Miracle-dz/UniFAR-FTUs huggingface dataset:
An evolutionary approach for interactive computer games

In this paper, we introduce the first stage of experiments on neuro-evolution mechanisms applied to predator/prey multicharacter computer games. Our test-bed is a computer game where the prey (i.e. player) has to avoid its predators by escaping through an exit without getting killed. By viewing the game from the predators' (i.e. opponents') perspective, we attempt offline to evolve neural-controlled opponents capable of playing effectively against computer-guided fixed strategy players. Their efficiency is based on cooperation which emerges from an abstract type of partial interaction with their environment. In addition, investigation of behavior generalization demonstrated the crucial contribution of playing strategies in the development of successful predator behaviors. However, emergent well-behaved opponents trained offline with fixed strategies do not make the game interesting to play. We therefore present an evolutionary mechanism for opponents that keep learning from a player while playing against it (i.e. online) and we demonstrate its efficiency and robustness in increasing the predators' performance while altering their behavior as long as the game is played. Computer game opponents following this online learning approach show high adaptability to changing player strategies, which provides evidence for the approach's effectiveness and interest against human players.
A Novel Hierarchical Detection Method for Enhancing Anomaly Detection Efficiency

Improving detection accuracy and efficiency is crucial to the effectiveness of an intrusion detection system. In this paper, a novel intrusion detection system based on hierarchical approach that integrates a Random Forest based misuse detection model and a Self-Organizing Map based anomaly detection model is proposed for improving detection rates with low computational cost. In the proposed detection system, two components of removing the known attacks through the misuse detection first and reducing features that are redundant and contribute little to the detection process make it possible to construct the normal profiles precisely and efficiently detect unknown attacks deviated significantly from normal pattern. The proposed system not only achieves a significant detection performance, but also enables fast detection through the hierarchical detection method with a good subset of features that are critical to the improvement of the performance of classifiers.
Iterative carrier phase synchronization for low-density parity-check coded systems

In this paper, we consider the effect of a carrier phase offset on the performance of a low-density parity-check (LDPC) coded QAM modulated system. We investigate an ML-based carrier phase synchronization algorithm that makes use of the posterior probabilities of the data symbols, provided by the iterative decoder. The resulting carrier phase synchronizer is an extension, to LDPC coded systems, of the iterative phase estimator for turbo coded systems, presented in V.Lottici and M.Louse [2002], and has negligible BER performance degradation as compared to the ideally synchronized system.
To repeat, or not to repeat

Introduction Over the last 75 years a pool of research-based knowledge about the effects on students of repeating a year level has been accumulating. It now overwhelmingly indicates that there are neither academic nor social advantages for the majority of students who repeat a year of their schooling. There is probably no other educational issue on which the research evidence is so unequivocal. There is also no other educational issue where there is such a huge gap between what the research says and the practices that schools continue to adopt. Paradoxically this discrepancy between evidence and practice has never been more apparent than in recent times when evidence-based approaches are being strongly promoted by educational systems across Australia
Performance Modeling and Analysis of Network Firewalls

Network firewalls act as the first line of defense against unwanted and malicious traffic targeting Internet servers. Predicting the overall firewall performance is crucial to network security engineers and designers in assessing the effectiveness and resiliency of network firewalls against DDoS (Distributed Denial of Service) attacks as those commonly launched by today's Botnets. In this paper, we present an analytical queueing model based on the embedded Markov chain to study and analyze the performance of rule-based firewalls when subjected to normal traffic flows as well as DoS attack flows targeting different rule positions. We derive equations for key features and performance measures of engineering and design significance. These features and measures include throughput, packet loss, packet delay, and firewall's CPU utilization. In addition, we verify and validate our analytical model using simulation and real experimental measurements.
Zone classification for low-power active RFID tags

Radio Frequency Identification (RFID) and its localization capability have played a significant role in the advancement of the internet-of-things in recent years. In this preliminary work, we examine a statistical approach to perform zone classification based on RFID signal strength. A one-dimensional experimental test was conducted in an outdoor and corridor environment with clear line of sight between the RFID reader and the tags. This empirical study shows that 3 out of 4 zones can be distinguished by using mean and standard deviation of equally-spaced data samples within the zone.
Interactive Second Language Learning from News Websites

We propose WordNews, a web browser extension that allows readers to learn a second language vocabulary while reading news online. Injected tooltips allow readers to look up selected vocabulary and take simple interactive tests. We discover that two key system components needed improvement, both which stem from the need to model context. These two issues are real-world word sense disambiguation (WSD) to aid translation quality and constructing interactive tests. For the first, we start with Microsoft’s Bing translation API but employ additional dictionary-based heuristics that significantly improve translation in both coverage and accuracy. For the second, we propose techniques for generating appropriate distractors for multiple-choice word mastery tests. Our preliminary user survey confirms the need and viability of such a language learning platform.
A novel model for the interpretation of the unidentified infrared (UIR) bands from interstellar space: deexcitation of Rydberg Matter

The so called unidentified infrared (UIR) emission bands, observed from interstellar space for more than 25 years, are presently believed to be due to carbonaceous material in some form, for example polycyclic aromatic hydrocarbons (PAHs). However, the evidence is based on absorption data, which clearly is not adequate due to differences in the pro- cesses, for example the thermal factor. It also seems doubtful that enough carbon is available to form all the required PAHs, and that the vapor pressure is high enough to keep almost all such molecules in the gas phase. We now report on a model in which all UIR bands are due to electronic deexcitation in the condensed phase named Rydberg Matter. This type of very low- density condensed matter is formed by condensation of Rydberg states of almost any type of atom or small molecule, in space mainly hydrogen atoms and molecules. The intial formation of Rydberg states is due to desorption of alkali atoms from surfaces of small particles, especially carbon particles. This desorption can be caused by radiation or moderate heat and gives long- lived circular Rydberg states. Rydberg Matter can be produced in macroscopic quantities in the laboratory. There is no lower gas density limit for its formation. All the reported UIR peaks from different objects fall within the bands for deexcitation from Ryd- berg Matter states with principal quantum numbersn = 40-200. Most of the transitions are two-electron deexcitation processes, but also one-electron capture processes are identified. The UIR spectra of type sA-Dc anb eunderstood within this model. The agreement with observations is better for the Rydberg Mat- ter model, with small a priori information content, than for the current PAH model.
Implementation Of Police Academy Information System In Learning Management At Police Academy Semarang

Learning management in Police Academy Educational Institutes and Training is covers planning, implementing, evaluating and controlling. But, there are some lectures that use monotonous lecturing on the lesson plan and most of students feel less concentration about it. The aim of this study is to analyse implementation of Police Academy Information System (SIAK) in order to support learning management process. This research is done by using qualitative descriptive approach to solve it. Variables of the research are management, learning, learning management, and SIAK (Police Academy Information System). The primary data obtained from interview and observation. The secondary data obtained from through documentation. Technique analysis data is data triangulation. The results of this study have shown that the lesson plan which is composed by lectures use monotonous lecturing as learning method on the planning stages in each meeting. The conclusion is SIAK is able to use easily by the lectures and the students although they don’t operate it effectively.
Rating and rewarding higher education for sustainable development research within the marketised higher education context: experiences from English universities

Abstract This paper explores one key aspect of marketisation in English universities, the quality-related research funding (QR) system, which central government in the United Kingdom uses to allocate funds to Higher Education Institutions (HEIs), based on a system of reviewing and rating the ‘quality’ of research at different HEIs. Specifically, it focuses on the experiences of 30 members of academic staff from eight universities across England who were engaged in research and/or scholarly activity in the broad field of Higher Education for Sustainable Development (HESD), during the time leading up to the 2014 Research Excellence Framework (REF) submission period. Interviewees were asked to talk about their experiences of being a HESD researcher/scholar within the context of the QR system and their perceptions of the relationship between the QR system and interdisciplinary, sustainability, pedagogic and HESD research. Findings from the semi-structured interviews and resulting qualitative analysis, reveal a number of obstacles facing HESD researchers which are outlined and explored in the paper. Strategies and rationale for improving the quality, reputation and ultimately, the ‘REF-ability’ of HESD research are discussed, and highlight the complex interface between marketisation and sustainability in higher education.
Two Problems of Wavelet Packet Transform

Wavelet packet transform (WPT) is a useful tool for time-frequency analysis. The WPT based on discrete wavelet transform (DWT) has a well-known problem. It is called shift-variance behavior. It varies the energy of DWT result and fails to detect a changing-point even when an original signal shifts only by one sample. Although the solution of multi-resolution analysis (MRA) by using the complex DWT has been released, many reports about the WPT do not accomplish shift-invariance. In this paper, we describe the reason not to complete the shift-invariance for the WPT. In the complex MRA, it constructs a theoretical structure of a parallel DWT with one sample delayed. However the WPT partly achieves it. In addition, the WPT evenly divides a frequency band into 2n parts where n is the decomposition level. Each band is placed in the wrong frequency order. Whenever high-pass filtered signals are down sampled, the origin of the frequency axis is translated to. We show how to make the correct order. The two problems of the shift-invariance and the wrong frequency order are solved.
Multi-objective parameters optimization of electric assist control strategy for parallel hybrid electric vehicle

To manage the drivestrain and power flow of hybrid electric vehicle (HEV) and achieve balanced performances on fuel economy, emissions, grade ability and acceleration ability, it is necessary to develop a control system with suitable parameters by solving a multi-objective optimization problem. Based on the proof of the relationship between dominating number and diversity in objective-space, a dominating number based multi-objective genetic algorithm is proposed to enhance the diversity of Pareto-front and has been applied to optimize parameters of electric assist control strategy for parallel HEV under standard test procedure provided in Advisor. Simulations under four drive cycles demonstrate availability and efficacy of the proposed algorithm.
Hyperspectral image lossless compression using DSC and 2-D CALIC

In recent few years, DSC (Distributed Source Coding) technology is catched much attentions in remote sensing image compression field,due to its excellent performance and low encoding complexity. In this paper, we propose a DSC-based practical solution for hyperspectral image lossless compression system, which applies the DSC technique using the power channel codes of Low-Density-Parity-Check Accumulated(LDPCA) codes and incorporates an efficient 2-D Context-Based Adaptive Lossless Image Coding (2-D CALIC) prediction. The performance is evaluated on a few hyperspectral data, and the results demonstrate that our proposed scheme is appropriate for hyperspectral image lossless compression and applied to similar binary DSC coder, it indicates that the complexity is significantly reduced at encoder.
An Approach to Incorporating Psychology into Economics

This article proposes an approach to improving the psychological realism of economics while maintaining its conventional techniques and goals--formal theoretical and empirical analysis using tractable models, with a focus on prediction and estimation. Besides tolerating the imperfections that come with precision, models should aim for two crucial criteria: power and scope. The approach advocated is to develop portable extensions of existing models that embed preexisting theories as parameter values, while introducing the new psychological assumptions as alternative parameter values, and make the model portable by defining it in all cases where existing models make predictions.
Bacteriophage-Derived Vectors for Targeted Cancer Gene Therapy

Cancer gene therapy expanded and reached its pinnacle in research in the last decade. Both viral and non-viral vectors have entered clinical trials, and significant successes have been achieved. However, a systemic administration of a vector, illustrating safe, efficient, and targeted gene delivery to solid tumors has proven to be a major challenge. In this review, we summarize the current progress and challenges in the targeted gene therapy of cancer. Moreover, we highlight the recent developments of bacteriophage-derived vectors and their contributions in targeting cancer with therapeutic genes following systemic administration.
Climate Change Impacts and Market Driven Adaptation: The Costs of Inaction Including Market Rigidities

This paper presents a first exercise comparing the cost of climate change stemming from integrated assessment models using reduced-form climate change damage functions with that performed by a CGE model. Furthermore, it investigates the role of market driven adaptation, which CGE models explicitly capture through their endogenous price setting mechanism, in determining these estimates. It is shown that world GDP losses computed by the CGE model are not significantly different from that used by some well-established hard-linked integrated assessment models when they consider the same impact categories. Specifically, the major driver of impacts is the modelling of catastrophic outcomes. Then, rigidities in market adjustments, differently said, in market-driven adaptation, are introduced. This is done restricting the elasticity of input substitution in the production function, the substitutability of domestic and imported inputs, and finally sectoral workforce mobility. We demonstrate that notwithstanding these frictions do increase the cost of climate change impacts they do not change substantively neither the qualitative nor the quantitative picture.
The Learning Styles Myth is Thriving in Higher Education

The existence of ‘Learning Styles’ is a common ‘neuromyth’, and their use in all forms of education has been thoroughly and repeatedly discredited in the research literature. However, anecdotal evidence suggests that their use remains widespread. This perspective article is an attempt to understand if and why the myth of Learning Styles persists. I have done this by analyzing the current research literature to capture the picture that an educator would encounter were they to search for “Learning Styles” with the intent of determining whether the research evidence supported their use. The overwhelming majority (89%) of recent research papers, listed in the ERIC and PubMed research databases, implicitly or directly endorse the use of Learning Styles in Higher Education. These papers are dominated by the VAK and Kolb Learning Styles inventories. These presence of these papers in the pedagogical literature demonstrates that an educator, attempting to take an evidence-based approach to education, would be presented with a strong yet misleading message that the use of Learning Styles is endorsed by the current research literature. This has potentially negative consequences for students and for the field of education research.
Weather-index drought insurance in Burkina-Faso: assessment of its potential interest to farmers using historical data

Abstract By using a detailed agricultural and climate dataset over Burkina-Faso and simple assumptions regarding the form of an insurance contract, the authors investigate the potential economic efficiency for farmers of a weather-index insurance system in this country. To do so, the results of more than 3000 simulated contracts applied to 30 districts, 21 yr (1984–2004), and five crops (cotton, millet, sorghum, maize, and groundnut) are explored. It is found that such an insurance system, even based on a simple weather index like cumulative rainfall during the rainy season, can present a significant economic efficiency for some crops and districts. The determinants of the efficiency of such contracts are analyzed in terms of yield/index correlations and yield variability. As a consequence of these two main determinants, the farmer’s gain from an insurance contract is higher in the driest part of the country. In the same way, maize and groundnuts are the most suitable to implement an insurance system sinc.
Enhancing value via cooperation: firms' process benefits from participation in a standard consortium

Firms benefit from participating in a consortium in two ways: from the final products and from the cooperation process. We define the latter as process benefits, which include both inter-organizational learning benefits and social capital benefits. This paper examines the drivers of these two types of process benefits. Based on 232 surveys collected from seven e-business standard consortia, our empirical findings show that firms expect more process benefits if they are more technically capable, value the final output higher, and participate in a better-managed consortium. Among the three, standard valuation is the most influential factor, indicating that the output benefits and process benefits are highly correlated. Surprisingly, within standard consortia, we also find that relational risk does not have a statistically significant impact on process benefits.
Measuring and modeling distraction by self-referential processing in a complex working memory span task

Two experiments using novel complex working memory span tasks were performed, both requiring the participants to remember a span of letters whilst being distracted by the processing of words. Word processing could either be selfreferential (SRP) or not. In the first experiment recall performance was compared between SRP and non-SRP conditions using the same words. In the second experiment, we compared SRP and non-SRP in two tasks equalized in semantic processing but using different words. In both experiments recall performance was significantly lower after SRP compared to non-SRP, indicating that SRP has a disruptive effect on the recall task. A cognitive model implemented in PRIMs, using goal competition during SRP, interfering with rehearsal of letters, could account for the observed experimental results. If SRP interferes with subsequent tasks in this manner it should also interfere with tasks other than recall, such as SRP occurring in daily life.
High Degree Vertices and Eigenvalues in the Preferential Attachment Graph

The preferential attachment graph is a random graph formed by adding a new vertex at each time-step, with a single edge which points to a vertex selected at random with probability proportional to its degree. Every m steps the most recently added m vertices are contracted into a single vertex, so at time t there are roughly t/m vertices and exactly t edges. This process yields a graph which has been proposed as a simple model of the World Wide Web [Barabási and Albert 99]. For any constant k, let Δ1 ≥ Δ2 ≥ … ≥ Δk be the degrees of the k highest degree vertices. We show that at time t, for any function ƒ with ƒ(t)→ ∞ as , and for , with high probability (whp). We use this to show that at time t the largest k eigenvalues of the adjacency matrix of this graph have λ k = (1 ± o(1))Δ k 1/2 whp.
Route-Exchange Algorithm for solving assignment problems based on swarm intelligence

Inspired by interaction behaviors of individuals in swarm intelligence, a novel algorithm for combinatorial optimization is proposed, which is called as Route-Exchange Algorithm (REA). In the heuristic approach, individuals of a swarm search the state space independently and simultaneously. When one encounters another in the process, they would interact with each other, exchange the information of routes toured, and utilize the more valuable experiences to improve their own search efficiency. In this paper, the algorithm is applied to assignment problem and quadric assignment problem. The experiment results indicate the algorithm can quickly converge to the optimal solution with quite low cost.
Instructional Practices Related to Standards and Assessments

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