Miracle-dz/UniFAR-FTUs huggingface dataset:
Too Darned Big to Test

The increasing size and complexity of software, coupled with concurrency and distributed systems, has made apparent the ineffectiveness of using only handcrafted tests. The misuse of code coverage and avoidance of random testing has exacerbated the problem. We must start again, beginning with good design (including dependency analysis), good static checking (including model property checking), and good unit testing (including good input selection). Code coverage can help select and prioritize tests to make you more efficient, as can the all-pairs technique for controlling the number of configurations. Finally, testers can use models to generate test coverage and good stochastic tests, and to act as test oracles.
Neural networks direct adaptive control for a class of MIMO uncertain nonlinear systems

This paper presents a direct adaptive control scheme based on multi-layer neural networks for a class of multi-input multi-output (MIMO) nonlinear systems with unknown nonlinearity. The on-line updating rules of the neural networks parameters are obtained by Lyapunov stability theory. All signals in the closed-loop system are bounded and the output tracking error converges to a small neighborhood of zero. In this sense the closed-loop system is stable. The effectiveness of the control scheme is verified by a simulation of two link manipulator.
OOREA: An Object-Oriented Resources, Events, Agents Model for Enterprise Systems Design

A number of modeling approaches have been proposed in the literature for designing business information systems. This paper critiques prior data modeling approaches and presents an integrated object-oriented modeling approach that captures both the structural and the behavioral aspects of the business domain. Although there is considerable interest in object-oriented (OO) technologies in practice and in the information systems literature, there is no widely accepted OO modeling approach that facilitates the identification of objects from a business information processing perspective. Based on McCarthy’s (1982) resources, events, agents (REA) framework, the business process focused object-oriented ontology presented in this paper identifies the key resources, events, and agents in an enterprise information systems context. Termed OOREA, the ontology extends McCarthy’s REA model by capturing both the structural aspects of modeling, in terms of the objects of interest in the domain, and also the behavioral aspects in terms of the processes that modify objects. Application of the model is illustrated in the context of sales and related events for a retailing enterprise.
Automatic Construction of Biological Abbreviation Dictionary from Abstracts of Biomedical Papers

Integration of knowledge described in a huge number of biomedical papers is a very important subject in the genome informatics area [1, 2]. Therefore, we need an intelligent information extracting system to save time. In order to extract information or knowledge from texts and utilize them, it is necessary to use various kinds of dictionaries, which are helpful in eliminating obscurities contained in natural languages (e.g. ambiguity and polysemy). We sought to develop a protein name abbreviation dictionary (PNAD) in an automatic way.
Combat PTSD and Implicit Behavioral Tendencies for Positive Affective Stimuli: A Brief Report

Background: Prior cognitive research in posttraumatic stress disorder (PTSD) has focused on automatic responses to negative affective stimuli, including attentional facilitation or disengagement and avoidance action tendencies. More recent research suggests PTSD may also relate to differences in reward processing, which has lead to theories of PTSD relating to approach-avoidance imbalances. The current pilot study assessed how combat-PTSD symptoms relate to automatic behavioral tendencies to both positive and negative affective stimuli. Method: Twenty male combat veterans completed the approach-avoidance task (AAT), Clinician Administered PTSD Scale, Beck Depression Inventory-II, and State-Trait Anger Expression Inventory-II. During the AAT, subjects pulled (approach) or pushed (avoid) a joystick in response to neutral, happy, disgust, and angry faces based on border color. Bias scores were calculated for each emotion type (avoid-approach response latency differences). Main and interaction effects for psychological symptom severity and emotion type on bias score were assessed using linear mixed models. Results: There was a significant interaction between PTSD symptoms and emotion type, driven primarily by worse symptoms relating to a greater bias to avoid happy faces. Post hoc tests revealed that veterans with worse PTSD symptoms were slower to approach as well as quicker to avoid happy faces. Neither depressive nor anger symptoms related to avoid or approach tendencies of emotional stimuli. Conclusion: Posttraumatic stress disorder severity was associated with a bias for avoiding positive affective stimuli. These results provide further evidence that PTSD may relate to aberrant processing of positively valenced, or rewarding stimuli. Implicit responses to rewarding stimuli could be an important factor in PTSD pathology and treatment. Specifically, these findings have implications for recent endeavors in using computer-based interventions to influence automatic approach-avoidance tendencies.
Event Contour: An Efficient and Robust Mechanism for Tasks in Sensor Networks

In large-scale sensor networks, due to the energy and communication constraints of each sensor, it is infeasible to collect event information from each individual sensor and process it at the sink. In this paper, we propose an efficient data-collection scheme that can be used for event monitoring and network-wide diagnosis. Our scheme relies on the well-known representation of data – contour maps, which trade off accuracy with the number of samples. To build the contour maps, we propose three novel algorithms: a distributed spatial and temporal data suppression algorithm, a reconstruction algorithm at the sink using interpolation and smoothing, and an efficient algorithm to convey routing information for extending data suppression over multiple hops. The error in data representation accuracy is bounded by a simple design parameter of our choice. By reducing the number of transmissions required to convey relevant information to the sink, the contour mapping strategy conserves power at sensor nodes and improves network lifetime. We also present novel and scalable security mechanisms to defend against the injection of forged reports. Our security mechanism uses location-based keys and is much more secure than existing schemes using node-based keys. Our scheme is suited for accomplishing many tasks in sensors networks: (1) It presents a global picture of the network in both temporal and spatial domains. (2) It can be used as a diagnosis tool, e.g., to detect faulty sensors and to scan for residual energy. (3) It can work in concert with in-network aggregation schemes to further reduce the communication overhead of aggregation schemes. It requires only negligible processing and storage requirements in sensors, thereby allowing for the sensor networking paradigm of "dumb sensor, smart sink" which enables economical deployment of large scale sensor networks. Simulation results show that our scheme is resilient to high packet loss rate in the network, and is robust to noise. The design is also energy efficient, resulting in up to an-order-of-magnitude power savings when compared with the base line scheme where every sensor sends its report to the sink.
Computers and Mathematics with Applications Stable Adaptive Fuzzy Control for Mimo Nonlinear Systems

In this paper, an indirect adaptive fuzzy control scheme is presented for a class of multi-input and multi-output (MIMO) nonlinear systems whose dynamics are poorly understood. Within this scheme, fuzzy systems are employed to approximate the plant's unknown dynamics. In order to overcome the controller singularity problem, the estimated gain matrix is decomposed into the product of one diagonal matrix and two orthogonal matrices, a robustifying control term is used to compensate for the lumped errors, and all parameter adaptive laws and robustifying control term are derived based on Lyapunov stability analysis. The proposed scheme guarantees that all the signals in the resulting closed-loop system are uniformly ultimately bounded (UUB). Moreover, the tracking errors can be made small enough if the designed parameter is chosen to be sufficiently large. A simulation example is used to demonstrate the effectiveness of the proposed control scheme.
Design of a solid-state file using flash EEPROM

This paper presents dynamic sector allocation, clustered sector allocation, and background garbage ~ h ~ ~ that are key algorithms in solid-state files (SSFs) using flash EEPROMs. Dynamic sector allocation resembles a log-structured file system, which sequentially writes all data modifications to the SSF. Clustered sector allocation is a technique for using the dynamic sector allocation mechanism in an SSF that incorporates a NAND flash EEPROM architecture. Dynamic sector allocation inevitably accumulates obsolete data on the SSF. This “garbage” must be erased in order to secure free space on the SSF. The garbage collection mechanism is a free-space-management method performed as a background process in the SSF. These three mechanisms are closely related and work collaboratively to enable flash EEPROMs to perform well in spite of the serious inherent limitations of the devices. We simulated the behavior of several SSFs and observed that 30% of the storage area of the SSFs must be used as a work area in order to ensure an acceptably low rate of memory-erase operations. We also demonstrated that the lifetime of the SSF is long enough for use in most personal computers. Finally, we have developed SSFs using the NAND type of flash EEPROMs that incorporate the above mechanisms.
A New Approach for Multicast Congestion Control using Asymmetric Paths

This paper introduces an efficient and new multicast congestion control algorithm for asymmetric paths. In the current Internet scenario streaming applications becomes popular and which uses multicast approach. Congestion control in multicast protocol is a difficult task and lot of research is going in this area. To enhance the bandwidth utilization, instead of symmetric path, an asymmetric path is a viable alternate. But the existing algorithms are not directly applicable for such application. Using new approach protocol the receiver explicitly adjusts its reception rate according to the network conditions using TCP throughput equation and Packet-Pair probe. Its effectiveness has been checked using simulation techniques. The most popular network simulator (NS2) was used in this analysis. It is found that the new approach protocol passes the basic requirements for an effective internet multicast protocol such as responsiveness, efficiency in network utilization, scalability, fairness and TCP-friendliness.
Self-efficacy and psychological well-being of nursing home residents in China: the mediating role of social engagement

Abstract The purpose of this study was to explore the role of self-efficacy and social engagement in psychological well-being of Chinese nursing home residents. A total of 307 residents completed the measurement of social engagement, self-efficacy and psychological well-being. The results showed that satisfaction with physical environment, social support, social activity engagement and self-efficacy were all positively correlated with psychological well-being. At the same time, social engagement partially mediated the effect of self-efficacy on psychological well-being. The results of this study should indicate additional actions for managers of nursing homes and social workers to improve the psychological well-being of older adults.
An Architectural Overview of the Alpha Real-time Distributed Kernel

Alpha is a non-proprietary experimental operating system kernel which extends the real-time domain to encompass distributed applications, such as for telecommunications, factory automation, and defense. Distributed real-time systems are inherently asynchronous, dynamic , and non-deterministic, and yet are nonetheless mission-critical.The increasing complexity and pace of these systems precludes the historical reliance solely on human operators for assuring system dependability under uncertainty. Traditional real-time OS technology is based on attempting to assert or impose determinism of not just the ends but also the means, for centralized low-level sampled-data monitoring and control, with an in-sufficiency of hardware resources. Conventional distributed OS technology is primarily based on two-party client/server hierarchies for explicit resource sharing in networks of autonomous users. These two technological paradigms are special cases which cannot be combined and scaled up cost-effectively to accommodate distributed real-time systems. Al-pha's new paradigm for real-time distributed computing is founded on best-effort management of all resources directly with computation completion time constraints which are expressed as benefit functions; and multiparty, peer-structured, trans-node computations for cooperative mission management.
Finding and Emulating Keyboard, Mouse, and Touch Interactions and Gestures while Crawling RIAs

Existing techniques for crawling Javascript-heavy Rich Internet Applications tend to ignore user interactions beyond mouse clicking, and therefore often fail to consider potential mouse, keyboard and touch interactions. We propose a new technique for automatically finding and exercising such interactions by analyzing and exercising event handlers registered in the DOM. A basic form of gesture emulation is employed to find states accessible via swiping and tapping. Testing the tool against 6 well-known gesture libraries and 5 actual RIAs, we find that the technique discovers many states and transitions resulting from such interactions, and could be useful for cases such as automatic test generation and error discovery, especially for mobile web applications.
IFMADM: An efficient network selection algorithm in integrated heterogeneous wireless network

This paper proposes an algorithm named IFMADM based on maximizing the difference among candidate networks in order to obtain weights of each attribute. Simulation results reveal that it outperforms the AHP-based algorithm in several respects. Firstly, it can not only ensure the accuray of decision making but also improve the distance among candidate networks. Secondly, the changes of number of attributes and candidate networks have less influence on the objectiveness of weighted values of attributes and their importance. Thirdly, ranking abnormality can be avoided efficiently because of large difference among candidate networks.
Socio-Technical Systems: A Meta-Design Perspective

Meta-design of socio-technical systems complies with the need to integrate two types of structures and processes: technical systems, which are engineered to provide anticipatable and reliable interactions between users and systems, and social systems, which are contingent in their interactions and a subject of evolution. Meta-design is focused on objectives, techniques, and processes to allow users to act as designers. It provides, rather than fixed solutions, frameworks within which all stakeholders can contribute to the development of technical functionality and the evolution of the social side, such as organizational change, knowledge construction, and collaborative learning. This paper combines the theoretical framework of meta-design and its underlying principles with the consideration of methodological aspects and practical cases. Five different principles are explored: (1) cultures of participation, (2) empowerment for adaptation and evolution, (3) seeding and evolutionary growth, (4) underdesign of models of socio-technical processes, and (5) structuring of communication. Design collaboratories and knowledge management are used as examples to analyze meta-designed systems representing socio-technical solutions as well as frameworks within which socio-technical solutions can be developed. The combination of theoretical and methodological considerations leads to a set of practical guidelines for meta-designers.
Further investigation of a relic neutralino as a possible origin of an annual – modulation effect in WIMP direct search

We analyze the annual–modulation effect, measured by the DAMA Collaboration with the new implementation of a further two–years running, in the context of a possible interpretation in terms of relic neutralinos. We impose over the set of supersymmetric configurations, selected by the annual– modulation data, the constraints derived from WIMP indirect measurements, and discuss the features of the ensuing relic neutralinos. We critically discuss the sources of the main theoretical uncertainties in the analysis of event rates for direct and indirect WIMP searches. Typeset using REVTEX E–mail: bottino@to.infn. it, donato@lapp.in2p3. fr, fornengo@flamenco.ific. uv.es, scopel@posta.unizar. es INFN Post–doctoral Fellow
A Methodology for Building a Patent Test Collection for Prior Art Search

This paper proposes a methodology for the construction of a patent test collection for the task of prior art search. Key to the justification of the methodology is an analysis of the nature and structure of patent documents and the patenting process. These factors enable a corpus of patent documents to be reverse engineered in order to arrive at high quality, realistic, relevance assessments. The paper first outlines the case for such a prior art search test collection along with the characteristics of patent documents, before describing the proposed method. Further research and development will be directed towards the application of this methodology to create a suite of prior art search topics for the evaluation of patent retrieval systems. We also include a preliminary analysis of its applica
Desarrollo de un modelo de gasificación en equilibrio químico para evaluar el potencial energético del cuesco en plantas extractoras de aceite de palma en Colombia

Introduction: In palm oil extraction plants, for every 10 tons of fresh fruit bunches (FFB) that are processed, an estimate of 3700 kg of waste are produced. This waste, consisting of empty fruit bunches, fibers, and kernels, mainly, has a lower heating value (LHV) of about 18 MJ/kg. This waste can be considered a by-product as it is possible to be used for steam generation or electricity production to completely or partially cover the energy demand of oil palm processing plants. Among these, kernels are the best option for biomass power generation in fixed-bed gasifiers coupled to motor or generator sets for power below 2 MW Objective: Evaluate energy potential of oil palm kernel for power generation in typical oil palm extraction plants trough fixed bed gasification coupled to motor/generator sets. Methodology: A chemical equilibrium model was developed to estimate gas composition and, therefore, energy potential of palm kernel biomass from extractive industries. Results: This tool enables analyzing process variations caused by changes in the gasifying agent, composition and moisture content of biomass. The model was used to analyze kernel energy potential from a typical plant that processes 10000 ton of fresh fruit bunches per month. Model results were validated using data from literature. The model is used to analyze the energy potential of waste from a typical 10000 ton RFF/month extractor plant. Conclusions: It is estimated that for every 22 kg/h of oil palm kernel, approximately 70 kg/h of gas are produced with an average composition of 12.5 % H2, 21.8 % CO, 9.5 % CO2, 56 % N2 and traces of CH4, with a low heat value (LHV) close to 4.1 MJ/Nm3. According to the results, the total electricity demand of a typical plant can be supplied using a gasification-based system feed with ~85 % of the kernel from the extraction process.
A Scalable and Privacy-Preserving Named Data Networking Architecture Based on Bloom Filters

Currently, there are numbers of different architectural proposals for future internet that focus on content-centric networking as the alternative of the existing location-based networking. These architectures give more emphasis on the security part of their paradigms and pay little attention or ignore on issues of privacy in their architectural designs. In this paper we propose the Scalable and Privacy Preserving Routing Protocol in Named Data Networking (SP-NDN) by utilizing the multiple Bloom filters in order to ameliorate user's interest packet flow privacy and security during the transit. In contrast to existing schemes, we present a content-dependent key tree based on multicast key management protocol to integrate Bloom filter and multicast encryption that mitigates the leakage of the original user's keywords and precluding unauthorized users (eavesdroppers) from guessing the key words. Our schemes guarantee the high security and privacy of user's interest packet during the transmission and at the same time trying to minimize the possible increase number of false positives likely to happen when a content is queried.
Spike Event Based Learning in Neural Networks

A scheme is derived for learning connectivity in spiking neural networks. The scheme learns instantaneous firing rates that are conditional on the activity in other parts of the network. The scheme is independent of the choice of neuron dynamics or activation function, and network architecture. It involves two simple, online, local learning rules that are applied only in response to occurrences of spike events. This scheme provides a direct method for transferring ideas between the fields of deep learning and computational neuroscience. This learning scheme is demonstrated using a layered feedforward spiking neural network trained self-supervised on a prediction and classification task for moving MNIST images collected using a Dynamic Vision Sensor.
What if they are right? Network approval, expectations, and relationship maintenance behaviors

Correspondence Andréanne Plamondon, École de Psychologie, Université de Moncton, 18 Antonine-Maillet Avenue, Moncton, NB E1A 3E9, Canada. Email: eap4361@umoncton.ca Mylène Lachance-Grzela, École de Psychologie, Université de Moncton, 18 Antonine-Maillet Avenue, Moncton, NB E1A 3E9, Canada. Email: mylene.lachance-grzela@umoncton.ca This study drew on uncertainty reduction and decisionmaking theories to investigate how perceptions of approval of romantic relationships from family and friends can influence romantic partners' dynamics. Using a dyadic approach, the authors examined whether expectations of a partner's behavior in the relationship mediated the associations between perceived social network approval and relationship maintenance behaviors in a sample of 137 couples. The actor–partner interdependence mediation model (APIMeM) was applied. Results showed that women's and men's perceptions of approval from their own and their partner's network were associated with their own level of expectations of their partner's behaviors. In turn, women's and men's expectations were associated with their own and their partner's maintenance behaviors.