agent. In the next time step, each agent updates its state using its own objective function and the information gathered from its immediate in-neighbors at that time. We design algorithms distributed over the network topologies, which guarantee that the individual regret, the difference between the network cost incurred by the agent’s states estimation and the cost incurred by the best fixed choice, grows only sublinearly. One algorithm is based on gradient-flow, which provably works for a sequence of time-varying uniformly strongly connected graphs. The other one is based on Alternating Direction Method of Multipliers, which works on fixed undirected graphs and gives an explicit regret bound in terms of the size of the network. We implement the proposed algorithms on a sensor network and the results demonstrate the good performance for both algorithms.
Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing

Cloud Computing has been envisioned as the next generation architecture of IT Enterprise. It moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. This work studies the problem of ensuring the integrity of data storage in Cloud Computing. In particular we consider the task of allowing a Third Party Auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud. The introduction of TPA eliminates the involvement of the client through the auditing of whether his data stored in the cloud is indeed intact.
Analysis Techniques For Racecar Data Acquisition

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An executable software project management model by beta-distributed stochastic Petri nets

This paper proposes a new software project time and cost management model using a beta-distributed stochastic Petri nets (BSPN), which is an integrated model of PERT and Petri nets. A beta-distributed transition, from PERT, is adapted for modeling the uncertainty of time and cost of a software project. Structural properties of the project are analyzed from structure of the BSPN. Behavioral characteristics of the project, such as time and cost, are analyzed using a chronological reachability graph of BSPN. <<ETX>>
Android application evolution and malware detection

Android has dominated the mobile market for a few years now. Meanwhile, Android has seen a sharper increase in malware. It is a matter of utmost urgency to find a better way to detect Android malware. In this thesis, we use static code analysis to extract the android application security features and build classification models to detect Android malware. Our permissions-based classification model can achieve 96.5% accuracy, 97.2% TPR and 95.5% TNR with lower overhead. By using multiple security metrics, the detection rate increases to 99.3% accuracy, 99.5% TPR and 99% TNR. Moreover, we investigate Android application security evolution. The data shows that more than half applications have security vulnerabilities or dangerous behaviors. Based on this result, we argue that there can be higher chance to impose update attack, where, the malware is contained in the updated version of a benign application. Our multiple-metrics based classification model is adapted to detect the update attack and can achieve similar or even better performance based on our initial results.