Query: Understanding "watchers" on GitHub

Relevant passages:
Social coding in GitHub: transparency and collaboration in an open software repository <=SEP=> Social applications on the web let users track and follow the activities of a large number of others regardless of location or affiliation. There is a potential for this transparency to radically improve collaboration and learning in complex knowledge-based activities. Based on a series of in-depth interviews with central and peripheral GitHub users, we examined the value of transparency for large-scale distributed collaborations and communities of practice. We find that people make a surprisingly rich set of social inferences from the networked activity information in GitHub, such as inferring someone else's technical goals and vision when they edit code, or guessing which of several similar projects has the best chance of thriving in the long term. Users combine these inferences into effective strategies for coordinating work, advancing technical skills and managing their reputation.

The social structure of free and open source software development <=SEP=> Metaphors, such as the Cathedral and Bazaar, used to describe the organization of FLOSS projects typically place them in sharp contrast to proprietary development by emphasizing FLOSS’s distinctive social and communications structures. But what do we really know about the communication patterns of FLOSS projects? How generalizable are the projects that have been studied? Is there consistency across FLOSS projects? Questioning the assumption of distinctiveness is important because practitioner-advocates from within the FLOSS community rely on features of social structure to describe and account for some of the advantages of FLOSS production. To address this question, we examined 120 project teams from SourceForge, representing a wide range of FLOSS project types, for their communications centralization as revealed in the interactions in the bug tracking system. We found that FLOSS development teams vary widely in their communications centralization, from projects completely centered on one developer to projects that are highly decentralized and exhibit a distributed pattern of conversation between developers and active users. We suggest, therefore, that it is wrong to assume that FLOSS projects are distinguished by a particular social structure merely because they are FLOSS. Our findings suggest that FLOSS projects might have to work hard to achieve the expected development advantages which have been assumed to flow from “going open.” In addition, the variation in communications structure across projects means that communications centralization is useful for comparisons between FLOSS teams. We

The Cathedral and the Bazaar <=SEP=> Permission is granted to copy, distribute and/or modify this document under the terms of the Open Publication License, version 2.0. $Date: 2002/08/02 09:02:14 $ Revision History Revision 1.57 11 September 2000 esr New major section “How Many Eyeballs Tame Complexity”. Revision 1.52 28 August 2000 esr MATLAB is a reinforcing parallel to Emacs. Corbatoó & Vyssotsky got it in 1965. Revision 1.51 24 August 2000 esr First DocBook version. Minor updates to Fall 2000 on the time-sensitive material. Revision 1.49 5 May 2000 esr Added the HBS note on deadlines and scheduling. Revision 1.51 31 August 1999 esr This the version that O’Reilly printed in the first edition of the book. Revision 1.45 8 August 1999 esr Added the endnotes on the Snafu Principle, (pre)historical examples of bazaar development, and originality in the bazaar. Revision 1.44 29 July 1999 esr Added the “On Management and the Maginot Line” section, some insights about the usefulness of bazaars for exploring design space, and substantially improved the Epilog. Revision 1.40 20 Nov 1998 esr Added a correction of Brooks based on the Halloween Documents. Revision 1.39 28 July 1998 esr I removed Paul Eggert’s ’graph on GPL vs. bazaar in response to cogent aguments from RMS on Revision 1.31 February 1

Social translucence: an approach to designing systems that support social processes <=SEP=> We are interested in desiging systems that support communication and collaboration among large groups of people over computing networks. We begin by asking what properties of the physical world support graceful human-human communication in face-to-face situations, and argue that it is possible to design digital systems that support coherent behavior by making participants and their activites visible to one another. We call such systems “socially translucent systems” and suggest that they have three characteristics—visbility, awareness, and accountability—which enable people to draw upon their experience and expertise to structure their interactions with one another. To motivate and focus our ideas we develop a vision of knowledge communities, conversationally based systems that support the creation, management and reuse of knowledge in a social context. We describe our experience in designing and deploying one layer of functionality for knowledge communities, embodied in a working system called “Barbie” and discuss research issues raised by a socially translucent approach to design.

Cave or Community? An Empirical Examination of 100 Mature Open Source Projects <=SEP=> Starting with Eric Raymond’s groundbreaking work, The Cathedral and the Bazaar, open-source software (OSS) has commonly been regarded as work produced by a community of developers. Yet, given the nature of software programs, one also hears of developers with no lives that work very hard to achieve great product results. In this paper, I sought empirical evidence that would help us understand which is more commonthe cave (i.e., lone producer) or the community. Based on a study of the top 100 mature products on Sourceforge, I find a few surprising things. First, most OSS programs are developed by individuals, rather than communities. The median number of developers in the 100 projects I looked at was 4 and the mode was 1numbers much lower than previous ones reported for highly successful projects! Second, most OSS programs do not generate a lot of discussion. Third, products with more developers tend to be viewed and downloaded more often. Fourth, the number of developers associated with a project is unrelated to the age of the project. Fifth, the larger the project, the smaller the percent of project administrators.

Case Reports of Adipose-derived Stem Cell Therapy for Nasal Skin Necrosis after Filler Injection <=SEP=> With the gradual increase of cases using fillers, cases of patients treated by non-medical professionals or inexperienced physicians resulting in complications are also increasing. We herein report 2 patients who experienced acute complications after receiving filler injections and were successfully treated with adipose-derived stem cell (ADSCs) therapy. Case 1 was a 23-year-old female patient who received a filler (Restylane) injection in her forehead, glabella, and nose by a non-medical professional. The day after her injection, inflammation was observed with a 3×3 cm skin necrosis. Case 2 was a 30-year-old woman who received a filler injection of hyaluronic acid gel (Juvederm) on her nasal dorsum and tip at a private clinic. She developed erythema and swelling in the filler-injected area A solution containing ADSCs harvested from each patient's abdominal subcutaneous tissue was injected into the lesion at the subcutaneous and dermis levels. The wounds healed without additional treatment. With continuous follow-up, both patients experienced only fine linear scars 6 months postoperatively. By using adipose-derived stem cells, we successfully treated the acute complications of skin necrosis after the filler injection, resulting in much less scarring, and more satisfactory results were achieved not only in wound healing, but also in esthetics.

Peer support services for individuals with serious mental illnesses: assessing the evidence. <=SEP=> OBJECTIVE
This review assessed the level of evidence and effectiveness of peer support services delivered by individuals in recovery to those with serious mental illnesses or co-occurring mental and substance use disorders.


METHODS
Authors searched PubMed, PsycINFO, Applied Social Sciences Index and Abstracts, Sociological Abstracts, Social Services Abstracts, Published International Literature on Traumatic Stress, the Educational Resources Information Center, and the Cumulative Index to Nursing and Allied Health Literature for outcome studies of peer support services from 1995 through 2012. They found 20 studies across three service types: peers added to traditional services, peers in existing clinical roles, and peers delivering structured curricula. Authors judged the methodological quality of the studies using three levels of evidence (high, moderate, and low). They also described the evidence of service effectiveness.


RESULTS
The level of evidence for each type of peer support service was moderate. Many studies had methodological shortcomings, and outcome measures varied. The effectiveness varied by service type. Across the range of methodological rigor, a majority of studies of two service types--peers added and peers delivering curricula--showed some improvement favoring peers. Compared with professional staff, peers were better able to reduce inpatient use and improve a range of recovery outcomes, although one study found a negative impact. Effectiveness of peers in existing clinical roles was mixed.


CONCLUSIONS
Peer support services have demonstrated many notable outcomes. However, studies that better differentiate the contributions of the peer role and are conducted with greater specificity, consistency, and rigor would strengthen the evidence.

Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010) <=SEP=> The simple, but general formal theory of fun and intrinsic motivation and creativity (1990-2010) is based on the concept of maximizing intrinsic reward for the active creation or discovery of novel, surprising patterns allowing for improved prediction or data compression. It generalizes the traditional field of active learning, and is related to old, but less formal ideas in aesthetics theory and developmental psychology. It has been argued that the theory explains many essential aspects of intelligence including autonomous development, science, art, music, and humor. This overview first describes theoretically optimal (but not necessarily practical) ways of implementing the basic computational principles on exploratory, intrinsically motivated agents or robots, encouraging them to provoke event sequences exhibiting previously unknown, but learnable algorithmic regularities. Emphasis is put on the importance of limited computational resources for online prediction and compression. Discrete and continuous time formulations are given. Previous practical, but nonoptimal implementations (1991, 1995, and 1997-2002) are reviewed, as well as several recent variants by others (2005-2010). A simplified typology addresses current confusion concerning the precise nature of intrinsic motivation.

Deep neural network for manufacturing quality prediction <=SEP=> Expected product quality is affected by multi-parameter in complex manufacturing processes. Product quality prediction can offer the possibility of designing better system parameters at the early production stage. Many existing approaches fail at providing favorable results duo to shallow architecture in prediction model that can not learn multi-parameter's features insufficiently. To address this issue, a deep neural network (DNN), consisting of a deep belief network (DBN) in the bottom and a regression layer on the top, is proposed in this paper. The DBN uses a greedy algorithm for unsupervised feature learning. It could learn effective features for manufacturing quality prediction in an unsupervised pattern which has been proven to be effective for many fields. Then the learned features are inputted into the regression tool, and the quality predictions are obtained. One type of manufacturing system with multi-parameter is investigated by the proposed DNN model. The experiments show that the DNN has good performance of the deep architecture, and overwhelms the peer shallow models. It is recommended from this study that the deep learning technique is more promising in manufacturing quality prediction.

A linguistic ontology of space for natural language processing <=SEP=> a r t i c l e i n f o a b s t r a c t We present a detailed semantics for linguistic spatial expressions supportive of computational processing that draws substantially on the principles and tools of ontological engineering and formal ontology. We cover language concerned with space, actions in space and spatial relationships and develop an ontological organization that relates such expressions to general classes of fixed semantic import. The result is given as an extension of a linguistic ontology, the Generalized Upper Model, an organization which has been used for over a decade in natural language processing applications. We describe the general nature and features of this ontology and show how we have extended it for working particularly with space. Treaitng the semantics of natural language expressions concerning space in this way offers a substantial simplification of the general problem of relating natural spatial language to its contextualized interpretation. Example specifications based on natural language examples are presented, as well as an evaluation of the ontology's coverage, consistency, predictive power, and applicability.

A Survey of Intrusion Detection Systems for Mobile Ad Hoc Networks <=SEP=> Tactical Mobile Ad-hoc Networks (MANETs) are widely deployed in military organizations that have critical needs of communication even with the absence of fixed infrastructure. The lack of communication infrastructure and dynamic topology makes MANETs vulnerable to a wide range attacks. Tactical military operations are among the prime users of ad-hoc networks. The military holds higher standards of security requirements and thus require special intrusion detection applications. Conventional Intrusion Detection System (IDS) require central control and monitoring entities and thus cannot be applied to MANETs. Solutions to secure these networks are based on distributed and cooperative security. This paper presents a survey of IDS specifically for MANETs and also highlights the strengths and weakness of each model. We present a unique evaluation matrix for measuring the effectiveness of IDS for MANETs in an emergency response scenario.

Enabling agricultural automation to optimize utilization of water, fertilizer and insecticides by implementing Internet of Things (IoT) <=SEP=> With the proliferation of smart devices, Internet can be extended into the physical realm of Internet-of-Things (IoT) by deploying them into a communicating-actuating network. In Ion, sensors and actuators blend seamlessly with the environment; collaborate globally with each other through internet to accomplish a specific task. Wireless Sensor Network (WSN) can be integrated into Ion to meet the challenges of seamless communication between any things (e.g., humans or objects). The potentialities of IoT can be brought to the benefit of society by developing novel applications in transportation and logistics, healthcare, agriculture, smart environment (home, office or plant). This research gives a framework of optimizing resources (water, fertilizers, insecticides and manual labour) in agriculture through the use of IoT. The issues involved in the implementation of applications are also investigated in the paper. This frame work is named as AgriTech.

Robust entropy-based endpoint detection for speech recognition in noisy environments <=SEP=> This paper presents an entropy-based algorithm for accurate and robust endpoint detection for speech recognition under noisy environments. Instead of using the conventional energy-based features, the spectral entropy is developed to identify the speech segments accurately. Experimental results show that this algorithm outperforms the energy-based algorithms in both detection accuracy and recognition performance under noisy environments, with an average error rate reduction of more than 16%.

A review on stress inducement stimuli for assessing human stress using physiological signals <=SEP=> Assessing human stress in real-time is more difficult and challenging today. The present review deals about the measurement of stress in laboratory environment using different stress inducement stimuli by the help of physiological signals. Previous researchers have been used different stress inducement stimuli such as stroop colour word test (CWT), mental arithmetic test, public speaking task, cold pressor test, computer games and works used to induce the stress. Most of the researchers have been analyzed stress using questionnaire based approach and physiological signals. The several physiological signals like Electrocardiogram (ECG), Electromyogram (EMG), Galvanic Skin Response (GSR), Blood Pressure (BP), Skin Temperature (ST), Blood Volume Pulse (BVP), respiration rate (RIP) and Electroencephalogram (EEG) were briefly investigated to identify the stress. Different statistical methods like Analysis of variance (ANOVA), two-way ANOVA, Multivariate analysis of variance (MANOVA), t-test, paired t-tests and student t-tests have used to describe the correlation between stress inducement stimuli, subjective parameters (age, gender and etc.,) and physiological signals. This present works aims to find the most appropriate stress inducement stimuli, physiological signals and statistical method to efficiently asses the human stress.

Towards Principled Methods for Training Generative Adversarial Networks <=SEP=> The goal of this paper is not to introduce a single algorithm or method, but to make theoretical steps towards fully understanding the training dynamics of generative adversarial networks. In order to substantiate our theoretical analysis, we perform targeted experiments to verify our assumptions, illustrate our claims, and quantify the phenomena. This paper is divided into three sections. The first section introduces the problem at hand. The second section is dedicated to studying and proving rigorously the problems including instability and saturation that arize when training generative adversarial networks. The third section examines a practical and theoretically grounded direction towards solving these problems, while introducing new tools to study them.

Decoding by linear programming <=SEP=> This paper considers a natural error correcting problem with real valued input/output. We wish to recover an input vector f/spl isin/R/sup n/ from corrupted measurements y=Af+e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to recover f exactly from the data y? We prove that under suitable conditions on the coding matrix A, the input f is the unique solution to the /spl lscr//sub 1/-minimization problem (/spl par/x/spl par//sub /spl lscr/1/:=/spl Sigma//sub i/|x/sub i/|) min(g/spl isin/R/sup n/) /spl par/y - Ag/spl par//sub /spl lscr/1/ provided that the support of the vector of errors is not too large, /spl par/e/spl par//sub /spl lscr/0/:=|{i:e/sub i/ /spl ne/ 0}|/spl les//spl rho//spl middot/m for some /spl rho/>0. In short, f can be recovered exactly by solving a simple convex optimization problem (which one can recast as a linear program). In addition, numerical experiments suggest that this recovery procedure works unreasonably well; f is recovered exactly even in situations where a significant fraction of the output is corrupted. This work is related to the problem of finding sparse solutions to vastly underdetermined systems of linear equations. There are also significant connections with the problem of recovering signals from highly incomplete measurements. In fact, the results introduced in this paper improve on our earlier work. Finally, underlying the success of /spl lscr//sub 1/ is a crucial property we call the uniform uncertainty principle that we shall describe in detail.

Design Exploration of Hybrid CMOS and Memristor Circuit by New Modified Nodal Analysis <=SEP=> Design of hybrid circuits and systems based on CMOS and nano-device requires rethinking of fundamental circuit analysis to aid design exploration. Conventional circuit analysis with modified nodal analysis (MNA) cannot consider new nano-devices such as memristor together with the traditional CMOS devices. This paper has introduced a new MNA method with magnetic flux (Φ) as new state variable. New SPICE-like circuit simulator is thereby developed for the design of hybrid CMOS and memristor circuits. A number of CMOS and memristor-based designs are explored, such as oscillator, chaotic circuit, programmable logic, analog-learning circuit, and crossbar memory, where their functionality, performance, reliability and power can be efficiently verified by the newly developed simulator. Specifically, one new 3-D-crossbar architecture with diode-added memristor is also proposed to improve integration density and to avoid sneak path during read-write operation.

Facial Expression Recognition with Convolutional Neural Networks <=SEP=> Facial expression recognition systems have attracted much research interest within the field of artificial intelligence. Many established facial expression recognition (FER) systems apply standard machine learning to extracted image features, and these methods generalize poorly to previously unseen data. This project builds upon recent research to classify images of human faces into discrete emotion categories using convolutional neural networks (CNNs). We experimented with different architectures and methods such as fractional max-pooling and finetuning, ultimately achieving an accuracy of 0.48 in a sevenclass classification task.

Object Constraint Language (OCL): A Definitive Guide <=SEP=> The Object Constraint Language (OCL) started as a complement of the UML notation with the goal to overcome the limitations of UML (and in general, any graphical notation) in terms of precisely specifying detailed aspects of a system design. Since then, OCL has become a key component of any model-driven engineering (MDE) technique as the default language for expressing all kinds of (meta)model query, manipulation and specification requirements. Among many other applications, OCL is frequently used to express model transformations (as part of the source and target patterns of transformation rules), well-formedness rules (as part of the definition of new domain-specific languages), or code-generation templates (as a way to express the generation patterns and rules). This chapter pretends to provide a comprehensive view of this language, its many applications and available tool support as well as the latest research developments and open challenges around it.

Topic models in information retrieval <=SEP=> 

Generating Descriptions with Grounded and Co-referenced People <=SEP=> Learning how to generate descriptions of images or videos received major interest both in the Computer Vision and Natural Language Processing communities. While a few works have proposed to learn a grounding during the generation process in an unsupervised way (via an attention mechanism), it remains unclear how good the quality of the grounding is and whether it benefits the description quality. In this work we propose a movie description model which learns to generate description and jointly ground (localize) the mentioned characters as well as do visual co-reference resolution between pairs of consecutive sentences/clips. We also propose to use weak localization supervision through character mentions provided in movie descriptions to learn the character grounding. At training time, we first learn how to localize characters by relating their visual appearance to mentions in the descriptions via a semi-supervised approach. We then provide this (noisy) supervision into our description model which greatly improves its performance. Our proposed description model improves over prior work w.r.t. generated description quality and additionally provides grounding and local co-reference resolution. We evaluate it on the MPII Movie Description dataset using automatic and human evaluation measures and using our newly collected grounding and co-reference data for characters.

Methodology of band rejection / addition for microstrip antennas design using slot line theory and current distribution analysis <=SEP=> Radio or wireless communication means to transfer information over long distance without using any wires. Millions of people exchange information every day using pager, cellular, telephones, laptops, various types of personal digital assistance (PDAs) and other wireless communication products. The worldwide interoperability for microwave access (Wi-Max) aims to provide wireless data over a long distance in variety of ways. It was based on IEEE 802.16 standard. It is an effective metropolitan area access technique with many favorable features like flexibility, cost, efficiency and fast networking, which not only provides wireless access, but also serves to expand the access to wired network. The coverage area of Wi-Max is around 30-50 km. it can provide high 100 Mbps data rates in 20 MHz bandwidth on fixed and nomadic applications in the 2-11 GHz frequencies. In this paper, a methodology of band rejection/addition for microstrip antennas design using slot line theory and current distribution analysis has been introduced and analyzed. The analysis and design are done by a commercial software. The radiation characteristics, such as; return loss, VSWR, input impedance, and the surface current densities have been introduced and discussed. Finally, the proposed optimum antenna design structure has been fabricated and the measured S-parameters of the proposed structure can be analyzed with network analyzer and compared with simulation results to demonstrate the excellent performance and meet the requirements for wireless communication applications.

Water content of latent fingerprints - Dispelling the myth. <=SEP=> Changing procedures in the handling of rare and precious documents in museums and elsewhere, based on assumptions about constituents of latent fingerprints, have led the author to an examination of available data. These changes appear to have been triggered by one paper using general biological data regarding eccrine sweat production to infer that deposited fingerprints are mostly water. Searching the fingerprint literature has revealed a number of reference works similarly quoting figures for average water content of deposited fingerprints of 98% or more. Whilst accurate estimation is difficult there is no evidence that the residue on fingers could be anything like 98% water, even if there were no contamination from sebaceous glands. Consideration of published analytical data of real fingerprints, and several theoretical considerations regarding evaporation and replenishment rates, indicates a probable initial average water content of a fingerprint, soon after deposition, of 20% or less.

A multiscale measure for mixing <=SEP=> We present a multiscale measure for mixing that is based on the concept of weak convergence and averages the “mixedness” of an advected scalar field at various scales. This new measure, referred to as the Mix-Norm, resolves the inability of the L2 variance of the scalar density field to capture small-scale variations when advected by chaotic maps or flows. In addition, the Mix-Norm succeeds in capturing the efficiency of a mixing protocol in the context of a particular initial scalar field, wherein Lyapunov-exponent based measures fail to do so. We relate the Mix-Norm to the classical ergodic theoretic notion of mixing and present its formulation in terms of the power spectrum of the scalar field. We demonstrate the utility of the Mix-Norm by showing how it measures the efficiency of mixing due to various discrete dynamical systems and to diffusion. In particular, we show that the Mix-Norm can capture known exponential and algebraic mixing properties of certain maps. We also analyze numerically the behaviour of scalar fields evolved by the Standard Map using the Mix-Norm. © 2005 Elsevier B.V. All rights reserved.

Artificial cooperative search algorithm for numerical optimization problems <=SEP=> In this paper, a new two-population based global search algorithm, the Artificial Cooperative Search Algorithm (ACS), is introduced. ACS algorithm has been developed to be used in solving real-valued numerical optimization problems. For purposes of examining the success of ACS algorithm in solving numerical optimization problems, 91 benchmark problems that have different specifications were used in the detailed tests. The success of ACS algorithm in solving the related benchmark problems was compared to the successes obtained by PSO, SADE, CLPSO, BBO, CMA-ES, CK and DSA algorithms in solving the related benchmark problems by using Wilcoxon Signed-Rank Statistical Test with Bonferroni-Holm correction. The results obtained in the statistical analysis demonstrate that the success achieved by ACS algorithm in solving numerical optimization problems is better in comparison to the other computational intelligence algorithms used in this paper. 2012 Elsevier Inc. All rights reserved.

Abstraction Refinement for Probabilistic Software <=SEP=> ion Refinement for Probabilistic Software Mark Kattenbelt, Marta Kwiatkowska, Gethin Norman, and David Parker Oxford University Computing Laboratory, Parks Road, Oxford, OX1 3QD Abstract. We present a methodology and implementation for verifying ANSI-C programs that exhibit probabilistic behaviour, such as failures or randomisation. We use abstraction-refinement techniques that represent We present a methodology and implementation for verifying ANSI-C programs that exhibit probabilistic behaviour, such as failures or randomisation. We use abstraction-refinement techniques that represent probabilistic programs as Markov decision processes and their abstractions as stochastic two-player games. Our techniques target quantitative properties of software such as “the maximum probability of file-transfer failure” or “the minimum expected number of loop iterations” and the abstractions we construct yield lower and upper bounds on these properties, which then guide the refinement process. We build upon stateof-the-art techniques and tools, using SAT-based predicate abstraction, symbolic implementations of probabilistic model checking and components from GOTO-CC, SATABS and PRISM. Experimental results show that our approach performs very well in practice, successfully verifying actual networking software whose complexity is significantly beyond the scope of existing probabilistic verification tools.

A study of SSL Proxy attacks on Android and iOS mobile applications <=SEP=> According to recent articles in popular technology websites, some mobile applications function in an insecure manner when presented with untrusted SSL certificates. These non-browser based applications seem to, in the absence of a standard way of alerting a user of an SSL error, accept any certificate presented to it. This paper intends to research these claims and show whether or not an invisible proxy based SSL attack can indeed steal user's credentials from mobile applications, and which types applications are most likely to be vulnerable to this attack vector. To ensure coverage of the most popular platforms, applications on both Android 4.2 and iOS 6 are tested. The results of our study showed that stealing credentials is indeed possible using invisible proxy man in the middle attacks.

Transient effects in application of PWM inverters to induction motors <=SEP=> Standard squirrel cage induction motors are subjected to nonsinusoidal wave shapes, when supplied from adjustable frequency inverters. In addition to causing increased heating, these wave patterns can be destructive to the insulation. Pulse width modulated (PWM) inverter output amplitudes and risetimes are investigated, and motor insulation capabilities are discussed. Voltage reflections are simulated for various cable lengths and risetimes and are presented graphically. Simulations confirm potential problems with long cables and short risetimes. Application precautions are also discussed.<<ETX>>

Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction <=SEP=> Recidivism prediction scores are used across the USA to determine sentencing and supervision for hundreds of thousands of inmates. One such generator of recidivism prediction scores is Northpointe's Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) score, used in states like California and Florida, which past research has shown to be biased against black inmates according to certain measures of fairness. To counteract this racial bias, we present an adversarially-trained neural network that predicts recidivism and is trained to remove racial bias. When comparing the results of our model to COMPAS, we gain predictive accuracy and get closer to achieving two out of three measures of fairness: parity and equality of odds. Our model can be generalized to any prediction and demographic. This piece of research contributes an example of scientific replication and simplification in a high-stakes real-world application like recidivism prediction.

Perpetual development: A model of the Linux kernel life cycle <=SEP=> Software evolution is widely recognized as an important and common phenomenon, whereby the system follows an ever-extending development trajectory w ith intermittent releases. Nevertheless there have been only few lifecycle models that attempt to por tray such evolution. We use the evolution of the Linux kernel as the basis for the formulation of such a model, integrating the progress in time with growth of the codebase, and differentiating bet ween development of new functionality and maintenance of production versions. A unique elem nt of the model is the sequence of activities involved in releasing new production versions, and how this has changed with the growth of Linux. In particular, the release follow-up phase before th forking of a new development version, which was prominent in early releases of production ve rsions, has been eliminated in favor of a concurrent merge window in the release of 2.6.x versions . We also show that a piecewise linear model with increasing slopes provides the best descr iption of the growth of Linux. The perpetual development model is used as a framework in which c ommonly recognized benefits of incremental and evolutionary development may be demonstra ted, nd to comment on issues such as architecture, conservation of familiarity, and failed p rojects. We suggest that this model and variants thereof may apply to many other projects in additio n to Linux.