nils-herrmann/clean_scirepeval huggingface dataset:
RID: Finding Reference Count Bugs with Inconsistent Path Pair Checking
Venue: ASPLOS 2016

Reference counts are widely used in OS kernels for resource management. However, reference counts are not trivial to be used correctly in large scale programs because it is left to developers to make sure that an increment to a reference count is always paired with a decrement. This paper proposes inconsistent path pair checking, a novel technique that can statically discover bugs related to reference counts without knowing how reference counts should be changed in a function. A prototype called RID is implemented and evaluations show that RID can discover more than 80 bugs which were confirmed by the developers in the latest Linux kernel. The results also show that RID tends to reveal bugs caused by developers' misunderstanding on API specifications or error conditions that are not handled properly.
Integrating Process Modeling and Simulation with Benchmarking using a Business Process Management System for Local Government

Recently, the strategic approaches of public sector organizations are reevaluated in order to achieve modern effective operations and provide better services to their customers (citizens and businesses) Business Process Management (BPM) solutions are recognized as essential tools for public services transformation, as they enable public organizations to be more efficient, to meet business challenges rapidly and flexibly, and to improve the customers experience by resolving incidents and responding to requests in a timely fashion. Within this context, this paper describes the development of a BPM System (BPMS) as a part of a web based integrated system for benchmarking, monitoring, simulation and redesigning processes. This system will be deployed initially in Municipalities and later on in several Greek government agencies, in order to offer more efficient, personalized and consistent services to citizens and businesses, in a reduced operational cost. The paper presents the methodological approach followed for BPMS development. It also highlights system's functionality and its usefulness in process design, benchmarking, redesign and continuous improvement.
Omnivores Going Astray: A Review and New Synthesis of Abnormal Behavior in Pigs and Laying Hens
Venue: Front. Vet. Sci.

Pigs and poultry are by far the most omnivorous of the domesticated farm animals and it is in their nature to be highly explorative. In the barren production environments, this motivation to explore can be expressed as abnormal oral manipulation directed toward pen mates. Tail biting (TB) in pigs and feather pecking (FP) in laying hens are examples of unwanted behaviors that are detrimental to the welfare of the animals. The aim of this review is to draw these two seemingly similar abnormalities together in a common framework, in order to seek underlying mechanisms and principles. Both TB and FP are affected by the physical and social environment, but not all individuals in a group express these behaviors and individual genetic and neurobiological characteristics play an important role. By synthesizing what is known about environmental and individual influences, we suggest a novel possible mechanism, common for pigs and poultry, involving the brain gut microbiota axis.
Laying performance, digestibility and plasma hormones in laying hens exposed to chronic heat stress as affected by betaine, vitamin C, and/or vitamin E supplementation
Venue: SpringerPlus

Heat stress had a negative effect on laying hens' performance, thus this research was to study the influences of betaine (Bet, 1000 mg/kg betaine) vitamin C (VC, 200 mg/kg ascorbic acid) and vitamin E (VE, 150 mg/kg a Tocopherol acetate) and their possible combinations on egg production, digestibility of nutrients, plasma hormones and reproductive organs of dual purpose hens exposed to chronic heat stress. Two hundred and eighty eight hens and thirty six cocks from 32 to 48 weeks of age were divided into nine treatment groups of four replicates, each containing eight hens and one cock. One group was kept under thermo natural condition and the eight others were kept under chronic heat stress (CHS) One of these eight was used as a negative control, while the others were supplemented with VC, VE and/or betaine and their possible combinations. Body weights, laying rate, feed intake, and feed conversion ratio in hens reared under CHS rooster without any supplementation during 32 to 48 weeks of impairment (P 0.0052) were recorded. Hens reared under heat stress and fed a diet supplemented with either Bet, VC, VE or combination of the supplements increased production traits. However, hens supplemented with VC showed the greatest production traits. Plasma glucose, estradiol 17 (E2) progesterone (P4) tri iodothyronine (T3) and thyroxine (T4) decreased in hens reared under CHS and fed a diet with no supplementation compared to the other treatments (P 0.001) Liver weights, spleen weights, thyroid gland weights, ovary weights, oviduct weights and oviduct lengths were lowest in hens reared under CHS and fed a diet with no supplementation (P 0.0480) In conclusion, dual purpose hens reared under CHS and supplemented with VC at 200 mg/kg diet and Bet at 1000 mg/kg enhanced the laying performance and combated CHS.
A Novel Electrohydraulic Brake System With Tire Road Friction Estimation and Continuous Brake Pressure Control
Venue: IEEE Transactions on Industrial Electronics

The braking system is the main active safety equipment of vehicles. This paper presents a new brake system architecture based on the use of proportional servovalves. The use of servovalves allows for faster and more precise control of the pressure, preventing the wheels from locking and reducing braking distances. A new control block has been developed to determine the optimum pressure in the braking circuit. The new controller is based on the use of fuzzy logic techniques. A Kalman filter based estimation algorithm allows for obtaining the adhesion between the wheel and road surface and vehicle speed. These parameters are used in a fuzzy block to detect the road type. Using the road type, an artificial neural network gives an estimation of the slip that produces higher adhesion, and a final block, which is also based on fuzzy logic, determines the optimal pressure in the braking circuit. The performance of the new brake architecture and controller is evaluated by simulating driving on different road surfaces and with real tests on dry and wet asphalt.
High Speed Inter Satellite Communication System by Incorporating Hybrid Polarization Wavelength Division Multiplexing Scheme

Inter Satellite communication is one of remarkable technologies that can be used to communicate between satellites. This work is focused to carry out the investigations of polarization scheme by incorporating dense wavelength division multiplexing (DWDM) scheme in inter satellite communication system. A 20x6 Gbps data are transported over inter satellite optical link having span of 5,000 km to realize the total data transmission of 120 Gbps. Moreover, results are also reported with the effect of RZ and NRZ modulation schemes. The performance of proposed inter satellite communication link is measured in terms of signal to noise ratio, received power and eye diagrams.
Supply analysis in wheat industry: contributions of value chain analysis in Ethiopia: Cases from Arsi and East Shewa Zones in Oromia National and Regional State

In this paper an attempt is made to analyse factors affecting supply issues at different functional nodes of Wheat Value Chain (WVC) flow of commodities and roles of cooperatives and other institutions in supply issues. Sources of primary data include input suppliers, service providers, wheat producers, traders, cooperatives, wheat processing industries. Interview schedules, informal group discussions and observations were used to collect primary data from actors in wheat value chain. The sample design was multiple sampling stages, zones as first stage sampling unit, districts as second stage sampling unit, kebeles as third stage sampling unit and key WVC actors as fourth stage sampling unit. Factors of supply issues in wheat industry has been analyzed with the help of descriptive statistics, qualitative methods and stepwise multiple regression (OLS) The result indicates that cooperative as actor has failed to supply adequate input, namely pesticide and herbicide caused input retailers to manifest their opportunistic behavior and exploit asymmetric information on input quality at small shops and spot market, which in turn, declined wheat productivity. Wheat producer's marketed surplus significantly increased with land size, fertilizer, extension service, and distance from main road, producer's WVC function, and decreased with crop rotation. About 90% of wheat processing industries ranked shortage of raw materials as the number one barrier for wheat product supply. Concerned body should work on technology and extension service supply and coordination to address low raw materials and final products supply at each functional node of wheat value chain.
Milk value chain analysis: industry competitiveness and the dairy policy environment in Pakistan

I ACKNOWLEDGEMENTS V COMMON LOCAL TERMINOLOGIES, MILK QUANTITY UNITS, AND QUALITY TESTING X TABLE OF CONTENTS XIV TABLE LIST XXI CHAPTER 1.  TO THE RESEARCH 1 RESEARCH PROBLEM AND RESEARCH QUESTIONS 2 THESIS DESIGN, METHODOLOGY, AND METHODS USED 2 DELIMITATIONS OF SCOPE AND KEY ASSUMPTIONS 6 CONCLUSION 7 CHAPTER 2.  INDUSTRY COMPETITIVENESS AND THE DAIRY POLICY ENVIRONMENT IN PAKISTAN 8 THE WORLD 8 PAKISTAN 11 MACROECONOMY, AGRICULTURE, LIVESTOCK AND EMPLOYMENT 11 POPULATION,  IN A MIXED CROP LIVESTOCK FARMING SYSTEM 15 MILK SUPPLY AND DEMAND 18 FOOD SYSTEMS 23 COMPETITION AND THE ROLE OF FIRMS IN A MARKET ECONOMY, COMPETITIVE ADVANTAGE, AND THE VALUE CHAIN 24
Upgrading and exploitation in the fishing industry: Contributions of value chain analysis

This article presents a framework for fisheries sector analysis based on the literatures on global value chains (GVCs) and global production networks (GPNs) A value chain approach offers an alternative to focusing primarily on policy as an explanatory variable, by bringing into focus relations among buyers, sellers and other stakeholders as well as their institutional context. After outlining the utility of this approach, the article identifies three questions at the forefront of contemporary debates on the dynamics of GVCs and GPNs. Namely: (1) How institutional context affects distributional and regulatory outcomes; (2) The conditions under which particular institutions that limit or regulate market forces are either productive or perverse; and (3) Why and how particular markets are constituted in the ways that they are. The article then showcases some of the central findings from the case studies brought together in this thematic issue, demonstrating how they contribute to current analytic debates surrounding value chains and core substantive problems facing both fisheries and those engaged in the fishing industry.
Teaching Hemingway and War

In 1925, Ernest Hemingway wrote to F. Scott Fitzgerald that "the reason you are so sore you missed the war is because the war is the best subject of all. It groups the maximum of material and speeds up the action and brings out all sorts of stuff that normally you have to wait a lifetime to get." Though a world war veteran for seven years, at the time he wrote Fitzgerald, Hemingway had barely scratched the surface of his war experiences in his writing, yet it would be a subject he could never resist. As an eyewitness to the emergence of modern warfare, through the Second World War, and as a writer devoted to recreating experience on the page, Ernest Hemingway has gifted us with an oeuvre of wartime representation ideal for the classroom. Teaching Hemingway and War offers fifteen original essays on Hemingway's relationship to war with a variety of instructional settings in mind, and the contributors bring to the volume a range of experience, backgrounds, and approaches. Some of the topics included are: The Violence of Story: Teaching In Our Time and Narrative Rhetoric* Hemingway's Maturing View of the Spanish Civil War* Robert Jordan's Philosophy of War in For Whom the Bell Tolls* Hemingway, PTSD, and Clinical Depression* Perceptions of Pain in The Sun Also Rises* Across the River and into the Trees as Trauma LiteratureThe final section provides three excellent undergraduate essays as examples of what students are capable of producing and as contributions to Hemingway studies in their own right.
Deformable image registration for adaptive radiotherapy with guaranteed local rigidity constraints
Venue: Radiation oncology

BackgroundDeformable image registration (DIR) is a key component in many radiotherapy applications. However, often resulting deformations are not satisfying, since varying deformation properties of different anatomical regions are not considered. To improve the plausibility of DIR in adaptive radiotherapy in the male pelvic area, this work integrates a local rigidity deformation model into a DIR algorithm. DIR framework is extended by constraints, enforcing locally rigid deformation behavior for arbitrary delineated structures. The approach restricts those structures to rigid deformations, while surrounding tissue is still allowed to deform elastically. The algorithm is tested on ten CT/CBCT male pelvis datasets with active rigidity constraints on bones and prostate and compared to the Varian SmartAdapt deformable registration (VSA) on delineations of bladder, prostate and bones.ResultsThe approach with no rigid structures (REG0) obtains an average dice similarity coefficient (DSC) of 0.87 0.06 and a Hausdorff Distance (HD) of 8.74 5.95 mm. The new approach with rigid bones (REG1) yields a DSC of 0.87 0.07, HD 8.91 5.89 mm. Rigid deformation of bones and prostate (REG2) obtains 0.87 0.06, HD 8.73 6.01 mm, while VSA yields a DSC of 0.86 0.07, HD 10.22 6.62 mm. No deformation grid foldings are observed for REG0 and REG1 in 7 of 10 cases; for REG2 in 8 of 10 cases, with no grid foldings in prostate, an average of 0.08 in bladder (REG2: no foldings) and 0.01 inside the body contour. VSA exhibits grid foldings in each case, with an average percentage of 1.81 for prostate, 1.74 for bladder and 0.12 for the body contour. While REG1 and REG2 keep bones rigid, elastic bone deformations are observed with REG0 and VSA. An average runtime of 26.2 s was achieved with REG1; 31.1 s with REG2, compared to 10.5 s with REG0 and 10.7 s with VMS.ConclusionsWith accuracy in the range of VSA, the new approach with constraints delivers physically more plausible deformations in the pelvic area with guaranteed rigidity of arbitrary structures. Although the algorithm uses an advanced deformation model, clinically feasible runtimes are achieved.
Improved Techniques for Training GANs
Venue: NIPS

We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework. We focus on two applications of GANs: semi supervised learning, and the generation of images that humans find visually realistic. Unlike most work on generative models, our primary goal is not to train a model that assigns high likelihood to test data, nor do we require the model to be able to learn well without using any labels. Using our new techniques, we achieve state of the art results in semi supervised classification on MNIST, CIFAR 10 and SVHN. The generated images are of high quality as confirmed by a visual Turing test: our model generates MNIST samples that humans cannot distinguish from real data, and CIFAR 10 samples that yield a human error rate of 21.3% We also present ImageNet samples with unprecedented resolution and show that our methods enable the model to learn recognizable features of ImageNet classes.
Auditing black box models for indirect influence
Venue: 2016 IEEE 16th International Conference on Data Mining (ICDM)

Data trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper understanding of model behavior and in particular how different features influence the model prediction. This is important when interpreting the behavior of complex models or asserting that certain problematic attributes (such as race or gender) are not unduly influencing decisions. In this paper, we present a technique for auditing black box models, which lets us study the extent to which existing models take advantage of particular features in the data set, without knowing how the models work. Our work focuses on the problem of indirect influence: how some features might indirectly influence outcomes via other, related features. As a result, we can find attribute influences even in cases where, upon further direct examination of the model, the attribute is not referred to by the model at all. Our approach does not require the black box model to be retrained. This is important if, for example, the model is only accessible via an API, and contrasts our work with other methods that investigate feature influence such as feature selection. We present experimental evidence for the effectiveness of our procedure using a variety of publicly available data sets and models. We also validate our procedure using techniques from interpretable learning and feature selection, as well as against other black box auditing procedures. To further demonstrate the effectiveness of this technique, we use it to audit a black box recidivism prediction algorithm.
Auditing Black Box Models for Indirect Influence
Venue: ICDM

Data trained predictive models see widespread use, but for the most part they are used as black boxes which output a prediction or score. It is therefore hard to acquire a deeper understanding of model behavior, and in particular how different features influence the model prediction. This is important when interpreting the behavior of complex models, or asserting that certain problematic attributes (like race or gender) are not unduly influencing decisions. In this paper, we present a technique for auditing black box models, which lets us study the extent to which existing models take advantage of particular features in the dataset, without knowing how the models work. Our work focuses on the problem of indirect influence: how some features might indirectly influence outcomes via other, related features. As a result, we can find attribute influences even in cases where, upon further direct examination of the model, the attribute is not referred to by the model at all. Our approach does not require the black box model to be retrained. This is important if (for example) the model is only accessible via an API, and contrasts our work with other methods that investigate feature influence like feature selection. We present experimental evidence for the effectiveness of our procedure using a variety of publicly available datasets and models. We also validate our procedure using techniques from interpretable learning and feature selection, as well as against other black box auditing procedures.
Adaptive management of multimodal biometrics fusion using ant colony optimization
Venue: Inf. Fusion

Adaptive fusion of multimodal biometrics using an ant colony optimization framework.Comparative performance evaluation from decision and score level fusion strategies.Experiments on publicly available databases ascertain superiority of ACO over PSO.Evaluation of ACO framework for fuzzy binary decision tree based verification.Comparative verification using decision tree and decision threshold in ACO framework. This paper presents a new approach for the adaptive management of multimodal biometrics to meet a wide range of application dependent adaptive security requirements. In this work, ant colony optimization (ACO) is employed for the selection of key parameters like decision threshold and fusion rule, to ensure the optimal performance in meeting varying security requirements during the deployment of multimodal biometrics systems. Particle swarm optimization (PSO) has been widely utilized for the optimal selection of these parameters in the earlier attempts in the literature [Veeramachaneni et al. 2005] and [Kumar et al. 2010] However, in PSO these parameters are computed in continuous domain while they are assumed to be better represented as discrete variables [Kumar et al. 2010] This paper therefore proposes the use of ACO, in which discrete biometric verification parameters are computed to ensure the optimal performance from the multimodal biometrics system. The proposed ACO based framework is also extended to the pattern classification approach where fuzzy binary decision tree (FBDT) is utilized for two class biometrics verification. The experimental results are presented on true multimodal systems from various publicly available databases; IITD databases of palmprint and iris, XM2VTS database of speech and faces, and the NIST BSSR1 databases of faces and fingerprint images. Our experimental results presented in this paper suggest that (i) ACO based approach is capable of operating on significantly small error rates in comparison to the widely employed PSO for automated selection of biometrics fusion rules/parameters, (ii) the score level fusion yields better performance with lower error rate in comparison to the decision level fusion, and finally (iii) the FBDT based classification approach delivers considerably superior performance for the adaptive biometrics verification.
Untangling the wine metabolome by combining untargeted SPME GCxGC TOF MS and sensory analysis to profile Sauvignon blanc co fermented with seven different yeasts
Venue: Metabolomics

Saccharomyces cerevisiae (SC) is the main driver of alcoholic fermentation, however for aroma and flavor formation in wine, non Saccharomyces species can have a powerful effect. This study aimed to compare untargeted volatile compound profiles from SPME GCxGC TOF MS and sensory analysis data of Sauvignon blanc wine inoculated with six different non Saccharomyces yeasts followed by SC. Torulaspora delbrueckii (TD) Lachancea thermotolerans (LT) Pichia kluyveri (PK) and Metschnikowia pulcherrima (MP) where commercial starter strains, while Candida zemplinina (CZ) and Kazachstania aerobia (KA) were isolated from wine grape environments. Each wine showed a distinct profile both sensorially and chemically. SC and CZ wines were the most distinct in both of these cases. SC wine had guava, grapefruit, banana, and pineapple aromas while CZ wine was driven by fermented apple, dried peach/apricot, and stewed fruit as well as sour flavor. Chemically over 300 unique features were identified as significantly different across the fermentations. SC wine had the highest number of esters in the highest relative concentration but all the yeasts had distinct ester profiles. CZ wine displayed the highest number of terpenes in high concentration but also produced a large amount of acetic acid. KA wine was high in ethyl acetate. TD wine had fewer esters but three distinctly higher thiol compounds. LT wine showed a relatively high number of increased acetate esters and certain terpenes. PK wine had some off odor compounds while the MP wine had high levels of methyl butyl methyl propyl and phenethyl esters. Overall, this study gives a more detailed profile of these yeasts contribution to Sauvignon blanc wine than previously reported.