Miracle-dz/UniFAR-FTUs huggingface dataset:
client server Stub & Skeleton Layer Remote Reference Layer Remote Reference Layer Stub

In this paper we show how to enhancing the Java RMI framework to support object groups. The package we have developed allows programmers to dynamically deal with groups of servers all implementing the same interface. Our group mechanism can be used both to improve reliability preventing system failures and to implement processor farm parallelism. Each service request dispatched to an object group returns all the values computed by the group members permitting the implementation of both kind of applications. Moreover, these approaches differ both over computations failure and over the semantic of the implemented interface. Our extension is achieved enriching the classic RMI framework and the existing RMI registry with new functionalities. From user’s point of view the multicast RMI acts just like the traditional RMI system, and really the same architecture has been used.
Pedestrian detection in near-infrared night vision system

Several premium automotive brands offer night vision systems to enhance the driver's ability to see at night. Most recent generation night vision systems have added pedestrian detection as a feature to assist drivers to avoid potential collisions. This paper reviews pedestrian detection based on two different sensing technologies: active night vision operating in the near-infrared (NIR) region of the electromagnetic spectrum, and passive night vision operating in the far-infrared (FIR) spectrum. It also discusses the pros and cons of each type of night-vision system with-respect-to the pedestrian detection capability, the effectiveness for collision avoidance, and the commercial attractiveness. The paper introduces an enhancement to the NIR active lighting scheme that significantly improves the pedestrian detection performance. With improved pedestrian detection performance, we argue that the NIR night vision system is more effective at improving night-time driving safety and may achieve broader market acceptance.
Nonlinear Modeling: Genetic Programming vs. Fast Evolutionary Programming

Both Genetic Programming (GP) and Fast Evolutionary Programming (FEP) combined with a Reduced Parameter Bilinear (RPBL) model have been recognized as effective time series modeling methods. This study compares the performance of these two methods for their ability to model time series data in terms of their accuracy and time efficiency. A brief review of GP and FEP are presented. Then the accuracy and time efficiency of these two methods are evaluated on several different time series. The performances of the two methods are compared against each other. INTRODUCTION Artificial evolutionary processes, such as genetic algorithms (GA), are based on reproduction, recombination, and selection of the fittest members in an evolving population of candidate solutions. Koza [1] extended this genetic model of learning into the space of programs and thus introduced the concept of genetic programming (GP). Sathyanarayan and Chellapilla [5] proposed an alternative modeling approach called fast evolutionary programming (FEP) to optimize the parameters of a reduced parameter bilinear model (RPBL). The RPBL model [6] is capable of effectively representing nonlinear models with the additional advantage of using fewer parameters than a conventional bilinear model. This paper applies both approaches to model several time series, including Mackey-Glass, sunspot, and stock price time series. GENETIC PROGRAMMING Genetic programming (GP) lets a computer learn programs. The top-level process of GP follows a similar evolutionary approach as a GA. The major difference between GPs and GAs is that GP structures are not encoded as linear genomes, but rather as terms or symbolic expressions. The units being mutated and recombined do not consist of characters or command sequences but rather functional modules, which are generally represented as tree-structured chromosomes. The basic algorithm of GP is as follows: 1. Generate an initial population and evaluate the fitness for each individual in the population. 2. Select individuals from the population, typically using roulette or tournament methods.
NIMA-related kinase TbNRKC is involved in basal body separation in Trypanosoma brucei

The NIMA-related kinase 2 (NEK 2) has important cell cycle functions related to centriole integrity and splitting. Trypanosoma brucei does not possess centrioles, however, cytokinesis is coupled to basal body separation events. Here we report the first functional characterisation of a T. brucei basal body-cytoskeletal NIMA-related kinase (NRK) protein, TbNRKC. The TbNRKC kinase domain has high amino acid identity with the human NEK1 kinase domain (50%) but also shares 42% identity with human NEK2. TbNRKC is expressed in bloodstream and procyclic cells and functions as a bona fide kinase in vitro. Remarkably, RNAi knockdown of TbNRKC and overexpression of kinase-dead TbNRKC in procyclic forms induces the accumulation of cells with four basal bodies, whereas overexpression of active protein produces supernumary basal bodies and blocks cytokinesis. TbNRKC is located on mature and immature basal bodies and is the first T. brucei NRK to be found associated with the basal body cytokinesis pathway.
JavaScript Concurrency Models

As soon as most of the modern applications are deployed on the web, JavaScript has become a mainstream programming environment. JavaScript applications nowadays should support heavyweight web applications. We can mention here online games, graphics, media management, and even data mining. In the same time, processors on computing devices (including mobile terminals) are getting more and more elaborated. For example, it is common to see heterogeneous processors, comprised of both CPUs and GPUs almost everywhere. It creates a natural demand to parallelism in the programming tools. In this paper, we provide a survey of parallel programming models in JavaScript.
Analysis of a Pool Management Scheme for Cloud Computing Centers

In this paper, we propose an analytical performance model that addresses the complexity of cloud centers through distinct stochastic submodels, the results of which are integrated to obtain the overall solution. Our model incorporates the important aspects of cloud centers such as pool management, compound requests (i.e., a set of requests submitted by one user simultaneously), resource virtualization and realistic servicing steps. In this manner, we obtain not only a detailed assessment of cloud center performance, but also clear insights into equilibrium arrangement and capacity planning that allows servicing delays, task rejection probability, and power consumption to be kept under control.
A Pilot Test of a Graduate Course in Suicide Theory, Risk Assessment, and Management

The present discussion outlines the design and initial implementation of a semester-long graduate course in suicide theory, risk assessment, and management. While the structure of the course is adaptable in light of various considerations (e.g., targeted group of students and availability of resources), we review suicide risk assessment core competencies and course structure and provide sample evidence-based applied and interactive assignments. An initial empirical test of the course yielded a number of encouraging findings, including increased factual knowledge concerning suicide risk assessment and management, and improved objectively assessed student accuracy in estimating chronic and acute suicide risk in response to a mock case vignette. We offer suggested next steps for modification and testing of the course in undergraduate and graduate training contexts.
View independent human posture identification using Kinect

As an important part of human computer interaction (HCI) system, posture identification has been extensively studied over last years. Recently, Microsoft Kinect Sensor has become a hot spot for posture identification because it is efficient in acquiring body joint location information. In this study, based on Kinect, we proposed a framework for view independent human posture identification. In this framework, a viewpoint rotation transformation was performed on original skeleton location data and then total 9 features were extracted for building a SVM classifier. About 4200 samples including five postures taken from different body orientations were collected to construct a dataset for performance evaluation. The results of PCA analysis showed that the transformation was efficient in distinguishing different postures. Further analysis demonstrated that this method achieved a superior performance of 98.0% when the orientation angle was between -60° and 60°. These results show that this view independent framework is powerful and efficient in viewpoint invariant posture identification.
Demand Models for Market Level Data

In this paper I propose new continuous and discrete choice demand models. To do so, I note that existing demand models from the continuousand discrete-choice demand literatures each have distinct advantages for taking to market-level data. I attempt to build models with the union of the good properties of each literature. For instance, the continuous choice models are more appropriate for disaggregated data than popular demand models such as the Translog or Almost Ideal Demand Systems since they can be estimated even when products enter or exit the market during the sample period. Variation in the observed set of products can then be used to help identify substitution patterns, in a way recently made popular in the discrete choice demand literature. I propose a continuous choice model that can use this important source of identifying data variation. I then propose a discrete-choice demand model that is provides a flexible functional form in the sense Diewert (1974). It is a particular member of the GEV class of models developed by McFadden (1981). In each case I argue that developing highly parameterized demand models and then mapping those parameters down to be functions of product characteristics (following Pinkse, Slade, and Brett (2002)) provides a simple, coherent, and data driven method for estimating very rich demand systems. Approaching aggregate demand models in this way is computationally much less demanding than using a random coefficient approach since it does not require the use of simulation estimators. Along the way, I propose a generalization to the contraction mapping developed in Berry, Levinsohn, and Pakes (1995) for discrete choice models based on the observation that the Expected maximum utility function for the GEV class of models is a super-modular function. J.E. L. Classification: D0, D11, D12, C51
Reconsideration of rules in tables with non-deterministic data

This paper briefly surveys rough set-based framework RNIA (Rough Non-deterministic Information Analysis), which can handle tables with non-deterministic data. Each rough set-based concept in the standard tables is redefined based on the possible world semantics. Especially, in rule generation, we reconsider the definition of rules, because the standard definition of rule generation cannot be applicable to defining rules in RNIA. In this paper, we describe the new framework for handling rules in RNIA, which gives us new rule-based table data analysis.
Estudio correlacional entre el bienestar psicológico, subjetivo y social, y el fatalismo, el trauma y las cogniciones irracionales postraumáticas, en personas adultas, desplazadas por la violencia sociopolítica, radicadas en la ciudad de Barranquilla.

The following research has pretended correlate Psychological, Subjective and Social Well-Being, and Fatalism, Trauma and Irrationals Posttraumatic Cognitions, in adults displaced by socio-political violence, established in Barranquilla, Colombia. Referring to variables of Well-Being, the adaptations to the Spanish (Diaz et al, 2006) from the scales of: Psychological Well-Being of Ryff, Subjective Well-Being of Diener, Single-item Scale of Satisfaction with Life of Cantril, Positive and Negative Affect Schedule of Watson, Clark y Tellegen (1988) and Social Well-Being of Keyes, were administered to 200 adults in displace situation. Thus, the scales of Fatalism of Blanco and Díaz (2007), Davidson Trauma Scale (1996), and The Posttraumatic Cognitions Inventory (PTCI) of Foa et al (1999) were applied. Outcomes indicate that people who have been victims of forced displacement, present undeniable symptoms of trauma with a psychosocial tint; they also have elements associated to the Positive Mental Health, which scales of Well-Being are indicators. Bienestar en Personas Desplazadas 9
On Models in Object-Oriented Methods-Critique and a new Approach to Reversibility

In this paper object-oriented methods are examined, problems are pointed out and a new method is presented. In object-oriented analysis and design methods two types of models can be identified. On one hand, static architecture models are quite similar in all methods and can be considered as very elaborate. For dynamic models, on the other hand, a number of problems are encountered. They are not expressive enough, they are not reversible and dynamic models do not support a seamless development process. We have developed the MODERN method. It reuses known static architecture models. For the dynamic model, though, a new approach is presented: In a task oriented model a delegation relation is examined. This model is fully reversible, strictly object-oriented and highly expressive. In MODERN the entire development process is reversible and seamless.
Transport and chemical transformations influenced by shallow cumulus over land

Abstract. The distribution and evolution of reactive species in a boundary layer characterized by the presence of shallow cumulus over land is studied by means of two large-eddy simulation models: the NCAR and WUR codes. The study focuses on two physical processes that can influence the chemistry: the enhancement of the vertical transport by the buoyant convection associated with cloud formation and the perturbation of the photolysis rates below, in and above the clouds. It is shown that the dilution of the reactant mixing ratio caused by the deepening of the atmospheric boundary layer is an important process and that it can decrease reactant mixing ratios by 10 to 50 percent compared to very similar conditions but with no cloud formation. Additionally, clouds transport chemical species to higher elevations in the boundary layer compared to the case with no clouds which influences the reactant mixing ratios of the nocturnal residual layers following the collapse of the daytime boundary layer. Estimates of the rate of reactant transport based on the calculation of the integrated flux divergence range from to −0.2 ppb hr-1 to −1 ppb hr-1, indicating a net loss of sub-cloud layer air transported into the cloud layer. A comparison of this flux to a parameterized mass flux shows good agreement in mid-cloud, but at cloud base the parameterization underestimates the mass flux. Scattering of radiation by cloud drops perturbs photolysis rates. It is found that these perturbed photolysis rates substantially (10–40%) affect mixing ratios locally (spatially and temporally), but have little effect on mixing ratios averaged over space and time. We find that the ultraviolet radiance perturbation becomes more important for chemical transformations that react with a similar order time scale as the turbulent transport in clouds. Finally, the detailed intercomparison of the LES results shows very good agreement between the two codes when considering the evolution of the reactant mean, flux and (co-)variance vertical profiles.
Sybil attack detection using a low cost short group signature in VANET

Vehicular ad hoc network (VANET) has attracted the attention of many researchers in recent years. It enables value-added services such as road safety and managing traffic on the road. Security issues are the challenging problems in this network. Sybil attack is one of the serious security threats that attacker tries to forge some identities. One of the main purposes for creating invalid identities is disruption in voting based systems. In this paper we propose a secure protocol for solving two conflicting goals privacy and Sybil attack in vehicle to vehicle (V2V) communications in VANET. The proposed protocol is based on the Boneh-Shacham (BS) short group signature scheme and batch verification. Experimental results demonstrate efficiency and applicability of the proposed protocol for providing the requirements of privacy and Sybil attack detection in V2V communications in VANET.
AGGRESSIVE BEHAVIOR IN WINTERING DARK-EYED JUNCOS : DETERMINANTS OF DOMINANCE AND THEIR POSSIBLE RELATION TO GEOGRAPHIC VARIATION IN SEX RATIO

Dark-eyed Juncos (./unto hyemalis) residing in central and eastern United States during winter exhibit clinal variation in sex ratio: the percentage of females increases with decreasing latitude from a low of approximately 20% in northern states to a high of about 75% in Texas (Ketterson and Nolan 1976). Similar cases of geographic variation in winter sex ratio have been described in other avian species (Nice 1937, Lack 1944, King et al. 1965, and references cited in Ketterson and Nolan 1976). Since energetic and other costs of migration presumably increase with distance traveled, it is interesting to inquire about compensating benefits that may accrue to the average female in her more southerly wintering grounds. One obvious possibility is a lessening of intersexual competition during the season when the sexes are not required to reside together and food is likely to be in short supply (Selander 1966, Balph 19’ 75, Ketterson and Nolan 1976). Recent studies indicate that among captive flocks, male juncos tend to dominate females (Balph 1977) and dominance improves survivorship (Baker and Fox 1978). If food has been limiting and males have tended over evolutionary time to dominate available resources, this may account for the longer migrations of females (Ketterson and Nolan 1976, Gauthreaux 1978). The purpose of the present paper is to corroborate male dominance in freeranging flocks and to report on other determinants of dominance.
On Amplitude and Phase in Printed Characters

waves of different frequencies. Each component is specified by its amplitude and phase. Two-dimensional images can be analyzed in the same way. In the case of naturalistic scenes, Oppenheim and Lim [1981], Piotrowski and Campbell [1982], and Shapley et al. [1990] have demonstrated that phase spectra are more important than amplitude spectra in determining the appearance of the image. Duan and Morris [1989] have indicated that this is also the case for printed text. The project described here uses Mathematica to provide a graphic demonstration of the relative importance of amplitudes and phases in determining the appearance of printed characters. The approach is similar to the one used by Oppenheim and Lim [1981], and Piotrowski and Campbell [1982]. Hybrid images, containing the amplitudes of one character and the phases of another, are synthesized. From these images, the viewer can deduce the relative importance of amplitude and phase based on which character the hybrid image resembles. The first step is to obtain bitmap images of some printed characters. This is easily done using the Mathematica notebook interface. We can generate a PostScript image with an input such as:
Construction workspace management: the development and application of a novel nD planning approach and tool

Activity Execution Workspace (AEW) is one of the main constraints and resources on construction sites. The proactive management of AEWs is a very challenging task due to the dynamic nature of construction sites, where the availability of AEW is continuously evolving and changing over time. Project managers are looking for proactive approaches and innovative IT tools to accurately manage workspaces on construction sites as this affects not only costs and duration of projects, but also the safety of construction sites. The review of current state-of-the-art shows that limited research has been devoted to this area and that significant methodological and practical limitations exist. This research paper presents a novel approach for the management of AEWs. The objective of this approach is to enable the management of AEWs by integrating the traditional planning process (CPM – Critical Path Method) and Building Information Modeling (BIM) data in a 4D/5D environment and providing real-time management and rehearsal of AEWs. The approach, prototype and pilot case study presented in this paper have proven that it is feasible and effective to proactively manage AEWs within a 4D/5D environment. This is in line with the principles of nD project management, where the ultimate aim is to give project planners the capability of rehearsing different construction options, before the construction starts, in order to improve the efficiency and productivity of construction processes.
Item Recommendation 6.1 Related Work

Recommending content is an important task in many information systems. For example online shopping websites like Amazon give each customer personalized recommendations of products that the user might be interested in. Other examples are video portals like YouTube that recommend videos to visitors. Personalization is attractive both for content providers, who can increase sales or views, and for customers , who can find interesting content more easily. In this chapter, we focus on item recommendation where the task is to create a user-specific ranking for a set of items. Preferences of users about items are learned from the user's past interaction with the system – e.g. his buying history, viewing history, etc. Thus, the context in item recommenders is the user and user-aware rankings should be generated. Recommender systems are an active topic of research. Most recent work is on scenarios where users provide explicit feedback, e.g. in terms of ratings. Nevertheless , in real-world scenarios most feedback is not explicit but implicit. Implicit feedback is tracked automatically, like monitoring clicks, view times, purchases, etc. Thus it is much easier to collect, because the user has not to express his taste explicitly. In fact implicit feedback is already available in almost any information system – e.g. web servers record any page access in log files. We start with introducing the related work in the field of item recommendation. Then, we discuss the problem setting and show how it fits into the context-aware ranking framework. Afterwards, we apply the Bayesian Context-aware Ranking (BCR) framework to personalization, thus we get Bayesian Personalized Ranking (BPR). We show the optimization criterion and learning algorithm for this instance of BCR. Then, we describe how the two popular item recommendation models k-nearest neighbor and matrix factorization can be learned with BPR. In the evaluation , we compare the quality of these approaches to the state-of-the-art recom-menders of weighted regularized matrix factorization and cosine kNN. The most popular model for recommender systems is k-nearest neighbor (kNN) collaborative filtering (Deshpande and Karypis, 2004). Traditionally, the similarity S. Rendle: Context-Aware Ranking with Factorization Models, SCI 330, pp. 69–84.