Miracle-dz/UniFAR-FTUs huggingface dataset:
Using wikis to promote quality learning in teacher training

This paper discusses writing as a social practice and speculates on how wikis might be used to promote higher quality academic writing and support collaborative learning. This study of undergraduate teacher trainees’ online learning activities focuses on how shared spaces – wikis – might be used to communicate ideas and generate course‐specific content. The study also explored how students, through such activities, were able to improve their academic writing skills and engage more critically in learning. Data captured from student discussion boards and a post‐module email questionnaire (n = 35) were used to map student perceptions of the usefulness of wikis in support of their academic studies. The data indicate that most students raised their skill level in writing directly to the publicly viewable wiki space, in sharp contrast to the more informal content they posted on the discussion boards. The scope of collaborative writing was limited due to students’ reluctance to edit each others’ work, but students appreciated the shared environment as a means of discussing their work and the content of the course. Students reported that their academic writing skills had improved through their formal participation in the wiki.
Pattern-level temporal difference learning, data fusion, and chess

Our research group is using chess as a vehicle for studying the fusion of adaptation, multiple representation, and search technologies for real-time decision making. Chess systems like Deep Blue have achieved Grandmaster chess play with a brute-force search of the game tree and human- supplied information, like piece-values and opening books. However, subtle aspects of chess, including positional features and advanced concepts, are not capable of being represented or processed efficiently with the standard method. Since 1989, Morph I-III have exhibited more autonomy and learning ability than traditional chess programs in `adaptive pattern-oriented chess'. Like its predecessors, Morph IV is a reinforcement learner, but it also uses a new technique we call pattern-level TD and Q-learning to mathematically map the state space and effectively learn to classify situations. Its three knowledge sources include two traditional ones: material and a piece-square table, and a new method called Distance. These are combined using a simple genetic algorithm and a decision tree. This paper shows the effectiveness of fusing knowledge to replace search in real-time situations, since an agent which combines all sources is capable of consistently beating an agent which employs any of the individual knowledge sources. Surprisingly, the pattern-level TD agent is slightly superior to the pattern-level Q-learning agent, despite the fact that the Q-learning agent updates more Q-values on each temporal step.
Ecstatic: An object-oriented programming language with an axiomatic semantics

This paper describes a small object-oriented programming language and its axiomatic semantics. The language includes common objectoriented features like methods and subtyping. Objects are implicitly references, and the semantics handles the aliasing that arises. The paper formalizes in first-order logic what it means for a method implementation to meet its specification.
Neural Computation Scheme of Compound Control: Tacit Learning for Bipedal Locomotion

: The growing need for controlling complex behaviors of versatile robots working in unpredictable environment has revealed the fundamental limitation of model-based control strategy that requires precise models of robots and environments before their operations. This di ﬃ culty is fundamental and has the same root with the well-known frame problem in artiﬁcial intelligence. It has been a central long standing issue in advanced robotics, as well as machine intelligence, to ﬁnd a prospective clue to attack this fundamental di ﬃ culty. The general consensus shared by many leading researchers in the related ﬁeld is that the body plays an important role in acquiring intelligence that can conquer unknowns. In particular, purposeful behaviors emerge during body-environment interactions with the help of an appropriately organized neural computational scheme that can exploit what the environment can a ﬀ ord. Along this line, we propose a new scheme of neural computation based on compound control which represents a typical feature of biological controls. This scheme is based on classical neuron models with local rules that can create macroscopic purposeful behaviors. This scheme is applied to a bipedal robot and generates the rhythm of walking without any model of robot dynamics and environments.
Enhancement of 3-D Video Displays by Means of Superimposed Stereo-Graphics

This paper describes a number of aspects of a display technology under development, which involves the integration of stereoscopic computer graphics and stereoscopic video displays. The background and justification for this development are discussed, based on the need of operators of remotely controlled vehicles and/or manipulators to estimate absolute sizes and locations of objects at a remotely viewed site. The basic technology involves superimposing an interactively controllable computer-generated stereographic cursor onto a stereoscopically viewed video image. Absolute measurements can be made with this system, based on relative comparison of cursor position with target object location. Experimental results are presented in which the ability of subjects to perform such tasks was investigated. In general, results were promising; subjects were able to align virtual pointers with real targets essentially as well as they were able to manipulate real objects. A number of implications of this technology for the enhancement of three dimensional video displays are discussed.
Reinforcement Learning is Direct Adaptive Optimal Control

Control problems can be divided into two classes: 1) regulation and tracking problems, in which the objective is to follow a reference trajectory, and 2) optimal control problems, in which the objective is to extremize a functional of the controlled system's behavior that is not necessarily defined in terms of a reference trajectory. Adaptive methods for problems of the first kind are well known, and include self-tuning regulators and model-reference methods, whereas adaptive methods for optimal-control problems have received relatively little attention. Moreover, the adaptive optimal-control methods that have been studied are almost all indirect methods, in which controls are recomputed from an estimated system model at each step. This computation is inherently complex, making adaptive methods in which the optimal controls are estimated directly more attractive. Here we present reinforcement learning methods as a computationally simple, direct approach to the adaptive optimal control of nonlinear systems.
Dual-loop feedback control of servo motor systems using singular perturbation method

This paper addresses a dual-loop feedback control problem for servo motor systems that are capable of the suppression of high frequency resonance or vibration (RV). The singular perturbation based model reduction method is used to convert the closed loop system in to two reduced-order subsystems, which represent the position control loop and the high frequency RV dynamics, respectively. A composite control strategy is proposed to suppress the high frequency RV based on the analysis while stabilizing the position loop. The theoretical results are validated through simulation study and frequency-domain analysis.
Metallographical Image Segmentation and Compression

The double-threshold binarization and morphological transform were applied to process the metallographical image. They could classify the grain and the grain boundary from gray metallographical image. Also, the eight-direction tracking techniques about Freeman chain encoding for metal metallographical compression had been discussed, and a grain boundary tracking algorithm was given. The experimental result shows that the proposed image processing method can segment grains and their boundaries efficiently. Freeman chain encoding can compress the stored data of metallographical image greatly. Compared with another compression method RLE, it has much higher compression effect.
Integrating Defect Data, Code Review Data, and Version Control Data for Defect Analysis and Prediction

In this thesis, we present a new approach to integrating software system defect data: Defect reports, code reviews and code commits. We propose to infer defect types by keywords. We index defect reports into groups by the keywords found in the descriptions of those reports, and study the properties of each group by leveraging code reviews and code commits. Our approach is more scalable than previous studies that consider defects classified by manual inspections, because indexing is automatic and can be applied uniformly to large defect dataset. Also our approach can analyze defects from programming errors, performance issues, high-level design to user interface, a more comprehensive variety than previous studies using static program analysis. By applying our approach to Honeywell Automation and Control Solutions (ACS) projects, with roughly 700 defects, we found that some defect types could be five times more than other defect types, which gave clues to the dominant root causes of the defects. We found certain defect types clustered in certain source files. We found that 20%-50% of the files usually contained more than 80% of the defects. Finally, we applied a known defect prediction algorithm to predict the hot files of the defects for the defect types of interest. We achieved defect hit rate 50%-90%.
Auditing the Corporate Governance Effort in an Organization

Abstract Corporate Governance is a key element to help an organization exude a positive perception in terms of how it is governed to meeting legal and regulatory requirements. A good governance upholds fiduciary responsibilities to investors, helps attract and retain employees and directors with integrity, makes a business an attractive alliance partner, generates community support and motivates stakeholder's performance. Auditing corporate governance can be complicated and may involve political risk but such an audit requires careful planning and a structured approach. Auditors assist in two ways in such an audit by providing assurance that corporate governance policies are effective and consulting services on relevant issues to enhance the governance structure. Key roles are played by: • The Board; • Audit Committee; • Internal Audit; • External audit; • Top Management. It is critical that these roles be reviewed and the infrastructure independently assessed to ensure they are discharged effectively.
Using multi-protocol encapsulation technology to develop optimum data broadcast systems

In both satellite and terrestrial environments, the data communication networks and the digital television networks are converging rapidly to enable secure and reliable multicasting and unicasting of data files and streams to both integrated receiver decoders (IRDs) and personal computers (PCs). This paper explores the different venues on the way to a robust data broadcasting product. A key new technology standard in this area is the digital video broadcasting (DVB) multi-protocol encapsulation standard. The paper compares and contrasts the DVB multi-protocol encapsulation standard to other data communication and broadcasting standards. It describes the technological details of this new standard, analyzes how reliability and security may be applied to this standard and explains how it can be used to implement the basic data communication services and enticing vertical applications.
Intrusion Detection Method Based on Frequent Pattern

As the surging development of the information technology, Intrusion Detection System has been devised for the safety of computer network. This paper focuses on the method of frequent pattern based intrusion detection. A new formula measuring the normal degree of a transaction is presented. We propose a new algorithm to calculate each transaction’s normal degree as well as detect intrusions. Experiment results show that the proposed algorithm is competent in detecting intrusions with high detection rate and relatively low false positive rate.
Effects Of Thymoquinone and Citalopram On Oxidative Stress in Gastric and Duodenum Tissue in Reserpinized Rats

295 Erciyes Med J 2019; 41(3): 295–9 • DOI: 10.14744/etd.2019. 77527 ORIGINAL ARTICLE – OPEN ACCESS This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Dilek Kuzay Effects of Thymoquinone and Citalopram on Oxidative Stress in Gastric and Duodenum Tissue in Reserpinized Rats Objective: Medicaments used in the therapy of GIS diseases have many detrimental impacts. Therefore, antioxidant effective molecules can help in the treatment process. This study aimed to examine the oxidant and antioxidant activity of thymoquinone (TQ) and citalopram in gastric and duodenum tissues of reserpinized rats. Materials and Methods: In the study, we split the rats in six groups of six rats each: 1) Control (C) 1; 2) Control (C) 2; 3) reserpine (R); 4) Reserpine+citalopram (R+C); 5) Reserpine+thymoquinone (R+T); 6) Reserpine+citalopram+thymoquinone (R+C+T). Reserpine (0.2 mg/kg) was intraperitoneally administered. TQ (10 mg/kg) and citalopram (10 mg/kg) were intragastrically administered 30 min before reserpine injection. The rats were treated for 14 consecutive days. At the end of the experiment, we examined total antioxidant status and total oxidant status in gastric tissue; and total nitric oxide, malondialdehyde, and glutathione levels in duodenum tissue. Results: There was a reduction on total oxidant status in gastric tissue in the R+C group in comparison with the R group (p<0.01). The decrease in total oxidant status in the R+C+T and R+T groups was more significant (p<0.01). An increase in total antioxidant status was observed in the R+C, R+T, and R+C+T groups when compared to the R group (p<0.01). In comparison to the R group, there was a reduction in malondialdehyde and nitric oxide levels and a rise in glutathione level in duodenum tissue in the R+C+T and R+T groups (p<0.01). Conclusion: Reserpine increased oxidative stress and decreased antioxidant capacity in gastric and duodenum tissues. TQ and citalopram+TQ treatment decreased oxidative stress and increased antioxidant capacity in gastric and duodenum tissues. TQ and citalopram+TQ treatments proved to be more effective in protection from oxidative stress caused by reserpine in gastric and duodenum tissues than citalopram treatment.
Distributed Constraint Reasoning

This tutorial aims on the one hand side to provide an introduction into distributed constraint reasoning and on the other side to highlight the current research trends in the area. The tutorial draws from earlier tutorials by Makoto Yokoo (CP98), Jorg Denzinger (IJCAI01) and Yokoo, Denzinger and Marius Silaghi (IJCAI03, AAMAS04, IJCAI05) and from the PhD dissertations of Silaghi and Adrian Petcu. The previous tutorials were created as half-day tutorials and this was also the planned time frame for this tutorial. Consequently, we had the hard decisions to make which of the concepts to present and where to put foci. We decided to focus the introduction part on asynchronous methods and to highlight new approaches to constraint optimization and the whole topic of semi-cooperative agents with its connections to issues like privacy and reigning in the competitiveness of agents. To make up for this rather subjective selection, we include a structured bibliography of works on distributed knowledge-based search and distributed constraint reasoning with some notations of where to place the particular works.
A comparison of specific space diversity techniques for reduction of fast fading in UHF mobile radio systems

Over the past few years a variety of space diversity system techniques have been considered for the purpose of reducing the rapid fading encountered in microwave mobile radio systems. Basic diversity methods are first reviewed in the framework of mobile propagation effects, and then specific techniques are compared from the standpoint of transmitter power required to achieve a certain performance. Criteria of comparison used included baseband SNR while moving and reliability when the vehicle stops at random. System parameters are type and order of diversity and transmission bandwidth. Tradeoffs between performance properties and system parameters are indicated. The calculations show that relatively modest use of diversity techniques can afford savings in transmitter power of 10-20 dB. For example, at a range of 2 mi, to obtain 30-dB baseband SNR while moving and 99.9-percent reliability when stopped requires a transmitted power of 8 W for a conventional FM system with no diversity. Two-branch selection diversity provides the same performance for a transmitter power of only 300 mW.
A genetic algorithm with neighborhood search for the resource‐constrained project scheduling problem

The resource‐constrained project scheduling problem (RCPSP) consists of a set of non‐preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to find a schedule of the activities to minimize the project makespan. This article presents a new genetic algorithm (GA) by incorporating a local search strategy in GA operators. The local search strategy improves the efficiency of searching the solution space while keeping the randomness of the GA approach. Extensive numerical experiments show that the proposed GA with neighborhood search works well regarding solution quality and computational time compared with existing algorithms in the RCPSP literature, especially for the instances with a large number of activities. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011
Network and Content Adaptive Streaming of Layered-Encoded Video over the Internet

In this thesis we propose new techniques and algorithms for improving the quality of Internet video streaming applications. We formulate optimization problems and derive control policies for transmission over the current best-effort Internet. This dissertation studies adaptation techniques that jointly adapt to varying network conditions (network-adaptive techniques) and to the characteristics of the streamed video (content-adaptive techniques). These techniques are combined with layered-encoding of the video and client buffering. We evaluate their performance based on simulations with network traces (TCP connections) and real videos (MPEG-4 FGS encoded videos). We first consider the transmission of stored video over a reliable TCP-friendly connection. We compare adding/dropping layers and switching among different versions of the video; we show that the flexibility of layering cannot, in general, compensate for the bitrate overhead over non-layered encoding. Second, we focus on a new layered-encoding technique, Fine-Granularity Scalability (FGS), which has been specifically designed for streaming video. We propose a novel framework for streaming FGS-encoded videos and solve an optimization problem for a criterion that involves both image quality and quality variability during playback. Our optimization problem suggests a real-time heuristic whose performance is assessed over different TCP-friendly protocols. We show that streaming over a highly variable TCP-friendly connection, such as TCP, gives video quality results that are comparable with streaming over smoother TCP-friendly connections. We present the implementation of our rate adaptation heuristic in an MPEG-4 streaming system. Third, we consider the general framework of rate-distortion optimized streaming. We analyze rate-distortion traces of long MPEG-4 FGS encoded videos, and observe that the semantic content has significant impact on the encoded video properties. From our traces, we investigate optimal streaming at different aggregation levels (images, groups of pictures, scenes); we advocate scene-by-scene optimal adaptation, which gives good quality results with low computational complexity. Finally, we propose a unified optimization framework for transmission of layered-encoded video over lossy channels. The framework combines scheduling, error protection through Forward Error Correction (FEC) and decoder error concealment. We use results on infinite-horizon average-rewards Markov Decision Processes (MDPs) to find optimal transmission policies with low-complexity and for a wide range of quality metrics. We show that considering decoder error concealment in the scheduling and error correction optimization procedure is crucial to achieving truly optimal transmission.
THE 3D DOCUMENTATION OF PROJECTED WOODEN WINDOWS (THE ROSHANS) IN THE OLD CITY OF JEDDAH (SAUDI ARABIA) USING IMAGE-BASED TECHNIQUES

The Roshan represents one of the most characteristic aspects of traditional architecture in Hejaz (Saudi Arabia) and a frequent feature in most of the Historical Jeddah’s heritage buildings. The old city has witnessed continued degradation recently, which has caused the loss its traditional architecture and hundreds of these projected wooden windows. Documentation is a major step towards heritage preservation, whether threatened by man-made or natural factors. However, due to the absence of specialists and experts an architectural database of the Roshans does not exist. Surveying these architectural elements is a very laborious and difficult process when using conventional methodologies including the laser sensors approach mainly due to the onsite limitations. Establishing an architectural database of the Roshans is the main objective in this research paper, based on the continuous development of data capture and modelling methodologies that allows the accurate recording of even the most complex and intricate details and patterns which are typically found in Roshans. Recent advances in image based techniques (digital close-range photogrammetry and computer vision) such as the semi-automated solutions of Dense Stereo Matching (DSM) and 3D modelling software has offered an accurate, inexpensive and practical solution to surveying, documenting and reconstructing these architectural heritage features. In this paper the application of these methods is tested and evaluated on the Roshans in the old city of Jeddah.
Alarm correlation for complex telecommunication networks using neural networks and signal processing

The aim of this paper is to investigate new tracks to tackle the open issues of alarm correlation for complex networks (e.g. IP/SDH or IP/WDM). The suggested approach consist of transforming, by means of a neural network the equipment alarm messages into a signal, and then, to use signal-processing methods in order to extract the relevant information for diagnosis.