Miracle-dz/UniFAR-FTUs huggingface dataset:
A HYBRID ARTIFICIAL BEE COLONY ALGORITHM FOR PORTFOLIO OPTIMIZATION PROBLEM

In this paper, a constrained mean-variance model is constructed for the portfolio optimization problem s. The model is a mixed quadratic integer programming problem, and it is too hard to solve by using the traditional optimal algorithms. The purpose of this paper is to use a heuristic algorithm to solve thi s problem. Combined with the differential evolution s trategy, a new hybrid artificial bee colony algorit hm is proposed for solving the constrained mean-variance model. In the new hybrid artificial bee colony algorithm, a new search scheme and obsolete rules a re presented to improve convergent speed of the algorithm. Computational results show that the algo rithm has great capability to solve the portfolio optimization problem. It supplies a new method for s lving the portfolio optimization problem.
ROBotic Open-architecture Technology for Cognition, Understanding and Behavior

Within the field of Neuro Robotics we are driven primarily by the desire to understand how humans and animals live and grow and solve every day’s problems. To this aim we adopted a “learn by doing” approach by building artificial systems, e.g. robots that not only look like human beings but also represent a model of some brain process. They should, ideally, behave and interact like human beings (being situated). The main emphasis in robotics has been on systems that act as a reaction to an external stimulus (e.g. tracking, reaching), rather than as a result of an internal drive to explore or “understand” the environment. We think it is now appropriate to try to move from acting, in the sense explained above, to “understanding”. As a starting point we addressed the problem of learning about the effects and consequences of self-generated actions. How does the robot learn how to pull an object toward itself or to push it away? How does the robot learn that spherical objects roll while a cube only slides if pushed? Interacting with objects is important because it implicitly explores object representation, event understanding, and can provide definition of objecthood that could not be grasped with a mere passive observation of the world. Further, learning to understand what one’s own body can do is an essential step toward learning by imitation. In this view two actions are similar not only if their kinematics and dynamics are similar but rather if the effects on the external world are the same. Along this line of research we discuss some recent experiments performed at the AILab at MIT and at the LIRA-Lab at the University of Genova on COG and Babybot respectively. We show how the humanoid robots can learn how to poke and prod objects to obtain a consistently repeatable effect (e.g. sliding in a given direction), to help visual segmentation, and to interpret a poking action performed by a human manipulator.
Troubling normal in world language education

ABSTRACT Queer theory problematizes societal norms related to sex, gender, and sexuality, while resisting normalcy. The authors utilize a queer theoretical approach in analysis of participant observation in adult Spanish and Mandarin classes as well as interviews with world language teachers. Analysis of interview data reveals how educators and adult language learners experience gender/sexuality norms in conventional classroom and school contexts. Classroom observations and analysis of classroom discourse identify moments when these norms may be “troubled” or upheld in contexts using a progressive new approach called Teaching Proficiency through Reading and Storytelling (TPRS). Findings suggest that the improvisational nature of TPRS raises complex questions about heteronormativity in language learning and the creative work in which educators and students can engage in dialogic classrooms.
A Hybrid Channel Allocation Algorithm using Hot-Spot Notification for Wireless Cellular Networks

The enormous growth of mobile telephone traffic, along with the limited number of channels available, requires efficient reuse of channels. Channel allocation schemes can be divided into three categories: fixed channel allocation (FCA), dynamic channel allocation (DCA), and hybrid channel allocation (HCA). In HCA, channels are divided into two disjoint sets: one set of channels is assigned to each cell on FCA basis, while the others are kept in a central pool for dynamic assignment. This paper presents a new hybrid channel allocation algorithm that sends a multi-level "hot-spot" notification to the central pool on each channel request that cannot be satisfied locally at the base station. This notification requests more than one channel be assigned to the requesting cell, proportional to the current hot-spot level of the cell. When a call using such a "borrowed" channel terminates, the cell may retain the channel depending upon its current hot-spot level. The simulation study of the protocol indicates that the protocol has low overhead, and it behaves similar to the FCA at high traffic and to the DCA at low traffic loads
Genetic programming evolved spatial descriptor for Indian monuments classification

Travel and tourism are the largest service industries in India. Every year people visit tourist places. and upload pictures of their visit on social networking sites or share via mobile device with friends and relatives. Millions of such photographs are uploaded and it is almost impossible to manually classify these pictures as per the monuments they have visited. Classification is helpful to hoteliers for development of new hotel with state of the art amenities, to travel service providers, to restaurant owners, to government agencies for security etc. The proposed system extracts Genetic programming evolved spatial descriptor and classifies the Indian monuments visited by tourists based on linear Support Vector Machine(SVM). The proposed system is divided into 3 main phases: preprocessing, genetic programming evolution and classification. The Preprocessing phase converts images into a form suitable for processing by genetic programming system using Generalized Co-Occurrence Matrix. The second phase generates best so far spatial descriptor in the form of program based on the fitness. The Fitness is calculated using SVM. Once program is obtained as output it can be utilized for classification. The proposed system is implemented in MATLAB and achieves high accuracy.
MACRO AND MICROHABITAT PATTERNS OF HABITAT USE AND SELECTION BY WILD BOAR IN LOS ALERCES NATIONAL PARK

The wild boar (Sus scrofa) is an invasive species and currently considered as one of the most dangerous species around the world. Although its negative impacts on ecosystems have been broadly described, little is known about its patterns of habitat use in protected areas of South America. In this study, we assessed macro and microhabitat patterns of habitat use and selection of wild boar in Los Alerces National Park, Argentina, during two contrasting study periods (spring-summer and autumn-winter). We surveyed 115 sampling plots to estimate use and availability of macrohabitat and microhabitat variables. Our results showed that Lomatia hirsuta forest was selected at the macrohabitat scale in both study periods, while Nothofagus pumilio forest and Valdivian evergreen rainforest were used significantly less than their availability, and therefore, they were avoided. At a microhabitat scale, we found that wild boars used low slopes and high canopy covers. The use of L. hirsuta forest was also associated with SE exposure and intermediate proportion of ground cover. This study is one of the first attempts to assess wild boar habitat use and selection at two scales in protected areas dominated by temperate forest in Patagonia and the results obtained might be helpful to design management actions to control this invasive species and understand its ecological role. RESUMEN. Patrones de uso y selección de macro y microhábitat del jabalí en el Parque Nacional Los Alerces. El jabalí (Sus scrofa) es una especie invasora que actualmente está considerada como una de las especies más dañinas del mundo. Aunque sus impactos negativos en los ecosistemas han sido ampliamente descritos, poco se sabe sobre sus patrones de uso y selección de hábitat en las áreas protegidas de América del Sur. En este estudio, se evaluaron los patrones de uso y selección de hábitat del jabalí a escalas de macro y micro-hábitat en el Parque Nacional Los Alerces, Argentina, durante dos periodos de estudio contrastantes (primavera-verano y otoño-invierno). Se relevaron 115 parcelas de muestreo para estimar el uso y la disponibilidad de variables de macrohábitat y de microhábitat. Nuestros resultados mostraron que, a escala de macrohábitat, el bosque de Lomatia hirsuta fue seleccionado en ambos periodos de estudio, mientras que el bosque de Nothofagus pumilio y la selva valdiviana se usaron significativamente menos que su disponibilidad, y por lo tanto, fueron seleccionados negativamente. A escala de microhábitat, se observó que el jabalí utilizó pendientes bajas y altas coberturas de dosel. El uso del bosque de Lomatia hirsuta también se asoció con la exposición SE y una proporción intermedia de la cobertura vegetal. Este estudio representa uno de los primeros intentos por evaluar el uso y la selección de hábitat del jabalí a dos escalas en áreas protegidas dominadas por bosques templados en la Patagonia, y los Mastozoología Neotropical, 26(1):143-154, Mendoza, 2019 http://www.sarem. org.ar http://www.sbmz. com.br A. Panebianco et al. 144
Distributed intrusion detection using mobile agents against DDoS attacks

Along with the increasing wide applications of computer and network technologies, the security problems of information systems are becoming more complicated. Most computer systems have some kind of a security flaw that may allow outsiders or legitimate users to gain unauthorized access to sensitive information. Among the network exploits, Distributed Denial of Service (DDoS) attack is a large-scale, coordinated attack on the availability of services of a victim system, launched indirectly through many compromised computers on the Internet. Intrusion detection systems (IDS) are network security tools that process local audit data or monitor network traffic to search for specific patterns or certain deviations from expected behavior which indicate malicious activities against the protected network. In our study, we proposed and tested four different distributed intrusion detection methods to detect DDoS attacks in the MIT DARPA LLDOS 1.0 dataset. Currently, all of our methods use the alarms generated by Snort, a signature-based network IDS. We used mobile agents in three of the methods on the Jade (Java Agent Development Framework) platform in order to reduce network bandwidth usage by moving data analysis computations to the location of the intrusion data. Based on reliability, network load and mean detection time values of each, one of the methods is shown to be better than the others.
“No Facts Equals Unconvincing”: Fact and Opinion as Conceptual Tools in High School Students’ Written Arguments

In this study, I present a qualitative analysis of 11 writing portfolios drawn from a yearlong instructional program designed to apprentice students into the practices of argumentative writing typical of early-college coursework in the United States. The students’ formal and informal writings were parsed into utterances and coded along two developmental dimensions: reciprocity, or the extent to which each utterance answered to the immediate context in which it was generated; and indexicality, or the extent to which each utterance evidenced modes of reasoning that reflect the conventions of academic argumentation. My analysis found that although students’ writing evidenced a high degree of reciprocity, they frequently employed nonacademic modes of reasoning. Focusing on a subset of utterances, I show how their tacit orientations toward the concepts of fact and opinion limited the extent to which their reasoning satisfied the evidentiary expectations of formal academic discourse. This discovery suggests that students’ development as writers of academic arguments is closely linked to their formal instruction in argumentative writing as well as to their tacit understandings of concepts fundamental to argumentation. Moreover, these findings highlight important distinctions between formal and informal reasoning and how those distinctions may be implicated in both curriculum and instruction.
Feature Normalisation for Robust Speech Recognition

Speech recognition system performance degrades in noisy environments. If the acoustic models are built using features of clean utterances, the features of a noisy test utterance would be acoustically mismatched with the trained model. This gives poor likelihoods and poor recognition accuracy. Model adaptation and feature normalisation are two broad areas that address this problem. While the former often gives better performance, the latter involves estimation of lesser number of parameters, making the system feasible for practical implementations. This research focuses on the efficacies of various subspace, statistical and stereo based feature normalisation techniques. A subspace projection based method has been investigated as a standalone and adjunct technique involving reconstruction of noisy speech features from a precomputed set of clean speech building-blocks. The building blocks are learned using non-negative matrix factorisation (NMF) on log-Mel filter bank coefficients, which form a basis for the clean speech subspace. The work provides a detailed study on how the method can be incorporated into the extraction process of Mel-frequency cepstral coefficients. Experimental results show that the new features are robust to noise, and achieve better results when combined with the existing techniques. The work also proposes a modification to the training process of SPLICE algorithm for noise robust speech recognition. It is based on feature correlations, and enables this stereo-based algorithm to improve the performance in all noise conditions, especially in unseen cases. Further, the modified framework is extended to work for non-stereo datasets where clean and noisy training utterances, but not stereo counterparts, are required. An MLLR-based computationally efficient run-time noise adaptation method in SPLICE framework has been proposed.
Joint Spectrum estimation of Polarization and Space

The Joint Spectrum of Polarization and Space is constructed for the first time, which can depict the EM signal more completely. Based on the polarization sensitive antenna array, the joint spectrum is defined and the analytic function of joint spectrum is presented by MUSIC method. The discrimination power of joint spectrum is discussed theoretically in details. The polarization domain does not provide the same resolution capabilities as the other domains, when exploited alone. The simulations verify the superiority of the joint spectrum and coincide with the theoretical analysis. It is shown that the joint spectrum outperforms the spatial spectrum in characteristic detection and estimation.
Embedding Intelligence: Research Issues for Ubiquitous Computing

Summary: In this paper we discuss the need for new technologies to enable the full benefits of ubiquitous computing to be realised in domestic environments. We argue that a key aspect of such new technology is that of embedding intelligence into devices. We do this by explaining the enhanced functionality that embedded-intelligence can provide to everyday products. In particular we describe how intelligence is the key to groups of artefacts learning to work together to achieve higher level, user-determined goals. We outline a scenario for an “Intelligent Domestic Environment” based on an Intelligent Student Dormitory (iDorm) being built at the University of Essex that will allow experimentation on “cognitive disappearance” of explicit control of devices arising from a networked system of intelligent artefacts. We explain the challenges facing those seeking to develop methods of embedding intelligent into computationally compact and distributed co-operating artefacts. Finally we summarise our arguments as to why “cognitive disappearance” requires intelligent artefacts and describe some of the projects we are working on that address these underlying research issues. 1.0 Introduction 1.1 The Vision Today people’s domestic spaces are becoming increasingly “decorated” by electronic or computer-base d artefacts (gadgets) varying from, mobile telephones through CD players to transport systems and beyond. The variety of computer-based artefacts, and their capabilities, is growing at an unprecedented rate fuelled by advances in microelectronics and Internet technology. Cheap and compact microelectronics means most everyday artefacts (e.g. shoes, cups) are now potential targets of embedded-computers, while ever-pervasive networks will allow such artefacts to be associated together in both familiar and novel arrangements to make highly personalised systems. However, in order to realise this possibility, technologies must be developed that will support ad-hoc and highly dynamic (re)structuring of such artefacts whilst shielding non-technical users from the need to understand or work directly with the technology “hidden” inside such artefacts or systems of artefacts. How can this aim be achieved? The authors are part of the eGadgets project [http://www.extrovert-gadgets.net] which is funded by the EU “Disappearing Computer” programme and in this paper we will describe how embedding intelligence into artefacts in the form of embedded-agents could provide one viable solution.
Procedia Social and Behavioral Sciences Empirical Study of Cost Management Success Determinants in Agile Based Software Development Project: a Rasch Measurement Model Analysis

Ineffective cost management in software development causes project over budget and strongly contributed to project failure. Due to that, it is important to look at the success determinants that help software development community to have better cost management of the project. This paper identifies the success determinants in agile based software development project. The online survey is used in order to collect data from the respondents which involve in the cost management process in the company in Malaysia. This study used Rasch Measurement Model to analyze the result. Preliminary findings show a small number of respondents and the respondents are not representing the sampling unit becomes a problem to generalize the result. As a result, this study provides very low item reliability and person reliability is acceptable. Therefore, more feedback from respondent is needed in order to increase the item and person reliability
Software Defined Networking: Identification of Pathways for Security Threats

As Industries and Data Center plan to implement Software Defined Networking (SDN), the main concern is the anxiety about security. The Industries and Data Centers are curious to know how a SDN product will support them that their data, supporting applications and built in infrastructure are not vulnerable to threats. The initiation of SDN, will demand new pathways for securing control plane traffic. The traditional networks usually trust switching intelligence to implement various defense mechanisms besides known attacks. Many attacks which distress traditional networks also affect SDNs, partially due to SDN architecture complexities and most prominent among them is DoS. This paper identifies the pathways of threats to SDN systems and discuss methods to ways to mitigate them.
Into the Void: The Gap Between N-Back and Complex Span Tasks Suggests Inadequacies in Current Models of Working Memory

The tasks used to assess working memory are a highly contentious issue in cognitive psychology. Previous research has found a weak relationship between two key types of working memory tasks: N-Back and Complex Span. This is commonly interpreted as evidence that one or both tasks possess poor construct validity. However, this finding may be a result of assessing different modalities of working memory. The current pilot study aimed to clarify the differences between the two tasks by assessing performance on each within the same modality. A spatial and verbal version of each task was used. Although, theoretically, these tasks assess the same construct, the pilot data revealed low correlations between them. This suggests that the current models of working memory may be inadequate, or that unidentified differences between the tasks may be influencing the results. Due to their widespread use and applications, it is important to better understand models of working memory and develop improved tasks.
An interactive bulletin board with mobile devices

An interactive bulletin board is a system for interchanging information between a public screen and a mobile device. Nowadays, there are many studies on interactions between different devices such as a Microsoft Surface and a smart board. For an interactive bulletin board, we propose a marker detection method that relies on the camera of a mobile device. Our proposed system, which has some advantages over other works, needs no particular hardware, such as a projector, a touch screen, or a special camera. Moreover, the whole process can be simply performed with actions that are similar to the act of attaching a memo to a bulletin board.
The Chandra view of extended X-ray emission from Pictor A

We discuss the extended X-ray emission seen in three archival Chandraobservations, and one archival XMM-Newtonobservation, of the FRII radio galaxy Pictor A. The overall properties of the X-ray lobes are consistent with the conclusions of earlier workers that the extended X-ray emission is largely due to the inverse-Compton process, and the implied departure from equipartition is in the range seen by us in other sources. In d etail, we show that the X-ray/radio flux ratio varies quite strongly as a function of position thr oughout the source, and we discuss possible implications of this observation for the spatial v ariation of electron energy spectra and magnetic field strength through the lobe. We show that the rad io and X-ray properties of the lobe are not consistent with a simple model in which variations in the magnetic field strength alone are responsible for the observed differences between emission at different frequencies. We also discuss the origins of the extended emission seen around the eastern hotspot, arguing that it may be diffuse synchrotron radiation tracing a regio n of distributed particle acceleration, and the implications of a possible weak X-ray counterjet detection which, taken together with the other properties of the bright X-ray jet, leads us to suggest that the X-ray jet and possible counterjet are also produced by synchrotron emission.
Expert Teachers : Their Characteristics , Development and Accomplishments

In the 1980s new methods and findings from cognitive psychology began to influence research on teaching. The emerging literature on commonalities in expertise across different fields seemed pertinent to educational researchers because it appeared to describe characteristics of effective teachers. So without much theory to guide them, a few scholars began to explore expertise in teaching and this work produced some well-warranted assertions about expertise in pedagogy (Berliner, 1987; 1994a; 1994b; 2001).