Miracle-dz/UniFAR-FTUs huggingface dataset:
A Genetic Algorithm for Function Optimization: A Matlab Implementation

A genetic algorithm implemented in Matlab is presented. Matlab is used for the following reasons: it provides many built in auxiliary functions useful for function optimization; it is completely portable; and it is e cient for numerical computations. The genetic algorithm toolbox developed is tested on a series of non-linear, multi-modal, non-convex test problems and compared with results using simulated annealing. The genetic algorithm using a oat representation is found to be superior to both a binary genetic algorithm and simulated annealing in terms of e ciency and quality of solution. The use of genetic algorithm toolbox as well as the code is introduced in the paper.
ANALISIS PERATAAN LABA (INCOME SMOOTHING) : Faktor-Faktor yang Mernpengaruhi dan Kaitannya dengan Kinerja Saham Perusahaan Publik di Indonesia

The objective of research is to analysis any factors which its influencing to income smoothing and its correlation to stock performance (return and risk) of public companies in Indonesia. Data of this research were obtained from 30 companies listed in Jakarta Stock Exchange which have been selected using (purposive) judgment sampling method. Samples were classified to be smoother and non smootherusing Eckel's model (1981). Eckel model classification in this research use three object of variable of income : operation income, income before tax, and income after tax. Test of One-Sample Kolmogmv Smimov, Mann-Whitney, t-Test, and Mult4variate Logistics were used for data analysing. The result of this research indicate that the coefficient variation of operating income and income before tax shows that: company size, net profit margin (NPM), industrial sector, and winnernosser stocks are not influencing income smoothing. Based on coefficient of variation of income after tax indicates that company size, net profit margin (NPM), and industrial sector are not influencing income smoothing while winner/losser stocks influence income smoothing. And it also indicated that there are not difference return between smoother and non smoother. The risk also is not different between them. Keywords: income smoothing, return, risk,
Analyzing Credit Risk Data: A Comparison of Logistic Discrimination, Classification Tree Analysis, a

Three different discriminant techniques are applied and compared to analyze a complex data set of credit risks. A large sample is split into a training, a validation, and a test sample. The dependent variable is whether a loan is paid back without problems or not. Predictor variables are sex, job duration, age, car ownership, telephone ownership, and marital status. The statistical techniques are logistic discriminant analysis with a simple mean effects model, classification tree analysis, and a feedforward network with one hidden layer consisting of three units. It turns out, that in the given test sample, the predictive power is about equal for all techniques with the logistic discrimination as the best technique. However, the feedforward network produces different classification rules from the logistic discrimination and the classification tree analysis. Therefore, an additional coupling procedure for forecasts is applied to produce a combined forecast. However, this forecast turns out to be slightly worse than the logit model.
RSQ: a statistical method for quantification of isoform-specific RSQ: a statistical method for quantification of isoform-specific structurome using transcriptome-wide structural profiling data structurome using transcriptome-wide structural profiling data

: The structure of RNA, which is considered to be a second layer of information alongside the genetic code, provides fundamental insights into the cellular function of both coding and non-coding RNAs. Several high-throughput technologies have been developed to profile transcriptome-wide RNA structures, i.e., the structurome. However, it is challenging to interpret the profiling data because the observed data represent an average over different RNA conformations and isoforms with different abundance. To address this challenge, we developed an RNA structurome quantification method (RSQ) to statistically model the distribution of reads over both isoforms and RNA conformations, and thus provide accurate quantification of the isoform-specific structurome. The quantified RNA structurome enables the comparison of isoform-specific conformations between different conditions, the exploration of RNA conformation variation affected by single nucleotide polymorphism (SNP) , and the measurement of RNA accessibility for binding of either small RNAs in RNAi-based assays or RNA binding protein in transcriptional regulation. The model used in our method sheds new light on the potential impact of the RNA structurome on gene regulation.
An Analysis of the Control Hierarchy Modelling of the CMS Detector Control System

The supervisory level of the Detector Control System (DCS) of the CMS experiment is implemented using Finite State Machines (FSM), which model the behaviours and control the operations of all the sub-detectors and support services. The FSM tree of the whole CMS experiment consists of more than 30.000 nodes. An analysis of a system of such size is a complex task but is a crucial step towards the improvement of the overall performance of the FSM system. This paper presents the analysis of the CMS FSM system using the micro Common Representation Language 2 (mcrl2) methodology. Individual mCRL2 models are obtained for the FSM systems of the CMS sub-detectors using the ASF+SDF automated translation tool. Different mCRL2 operations are applied to the mCRL2 models. A mCRL2 simulation tool is used to closer examine the system. Visualization of a system based on the exploration of its state space is enabled with a mCRL2 tool. Requirements such as command and state propagation are expressed using modal mu-calculus and checked using a model checking algorithm. For checking local requirements such as endless loop freedom, the Bounded Model Checking technique is applied. This paper discusses these analysis techniques and presents the results of their application on the CMS FSM system.
Seoul: Birth of a Broadband Metropolis

Following a half-century of breakneck urbanization, the capital of South Korea emerged in the late 1990s as the world’s most digitally networked city. With nearly 80 percent household broadband penetration in 2004, Seoul surpassed both global cities and ‘technopoles’ in speed and comprehensiveness in embracing broadband technology. This article describes the physical development of Seoul’s broadband infrastructure and its frequent intersections with daily urban life. As the world’s fourth largest urban agglomeration, Seoul offers a unique case for investigating the intersection of telecommunications policy, development, and culture in large metropolitan regions, as well as the everyday implications of pervasive computing. It also highlights emerging challenges and opportunities presented by the rapid and widespread deployment of digital network infrastructure.
- 1-A Methodology for Validating Software Product Metrics

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A ug 2 01 5 BUILDING

The game of nim, with its simple rules, its elegant solution and its historical importance is the quintessence of a combinatorial game, which is why it led to so many generalizations and modifications. We present a modification with a new spin: building nim. With given finite numbers of tokens and stacks, this two-player game is played in two stages (thus belonging to the same family of games as e.g. nine-men’s morris): first building, where players alternate to put one token on one of the, initially empty, stacks until all tokens have been used. Then, the players play nim. Of course, because the solution for the game of nim is known, the goal of the player who starts nim play is a placement of the tokens so that the Nim-sum of the stack heights at the end of building is different from 0. This game is trivial if the total number of tokens is odd as the Nim-sum could never be 0, or if both the number of tokens and the number of stacks are even, since a simple mimicking strategy results in a Nim-sum of 0 after each of the second player’s moves. We present the solution for this game for some non-trivial cases and state a general conjecture.
Analysis of the potential of a wave energy conversion system for Maltese waters

This paper presents the analysis of waves in the Maltese waters. Through data analysis the results will highlight the most common waves together with others which yield the largest power. The paper also presents a novel type of wave energy converter with a hydraulic power take off system which is being proposed to be replaced by a linear electric machine. Thus wave data was also analysed with respect to this prototype design. However due to its operational characteristics the design is not an optimal one for the local waters and a point absorber type of converter is suggested. This mechanical structure, in conjunction with the linear machine, shall absorb more power from waves with a large wavelength and a relatively small wave height.
Fast Implementations of Algebraic Methods for 3D Reconstruction from Cone-Beam Data

The prime motivation of this work is to devise techniques that make the Algebraic Reconstruction Technique (ART) and related methods more efﬁcient for routine clinical use, while not compromising their accuracy. Since most of the computational effort of ART is spent for projection/backprojection operations, we ﬁrst seek to optimize the projection algorithm. Existing projection algorithms are surveyed and it is found that these algorithms either lack accuracy or speed, or are not suitable for cone-beam reconstruction. We hence devise a new and more accurate extension to the splatting algorithm, a well-known voxel-driven projection method. We also describe a new 3D ray-driven projector that is considerably faster than the voxel-driven projector, and at the same time more accurate and perfectly suited for the demands of cone-beam. We then devise caching schemes for both ART and Simultaneous ART (SART), which minimize the number of redundant computations for projection and backprojection and, at the same time, are very memory-conscious. We ﬁnd that with caching the cost for an ART projection/backprojection operation can be reduced to the equivalent cost of 1.12 projections. We also ﬁnd that SART, due to its image-based volume correction scheme, is considerably harder to accelerate with caching: Implementations of the algorithms yield runtime ratios T SART / T ART between 1.5 and 1.15, depending on the amount of caching used.
Series 2002 SWP 2002 / 28 Adding Value to Online Privacy for Consumers : Remedying Deficiencies in Online Privacy Policies With an Holistic Approach

Online privacy policies are important mechanisms for informing web site users about the level of information privacy protection afforded them when visiting web sites. To date, societal mechanisms and technologies have been the focus of attempts to improve the quality and effectiveness of online privacy policies. Little attention, however, has been given to the development and use of organisational measures for this purpose. In this paper we present findings from a longitudinal, empirical study of online privacy policies. Our research found that although online privacy policies have improved in quality and effectiveness since 2000, they still fall well short of the level of privacy assurance desired by consumers. This study has identified broad areas of deficiency in existing online privacy policies, and offers a solution in the form of an holistic framework for the development, factors and content of online privacy policies for organisations. Our study adds to existing theory in this area and, more immediately, will assist businesses concerned about the effect of privacy issues on consumer web usage.
Sampling inner experience in the learning disabled population

The inner experience of four learning disabled individuals and three undiagnosed individuals, ages 24 to 40 years, was investigated using the method of descriptive inner experience sampling (Hurlburt, 1990). This method requires that the subject "freeze" moments of inner experience when signaled by a randomly programmed beeping device, and write down the thoughts, feelings, images and/or other inner experiences occurring at that precise moment. Within 24 hours, the subject met with the experimenter and discussed in detail each sampled moment. The experimenter then prepared descriptions of each sampled moment, which were examined for salient charactistics which emerged from these descriptions. If was found that learning disabled individuals experience considerably less Inner Speech than most normal individuals, supporting the findings of other research that did not employ the thought sampling method. The learning disabled subjects also experienced Images, Feelings, and Unsymbolized Thinking more frequently than normal subjects. Three undiagnosed subjects were also examined in this manner. These subjects do not form a control group but are presented to add to the pool of subjects that have been sampled using this method.
Dunes and ocean front structures under wave attack

Sand dunes and sandbars which serve as natural protective barriers to ocean front structures on many beaches can undergo geological change due to wave action. Engineered structures such as concrete seawalls, stone revetments, and bulkheads can be damaged or destroyed by storm driven waves. Once these coastal defenses are eroded or destroyed by wave action landward buildings are vulnerable to wave attack. This paper focuses on the relationship of wave runup and setup to dune morphology and how wave forces directed at structures behind the dunes can be quantified. A comparison of wave forces to wind forces is made with the intention of demonstrating the dominance of wave action in producing damage to structures along the coast. Forecast techniques that allow wave action in the velocity zone to be integrated into operational forecasts are presented along with a case study of overwash during the 6-9 March 2013 Atlantic Storm. _____________________________________
Author’s Accepted Manuscript New trends in cognitive science: Integrative approaches to learning and development

A new trend in Cognitive Science is the use of artificial agents and systems to investigate learning and development of complex organisms in natural environments. This work, in contrast with traditional AI work, takes into account principles of neural development, problems of embodiment, and complexities of the environment. Current and future promises and challenges for this approach are defined and outlined. 1. Historical changes in Modeling: Towards Adaptive, Interactive Intelligence A widely circulated story about early Cognitive Science efforts has it that Marvin Minsky assigned an undergraduate student computer vision as a summer project. The anecdote builds irony with historical hindsight, as successive theoretical trends in the behavioral and computational sciences each have run into the barrier of Real Complexity: the monumentally interactive intricacies of organism-environment dynamics that give rise to human thought and action. Cognitive Scientists have repeatedly discovered that such prosaic skills as producing phonemes or tracking objects are quite challenging to model on anything approaching the scale of an actual organism. A growing appreciation for neural and cognitive complexity, anatomical structure and function of real organisms’ brains and bodies, and rich ecological structures have mandated a reconceptualization of models of intelligent behavior. The mandate is to push beyond the symbolic models of human information processing of the 1980’s and 1990’s, and to meaningfully elaborate on early work on neural networks by incorporating relevant information about neuroscience (e.
Installation, setup and use of a low cost c - band meteosat - 8 ground receiving station in Rwanda

This paper provides a description to setup and operate a low-cost Meteosat Second Generation ground receiving station. A C-band receiving configuration, relevant for Africa, is described using as an example the operational system at the Geographic Information Systems & Remote Sensing Research and Training Centre (CGIS) of the National University of Rwanda (NUR) in Butare. Additional software developed is firstly the MSG File-Manager, performing the data transfer between the receiving station and the data processing and archiving system in an orderly manner. Secondly, for data import, a software tool called the MSG DataRetriever is developed which facilitates the import of the raw compressed (time series) data into common used image processing software package formats. The data is geometrically and radiometrically calibrated during the import. Thirdly, in order to process the images additional tools to handle and analyse time series data are developed and integrated in the ILWIS software package (shareware). Procedures and software described are developed to ensure a low-cost alternative to build a Meteosat time series archive coupled with freeor shareware processing tools to retrieve (regular) products relevant for e.g. environmental and hydrological applications by non-meteorological organizations in Africa dealing with geo-spatial temporal data analysis.
A Review Paper on Green Cloud Computing-A New form of Computing

In cloud computing hosted services are delivered to users by using a network of remote servers over the internet. Cloud users are increasing day by day which has compelled the cloud service provider to open more data centers for hosting their services efficiently. The growing demand of Cloud computing has increased the energy consumption of cloud data centers dramatically. High energy consumption not only increases the operational cost but also reduces the profit margin of cloud service providers and affects the environment by its carbon emission. So, in order to make cloud computing an eco friendly technology some energy-efficient solutions are required. Hence, this paper is addressing the motivation and driving forces for green computing. It also discusses the key issues present in green cloud computing.
International Journal of Applied Sciences and Smart Technologies

Many people like traveling. However, often it is difficult for them to find a tourism site that they like much. Too many information about tourism is the problem. To overcome this problem, we need to filter the information. Recommender System could filter the information. By considering the advantages, the system used item-based collaborative filtering approach to give recommendation. Some tourism sites around Daerah Istimewa Yogyakarta province were used in this research. The system is able to give recommendation to users. The accuracy of the rating prediction is 0,6293 and the average time consumption is 1693,33 milliseconds.
An Algorithmic Diversity Diet? Questioning Assumptions behind a Diversity Recommendation System for PSM

: With the growing influence of personalized algorithmic recommender systems on the exposure of media content to users, the relevance of discussing the diversity of recommendations increases, particularly as far as public service media (PSM) is concerned. An imagined implementation of a diversity diet system however triggers not only the classic discussion of the reach – distinctiveness balance for PSM, but also shows that ‘diversity’ is understood very differently in algorithmic recommender system communities than it is editorially and politically in the context of PSM. The design of a diversity diet system generates questions not just about editorial power, personal freedom and techno-paternalism, but also about the embedded politics of recommender systems as well as the human skills affiliated with PSM editorial work and the nature of PSM content.
Interactive effects of wildfire and permafrost on microbial communities and soil processes in an Alaskan black spruce forest

Boreal forests contain significant quantities of soil carbon that may be oxidized to CO2 given future increases in climate warming and wildfire behavior. At the ecosystem scale, decomposition and heterotrophic respiration are strongly controlled by temperature and moisture, but we questioned whether changes in microbial biomass, activity, or community structure induced by fire might also affect these processes. We particularly wanted to understand whether postfire reductions in microbial biomass could affect rates of decomposition. Additionally, we compared the short‐term effects of wildfire to the long‐term effects of climate warming and permafrost decline. We compared soil microbial communities between control and recently burned soils that were located in areas with and without permafrost near Delta Junction, AK. In addition to soil physical variables, we quantified changes in microbial biomass, fungal biomass, fungal community composition, and C cycling processes (phenol oxidase enzyme activity, lignin decomposition, and microbial respiration). Five years following fire, organic surface horizons had lower microbial biomass, fungal biomass, and dissolved organic carbon (DOC) concentrations compared with control soils. Reductions in soil fungi were associated with reductions in phenol oxidase activity and lignin decomposition. Effects of wildfire on microbial biomass and activity in the mineral soil were minor. Microbial community composition was affected by wildfire, but the effect was greater in nonpermafrost soils. Although the presence of permafrost increased soil moisture contents, effects on microbial biomass and activity were limited to mineral soils that showed lower fungal biomass but higher activity compared with soils without permafrost. Fungal abundance and moisture were strong predictors of phenol oxidase enzyme activity in soil. Phenol oxidase enzyme activity, in turn, was linearly related to both 13C lignin decomposition and microbial respiration in incubation studies. Taken together, these results indicate that reductions in fungal biomass in postfire soils and lower soil moisture in nonpermafrost soils reduced the potential of soil heterotrophs to decompose soil carbon. Although in the field increased rates of microbial respiration can be observed in postfire soils due to warmer soil conditions, reductions in fungal biomass and activity may limit rates of decomposition.
SmartCoast: A Wireless Sensor Network for Water Quality Monitoring

The implementation of the Water Framework Directive (WFD) across the EU, and the growing international emphasis on the management of water quality is giving rise to an expanding market for novel, miniaturized, intelligent monitoring systems for freshwater catchments, transitional and coastal waters. This paper describes the "SmartCoast" multi sensor system for water quality monitoring. This system is aimed at providing a platform capable of meeting the monitoring requirements of the Water Framework Directive. The key parameters under investigation include temperature, phosphate, dissolved oxygen, conductivity, pH, turbidity and water level. The "plug and play" capabilities enabled by the wireless sensor network (WSN) platform developed at Tyndall allow for integration of sensors as required are described, as well as the custom sensors under development within the project.