Miracle-dz/UniFAR-FTUs huggingface dataset:
Tuning RED for Web traffic

We study the effects of RED on the performance of Web browsing with a novel aspect of our work being the use of a user-centric measure of performance: response time for HTTP request-response pairs. We empirically evaluate RED across a range of parameter settings and offered loads. Our results show that: 1) contrary to expectations, compared to a FIFO queue, RED has a minimal effect on HTTP response times for offered loads up to 90% of link capacity; 2) response times at loads in this range are not substantially affected by RED parameters; 3) between 90% and 100% load, RED can be carefully tuned to yield performance somewhat superior to FIFO, however, response times are quite sensitive to the actual RED parameter values selected; and 4) in such heavily congested networks, RED parameters that provide the best link utilization produce power response times. We conclude that for links carrying only Web traffic, RED queue management appears to provide no clear advantage over tail-drop FIFO for end-user response times.
Personalized Time-Aware Tag Recommendation

Personalized tag recommender systems suggest a list of tags to a user when he or she wants to annotate an item. They utilize users’ preferences and the features of items. Tensorfactorization techniques have been widely used in tag recommendation. Given the user-item pair, although the classic PITF (Pairwise Interaction Tensor Factorization) explicitly models the pairwise interactions among users, items and tags, it overlooks users’ short-term interests and suffers from data sparsity. On the other hand, given the user-item-time triple, time-aware approaches like BLL (Base-Level Learning) utilize the time effect to capture the temporal dynamics and the most popular tags on items to handle cold start situation of new users. However, it works only on individual level and the target resource level, which cannot find users’ potential interests. In this paper, we propose an unified tag recommendation approach by considering both time awareness and personalization aspects, which extends PITF by adding weightsto user-tag interaction and item-tag interaction respectively. Compared to PITF, our proposed model can depict temporal factor by temporal weights and relieve data sparsity problem by referencing the most popular tags on items. Further, our model brings collaborative filtering (CF) to time-aware models, which can mine information from global data and help improving the ability of recommending new tags. Different from the power-form functions used in the existing time aware recommendation models, we use the Hawkes process with the exponential intensity function to improve the model’s efficiency. The experimental results show that our proposed model outperforms the state of the art tag recommendation methods in accuracy and has better ability to recommend new tags.
Energy efficient clustering based data gathering using hybrid DB-EMGM in distributed sensor networks

Clustering is one of the most useful methods for data gathering in distributed wireless sensor networks (WSNs). In additions, sensors in such environment are energy constrained and generate the huge amount of data due to redundant data transmission and thus reducing lifetime of networks. Moreover, there is need to use efficient clustering techniques for collecting relevant data from nodes to eliminate redundancy. The data gathering using existing clustering algorithms engage some problems like arbitrary shape of clusters, estimating input parameters, detection of noisy points. In this paper, we propose an improved clustering method known as hybrid DB-EMGM that combines both EMGM and DBSCAN methods. The improved method aims to reduce the data traffic inside the WSNs network by minimizing intra cluster distance and, thus, finding location of cluster heads using calculated cluster covariance and mean when forming different clusters. The concept of mobile sink node is utilized for collecting the relevant data from all nodes by visiting every cluster heads. Since the mobility concept of node tries to reduce wireless data transmission by following the shortest path based on cluster heads location. The results of our method show that it is computationally faster than EMGM by reducing intra and inter cluster communication distance and increases the transmission rate to the sink node. The performance of our improved method is validated through results presented.
Integrating the visualisation reference model with ecological interface design

Motivation -- In some situations EID's high-level visual design principles can be difficult to apply. A more concrete design methodology would make the framework more accessible for interface designers. Research approach -- Graphics research was reviewed across a number of fields. The Visualisation Reference Model was identified as a useful model that could be used alongside EID's visual design principles. A case study is used to demonstrate this approach. Findings/Design -- Supplementing a work domain analysis with a task analysis can reveal how information requirements are used. This allows data transformations and visual mapping to be carried out to generate visual components in an ecological interface design. Take away message -- Task analysis not only improves the quality of our information requirements, it can also inform the visual design process.
The own v lease decision ‐ Myth and reality

The own versus lease decision is a surprisingly controversial topic. Although the issues driving the decision appear straightforward, they are interpreted differently, leading corporations to make opposite decisions in similar circumstances. Overall, however, the author’s experience is that the current trend is away from ownership. In the slower‐moving decades of the past, corporations chose to own their real estate to keep control of their place of work. These buildings were often constructed specifically for their use and were as much image statements as places of work. Today, the pendulum of popular opinion has swung to the other extreme. In an era where asset metrics such as EVA (Economic Value Add) and ROA (Return on Assets) are in vogue, it is no longer acceptable for corporations to invest funds in capital‐intensive assets that are not central to the company’s business. Under the banner of flexibility and better asset utilisation, many companies have adopted a ‘lease only’ policy and refuse to own any building, even their corporate headquarters. Unfortunately, it’s not that simple. Although easy to follow and implement, simple rules such as ‘own everything’ or ‘lease everything’ don’t work. Each decision needs to be assessed against a number of criteria which determine the relative advantages of leasing or owning in a given situation. It is an environment in which many myths have emerged. The following paper outlines many of the issues involved in own v lease decisions and reviews some of these myths. By providing a framework for making the decision, it asserts that, as with most major business decisions, there is no getting away from the need for an intelligent analyst.
Work to school: Teachers from industry

The conference committee for the annual conference of the Australian Teacher Education Association (ATEA) facilitates the review of all papers for admission to the conference. Abstracts for all papers presented are reviewed by the organising committee as to suitability for presentation as research at the annual conference, but full paper refereeing is optional. Only papers actually presented at the conference are published on the ATEA website.
Governing Information Technology Risk

Regulatory changes have affected the composition, role, and responsibilities of Boards of Directors worldwide. While stronger frameworks for directors9 fiduciary responsibilities have resulted, considerably less attention has been devoted to understanding the nature of, and concomitant duty-of-care towards, the information systems and technology assets in the organization, or IT Governance. As a result, Boards have not demonstrated the competence or attention that good IT governance demands. IT Governance takes two forms: a defensive form, IT Risk Governance, that seeks to safeguard the organization from the consequences of IT-related disasters; and a strategic form, IT Value Governance, which creates lasting shareholder value. This article focuses on IT Risk Governance. Based on an academic and trade literature review, and interviews with Board members from six international firms, it presents a model, the IT Risk Governance Chain, and a dashboard that outlines the critical areas of IT risk and the key questions directors should ask to properly safeguard the information and technology assets of their firms.
(Re)Branching Narrativity: Virtual Space Experience in Twitch

Twitch, as an online platform for gamers, has been analyzed in terms of its commercial benefits for the increase of game sales and its role in bringing fame to streamers. By focusing on Twitch’s interactive capacity, this paper compares this platform to narrative games, playable stories, and mobile narratives in terms of the role of the user(s) and their virtual space experience. Drawing on theories by Marie-Laure Ryan and Rita Raley, the paper argues that Twitch assigns authorial roles to the users (i.e., the streamers and the subscribers), who branch the existing narrative of the game by determining the path of the setting collectively. By doing so, the paper proposes Twitch as a space, which extends the immersion that is discussed around multiple forms of interactive narrativity.
On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.
Borrowing for College: A Comparison of Long‐Term Debt Financing between Public and Private, Nonprofit Institutions of Higher Education

Institutions of higher education provide an excellent opportunity to compare long‐term debt financing in the nonprofit and public sectors. The proposed models explain the long‐term debt per student at public and private‐nonprofit research universities. Student enrollment, enrollment growth, total assets, and revenue variables as a group all influence debt levels. The strongest predictors of debt balances are the fixed characteristics of the universities themselves. Empirical evidence from the university sector also suggests the absence of a powerful arbitrage incentive to issue debt.
Directive functions of autobiographical memory: The guiding power of the specific episode

Vivid memories of personal experiences provide models for present activities and contribute to successful problem solving and adaptation. The memories serve important directive functions: they inform, guide, motivate, and inspire. Yet directive functions have received less emphasis in the research literature than social or self functions. Explanations for this relative neglect are explored. Case studies and systematic research illustrate the prominence of memory directives in everyday life. Empirical studies that have compared memory functions are examined critically, reasons why directive functions may be underestimated using existing methods are discussed, and ideas for future research are outlined.
Processes of Socio-spatial Differentiation in Post-communist Prague

This paper analyses processes which transform the socio-spatial pattern of post-communist Prague and describes major changes in the city's social geography. It begins with a brief introduction about the socio-spatial pattern of a socialist city and a discussion of methods and concepts of investigation of processes of socio-spatial change in contemporary Prague. Growing income inequalities and transformations in the housing system are examined as the main underlying causes of growing socio-spatial disparities. In the section concerning the mechanism of socio-spatial differentiation, attention is focused on the role of social mobility, migration, housing renovation and new housing construction. The conclusions summarise major changes in the social geography of post-communist Prague and discuss implications of central and local government policies for the growth in socio-spatial disparities.
The Roles of the Two Zinc Binding Sites in DnaJ*

All type I DnaJ (Hsp40) homologues share the presence of two highly conserved zinc centers. To elucidate their function, we constructed DnaJ mutants that separately replaced cysteines of either zinc center I or zinc center II with serine residues. We found that in the absence of zinc center I, the autonomous, DnaK-independent chaperone activity of DnaJ is dramatically reduced. Surprisingly, this only slightly impaired the in vivo function of DnaJ, and its ability to function as a co-chaperone in the DnaK/DnaJ/GrpE foldase machine. The DnaJ zinc center II, on the other hand, was found to be absolutely essential for the in vivo and in vitro function of DnaJ. This did not seem to be caused by a lack of substrate binding affinity or an inability to work as an ATPase-stimulating factor. Rather it appears that zinc center II mutant proteins lack a necessary additional interaction site with DnaK, which seems to be crucial for locking-in substrate proteins onto DnaK. These findings led us to a model in which ATP hydrolysis in DnaK is only the first step in converting DnaK into its high affinity binding state. Additional interactions between DnaK and DnaJ are required to make the DnaK/DnaJ/GrpE foldase machinery catalytically active.
Voter Mobilization and the Obama Victory

As with the other presidential elections from this decade, the 2008 election was followed by considerable speculation as to how new efforts to mobilize voters affected the eventual outcome. Although the conventional wisdom implies that “Democrats benefit from higher turnout,” previous research in political science demonstrates that such a conclusion applies to actual election results inconsistently. In this article, we outline the difficulties involved with assessing turnout effects within a particular election and proceed to test the hypothesis that the Obama campaign benefited from higher turnout using three different methods. The evidence suggests that the Obama campaign benefited substantially from voter turnout, particularly in comparison with the Kerry campaign in 2004, yet they also were successful in changing the minds of already mobilized voters. Although various data difficulties suggest the presence of some bias in our estimates, the consistency of the results across tests supports the general conclusion.
Combination of Bayesian and Latent Semantic Analysis with Domain Specific Knowledge

With the development of information technology, electronic publications become popular. However, it is a challenge to retrieve information from electronic publications because the large amount of words, the synonymy problem and the polysemi problem. In this paper, we introduced a new algorithm called Bayesian Latent Semantic Analysis (BLSA). We chose to model text not based on terms but associations between words. Also, the significance of interesting features were improved by expand the number of similar terms with glossaries. Latent Semantic Analysis (LSA) was chosen to discover significant features. Bayesian post probability was used to discover segmentation boundaries. Also, Dirchlet distribution was chosen to present the vector of topic distribution and calculate the maximum probability of the topics. Experimental results showed us that both Pk [8] and WindowsDiff [27] decreased 10% by using BLSA in comparison to the Lexical Cohesion with the original data.
Family Demography, Social Theory, and Investment in Social Capital

The analytic models used by family demographers would be strengthened by the concept of social capital, placed in the context of social exchange theory. Using that concept to designate resources that emerge from social ties, the authors advance five propositions: 1) social capital is a multidimensional attribute of an individual; 2) the dimensions of social capital are the number of relationships a person has, their quality (strength), and the resources available through those relationships; 3) group membership and interaction facilitate the development of social capital; 4) the structural properties of groups influence the development of social capital; and 5) the acquisition and maintenance of social capital is a major motivator of human behavior. The formation of sexual partnerships, the birth and rearing of children, and both intragenerational and intergenerational transfers constitute major forms of investment in social capital in virtually all societies. Copyright 1999 by The Population Council, Inc.
Two for one: querying property graph databases using SPARQL via gremlinator

In the past decade Knowledge graphs have become very popular and frequently rely on the Resource Description Framework (RDF) or Property Graphs (PG) as their data models. However, the query languages for these two data models - SPARQL for RDF and the PG traversal language Gremlin - are lacking basic interoperability. In this demonstration paper, we present Gremlinator, the first translator from SPARQL - the W3C standardized language for RDF - to Gremlin - a popular property graph traversal language. Gremlinator translates SPARQL queries to Gremlin path traversals for executing graph pattern matching queries over graph databases. This allows a user, who is well versed in SPARQL, to access and query a wide variety of Graph databases avoiding the steep learning curve for adapting to a new Graph Query Language (GQL). Gremlin is a graph computing system-agnostic traversal language (covering both OLTP graph databases and OLAP graph processors), making it a desirable choice for supporting interoperability for querying Graph databases. Gremlinator is planned to be released as an Apache TinkerPop plugin in the upcoming releases.
Career Transitions: An Empirical Examination of Second Career of Military Retirees

We examined the prospects of successful career transition from the defense forces and into the dynamic and turbulent civilian career, focusing on possible antecedents for success in the second career. Based on a sample of 202 high level retirees from military and civilian defense organizations in Israel, our results indicate that preparations for retirement, social capital, perception of organizational politics in the new working place and work-family conflict are related to the dependent variables and affect the retiree's success in their second career. In addition, organizational commitment was found to serve as a mediator in these relationships. Implications for theory of career development and change, as well as practical implications and recommendations for future studies, are discussed.
General Equilibrium Pricing of Options on the Market Portfolio with Discontinuous Returns

When the price process for a long-lived asset is of a mixed jump-diffusion type, pricing of options on that asset by arbitrage is not possible if trading is allowed only in the underlaying asset and a risk-less bond. Using a general equilibrium framework, we derive and analyze option prices when the underlying asset is the market portfolio with discontinuous returns. The premium for the risk of jumps and the diffusion risks forms a significant part of the prices of the options. In this economy, an attempted replication of call and put options by the Black-Scholes type of trading strategies may require substantial infusion of funds when jumps occur. We study the cost and risk implications of such dynamic hedging plans. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Update on Osteoarthritis

Osteoarthritis is the most common type of arthritis affecting humans. Its clinical features are well recognized, and its diagnosis is easily established. The etiopathogenesis of the disease is still poorly understood. The definition and classification of osteoarthritis have only recently been set up by the American Rheumatism Association and the National Institutes of Health-sponsored workshop. Management should be four-fold: educational, physiatric, medical, and surgical. The management goal should be individualized and be aimed at symptomatic relief and restoration of function. (Can Fam Physician 1990; 36:539-541, 614.) RESUME
Structural Equation Modeling: A Practical Introduction

Structural equation modeling (SEM) is a popular statistical technique that has become an essential tool for business academics and practitioners. The technique is particularly well suited for evaluating the relationships among any number of observed and latent variables. Thus, typical applications for SEMs are model and theory testing, and scale development. The purpose of this article is to introduce the technique and to explain its use in practical terms that do not require a strong statistical background. Two previous Journal of African Business articles are used to demonstrate SEM applications, and the article concludes with a brief introduction to SEM software packages.