Miracle-dz/UniFAR-FTUs huggingface dataset:
PARTIAL UNFOLDING FOR COMPOSITIONAL NONBLOCKING VERIFICATION OF EXTENDED FINITE-STATE MACHINES

This working paper describes a framework for compositional nonblocking verification of reactive systemsmodelled as extended finite-state machines. The nonblocking property can capture the absence of livelocks and deadlocks in concurrent systems. Compositional verification is shown in previous work to be effective to verify this property for large discrete event systems. Here, these results are applied to extended finite-state machines communicating via shared memory. The model to be verified is composed gradually, simplifying components through abstraction at each step, while conflict equivalence guarantees that the final verification result is the same as it would have been for the non-abstracted model. The working paper concludes with an example showing the potential of compositional verification to achieve substantial state-space reduction.
The effect of cognitive reflection on the efficacy of impression management

Purpose The purpose of this paper is to investigate whether analysts’ personal cognitive traits mitigate the efficacy of graphical impression management. Design/methodology/approach Three experiments are conducted wherein 525 professional accountants working as financial analysts rate a hypothetical company’s performance graph depicting its net income trend. The manipulation is the presence (absence) of impression management techniques. Hypotheses test whether different techniques are effective and whether analysts’ cognitive reflection ability mitigates manipulation efficacy. Findings Presentation enhancement is effective only with impulsive analysts, showing the weakness of this technique through the use of colors. Measurement distortion and selectivity techniques are effective for reflective and impulsive analysts; however, reflective analysts are more critical about graphs prepared via selectivity that emphasize profit recovery following crises. Research limitations/implications Each impression management technique is investigated in isolation and in controlled conditions. Further research could consider how personal cognitive traits impact the efficacy of combined techniques and whether imbedding manipulated graphs with other information mitigates impression management efficacy. Practical implications Research on impression management is mostly “task-oriented;” few “people-oriented” studies focus on decision making by those using financial reports. Users’ cognitive reflection ability is shown to undermine the efficacy of some impression management techniques. Social implications Financial analysts, auditors and regulators could develop mechanisms to avoid pervasive usage of (or enhance skepticism regarding) techniques not mitigated by users’ reflectiveness. Originality/value Evidence from financial analysts with an accounting background provides insights on individual characteristics’ influence on graphical impression management efficacy.
AN AGGREGATE MULTI-LOOP CONTROL FOR A DC SERVODRIVE. THE DESIGN OF THE NEURO-FUZZY CONTROLLER.

The purpose of the study is the synthesis of a reliable and robust fuzzy controller for a 2 order DC servodrive. A first step is to prepare the computations associated to the main control loops for the above mentioned servosystem. This approach aims to aggregate the relations for the position and the velocity loops as an unique computation formula expressed into the variables specific for the real-time processing, optimized and adapted to a microcontroller arithmetic. The systemic variables considered are the position error and its variation during a sampling period, this second input into the next neuro-fuzzy control having the physical meaning of the speed. Both variables are expressed as dependences of the number of encoder impulses delivered during the sampling time. A second step is the design of a neuro-fuzzy controller for both the control loops. The ANFIS method uses training data delivered by the well tuned conventional control structure for generating a DISO fuzzy controller. Some special blocks were added to the standard structure in order to improve the IN-OUT data quality. Appreciations are made for the quality of the training process and the characteristics of the fuzzy inference system are presented. A subsequent paper will analyze the system with the neuro-fuzzy controller and its real time-time implementation.
Next Generation Manufacturing Systems and the Virtual Enterprise

Abstract Next Generation Manufacturing Systems (NGMS) will support the Next Generation Manufacturing Enterprises (NGMEs). Adaptive distributed manufacturing systems seem to be a promising solution for NGMEs to provide increased levels of flexibility, reconfigurability and intelligence to respond to the highly dynamic market demands. Virtual Enterprises (VEs) are expected to be the dominant manufacturing enterprise model in the 21st Century. VEs promise new possibilities where a manufacturing system is not know in advance and has to be structured, optimized and implement from scratch to produce e.g. one-of-a-kind products. VEs can approach each industrial project with tailored manufacturing systems represented by a temporary integration of processes capabilities and resources capacities from multiple enterprises in order to meet or exceed the quality-, time- and cost- frame requirements of the customer. VE paradigm represents the future of the NGMEs, and can be also used to provide industrial services in a collaborative way to evolve from physical products to the notion of extended products.
Generalised vectorisation for sparse matrix: vector multiplication

This work generalises the various ways in which a sparse matrix--vector (SpMV) multiplication can be vectorised. It arrives at a novel data structure that generalises three earlier well-known data structures for sparse computations: the Blocked CRS format, the (sliced) ELLPACK format, and segmented scan based formats. The new data structure is relevant since efficient use of new hardware requires the use of increasingly wide vector registers. Normally, the use of vectorisation for sparse computations is limited due to bandwidth constraints. In cases where computations are limited by memory latencies instead of memory bandwidth, however, vectorisation can still help performance. The Intel Xeon Phi, appearing as a component in several top-500 supercomputers, displays exactly this behaviour for SpMV multiplication. On this architecture the use of the new generalised vectorisation scheme increases performance up to 178 percent.
Towards a DevOps Approach for Software Quality Engineering

DevOps is a novel trend in software engineering that aims at bridging the gap between development and operations, putting in particular the developer in greater control of deployment and application runtime. Here we consider the problem of designing a tool capable of providing feedback to the developer on the performance, reliability, and in general quality characteristics of the application at runtime. This raises a number of questions related to what measurement information should be carried back from runtime to design-time and what degrees of freedom should be provided to the developer in the evaluation of performance data. To answer these questions, we describe the design of a filling-the-gap (FG) tool, a software system capable of automatically analyzing performance data either directly or through statistical inference. A natural application of the FG tool is the continuous training of stochastic performance models, such as layered queueing networks, that can inform developers on how to refactor the software architecture.
Oxygenated and water‐soluble organic aerosols in Tokyo

[1] Submicron organic aerosol was measured simultaneously with an Aerodyne aerosol mass spectrometer (AMS) and a particle-into-liquid sampler (PILS) capable of measuring water-soluble organic carbon (WSOC) during the winter and summer of 2004 in Tokyo. Both techniques are being used to investigate the formation of secondary organic aerosol (SOA), and the combined data sets provide unique insights. In summer, about 80% (40–65%) of organic aerosols were oxygenated when scaled by total (carbon) mass concentration, due to high photochemical activity, leading to the active formation of SOA. In winter the fraction of oxygenated organic aerosol is reduced to 39% (total mass base) and 23% (carbon mass base). Previous AMS studies have shown that signals at m/z 44 of the AMS mass spectra of ambient aerosols are dominated by COO+, which typically originates from oxygenated organic aerosols (OOA). The signals at m/z 44 and the derived OOA mass concentrations were highly correlated with WSOC (r2 = 0.78–0.91) throughout these seasons, indicating that OOA and WSOC were very similar in their chemical characteristics. Approximately 88 ± 29% of OOA was found to be water soluble on the basis of the comparison of the WSOC concentrations with those of oxygenated organic carbon (OOC) derived from the AMS data.
Learning Mobile App Usage Routine through Learning Automata

Since its conception, smart app market has grown exponentially. Success in the app market depends on many factors among which the quality of the app is a significant contributor, such as energy use. Nevertheless, smartphones, as a subset of mobile computing devices. inherit the limited power resource constraint. Therefore, there is a challenge of maintaining the resource while increasing the target app quality. This paper introduces Learning Automata (LA) as an online learning method to learn and predict the app usage routines of the users. Such prediction can leverage the app cache functionality of the operating system and thus (i) decreases app launch time and (ii) preserve battery. Our algorithm, which is an online learning approach, temporally updates and improves the internal states of itself. In particular, it learns the transition probabilities between app launching. Each App launching instance updates the transition probabilities related to that App, and this will result in improving the prediction. We benefit from a real-world lifelogging dataset and our experimental results show considerable success with respect to the two baseline methods that are used currently for smartphone app prediction approaches.
Personalizing knowledge delivery services: a conceptual framework

Consistent with the call of the Minnesota Symposium for new theory in knowledge management, we offer a new conceptualization of Knowledge Management Systems (KMS) as a portfolio of personalized knowledge delivery services. Borrowing from research on online consumer behavior, we describe the challenges imposed by personalized knowledge delivery services, and suggest design parameters that can help to overcome these challenges. We develop our design constructs through a set of hypotheses and discuss the research implications of our new conceptualization. Finally, we describe practical implications suggested by our conceptualization - practical suggestions that we hope to gain some experience with as part of an ongoing action research project at our partner organization.
The textual expression of critical thinking in PhD discussions in applied linguistics

The purpose of this study was to identify the textual resources used to express critical thinking in the Discussion chapters or chapter sections of PhD theses from the discipline of Applied Linguistics. Five Discussions were manually analysed using the social genre/cognitive genre model of the author (Bruce, 2008a) as the analytical framework. Three generic elements, used integratively, were found to express critical evaluations as part of constructing an overall argument in the Discussion chapters examined. The first element was the recursive use of an organizing content schema (move pattern), described as: Point, Support, Evaluation. The second was the use of key coherence relations to make critical statements in the ‘Evaluation’ part of this content schema. The third element was the embedding within the critical statements of the metadiscourse devices of hedging and attitude markers (Hyland, 2005). While not providing a prescriptive approach to expressing critical evaluation in this genre, the findings offer an analytical lens through which novice writers may examine and develop awareness of the types of textual resource used to develop this important element of Discussions.
Psychoeducational group activity : A model for clients of rehabilitative work

Since mental health problems are a globally known public health concern, effective prevention of mental health disorders has become an increasingly important part of mental health work. Psychoeducation is an essential part of patient counseling, treatment, rehabilitation and prevention of any long-term or recurring mental health disorders. Little was known about the role, impact and efficacy of psychoeducational group activity in the context of rehabilitative work. Based on the general knowledge of clients of work rehabilitation, it was assumed that the clients would benefit from psychoeducational group intervention aiming to promote mental health and well-being. The aim of this development work was to organize psychoeducational group activity for clients of rehabilitative work program. The purpose was to create a model for group sessions as a part of rehabilitative work. The development project was implemented in cooperation with an organization operating in Central Finland area. The project implementation included three pilot group sessions. The perspective of mental disorder prevention was integrated with services aimed for people suffering from long-term unemployment. The developed model for psychoeducational group activity in work rehabilitation was based on theoretical, evidence-based knowledge and it was structured according to the three pilot group sessions. Future research is needed to understand how psychoeducational approach is supporting the health and well-being of the clients in rehabilitative work services. Keywords/tags Psychoeducation, psychoeducational group intervention, mental disorder prevention, rehabilitative work, development work (subjects) Miscellaneous (Confidential information)
Roles of attention and form in visual motion processing : Psychophysical and brain imaging studies

INTRODUCTION It goes without saying that the human visual information processing system is very complex. Marr (1982) proposed that several principles should be taken into consideration to improve understanding of this complex system. These include the modularity principle and the feedforward principle. The modularity principle assumes that the visual system consists of several processes that are relatively independent of each other in early stages of visual processing (frontend processing). Therefore, each of these processes can be largely examined independently without considering the others. The feedforward principle assumes that the majority of visual functions can be understood without taking feedback effects into consideration. While research that follows these principles has greatly contributed to understanding some important aspects of visual information processing, other important aspects of information processing have been relatively neglected, especially, interactions between different processes and feedback from higher to lower levels (however, see Grossberg & Mingolla, 1985; Koch & Davis, 1994). Research on motion perception is not exceptional in this sense. Over the last decade, as in other aspects of visual processing, the majority of research on the processing of velocity of a moving object has mainly explored feedforward processing within the motion module (for a review, Hildreth & Koch, 1987; Nakayama, 1985; Snowden, 1992).
Quantum Gravity In De Sitter Space

We discuss some general properties of quantum gravity in De Sitter space. It has been argued that the Hilbert space is of finite dimension. This suggests a macroscopic argument that General Relativity cannot be quantized -- unless it is embedded in a more precise theory that determines the value of the cosmological constant. We give a definition of the quantum Hilbert space using the asymptotic behavior in the past and future, without requiring detailed microscopic knowledge. We discuss the difficulties in defining any precisely calculable or measurable observables in an asymptotically de Sitter spacetime, and explore some meta-observables that appear to make mathematical sense but cannot be measured by an observer who lives in the spacetime. This article is an expanded version of a lecture at Strings 2001 in Mumbai.
RECOGNITION OF EMOTIONAL SPEECH AND SPEECH EMOTION IN FARSI

Speech emotion can add extra information to speech in comparison with available textual information. However, it can also lead to some problems in the automatic speech recognition process. We evaluated the changes in speech parameters, i.e. formant frequencies and pitch frequency, due to anger and grief for Farsi language in a former research. Here, using those results, we try to improve emotional speech recognition accuracy using baseline models. We show that adding parameters such as formant and pitch frequencies to the speech feature vector can improve recognition accuracy. The percentage of improvement depends on parameter type, number of mixture components and the emotional condition. Identification of the emotional condition can also help in improving speech recognition accuracy. To recognize emotional condition of speech, formant and pitch frequencies were used successfully in two approaches, namely maximum likelihood and GMM.
Adaptive Control of a Class of Time-Delay Systems

The control of physical systems in the presence of time-delays becomes particularly challenging when parametric uncertainties are present. To cope with these ubiquitous uncertainties, we propose an adaptive controller in this paper that can accommodate both a time-delay and parametric uncertainties. The controller includes a) a control architecture that is based on the plant relative degree rather than the plant order, b) an integral implementation of the well known Posicast Controller so as to accommodate unstable plants, c) high-order tuners for parameter adaptation, and d) a Lyapunov-Krasvoskii functional that allows adaptive stabilization. The controller is shown to be semi-global in the time-delay r and to result in asymptotic tracking. The implications of the adaptive controller are explored in the context of combustion control through simulation studies. Robustness properties of the controller are briefly discussed.
Mixtape Application: Last.fm Data Characterization

This report analyses data collected from Last.fm and used to create a real-time recommendation system. We collected over 2M songs and 1M tags and 372K user's listening habits. We characterize users' profiles: age, playcount, friends, gender and country. We characterized song, artist and tag popularity, genres of songs. Additionally we evaluated the co-occurrence of songs in users' histories, which can be used to compute similarity between songs.
Improving Resource Utilisation in the Cloud Environment Using Multivariate Probabilistic Models

Resource provisioning based on virtual machine (VM) has been widely accepted and adopted in cloud computing environments. A key problem resulting from using static scheduling approaches for allocating VMs on different physical machines (PMs) is that resources tend to be not fully utilised. Although some existing cloud reconfiguration algorithms have been developed to address the problem, they normally result in high migration costs and low resource utilisation due to ignoring the multi-dimensional characteristics of VMs and PMs. In this paper we present and evaluate a new algorithm for improving resource utilisation for cloud providers. By using a multivariate probabilistic model, our algorithm selects suitable PMs for VM re-allocation which are then used to generate a reconfiguration plan. We also describe two heuristics metrics which can be used in the algorithm to capture the multi-dimensional characteristics of VMs and PMs. By combining these two heuristics metrics in our experiments, we observed that our approach improves the resource utilisation level by around 8% for cloud providers, such as IC Cloud, which accept user-defined VM configurations and 14% for providers, such as Amazon EC2, which only provide limited types of VM configurations.
Residues Distal to the Active Site Contribute to Enhanced Catalytic Activity of Variant and Hybrid β-Lactamases Derived from CTX-M-14 and CTX-M-15

ABSTRACT A variety of CTX-M-type extended-spectrum β-lactamases (ESBLs), including hybrid ones, have been reported in China that are uncommon elsewhere. To better characterize the substrate profiles and enzymatic mechanisms of these enzymes, we performed comparative kinetic analyses of both parental and hybrid CTX-M enzymes, including CTX-M-15, -132, -123, -64, -14 and -55, that are known to confer variable levels of β-lactam resistance in the host strains. All tested enzymes were susceptible to serine β-lactamase inhibitors, with sulbactam exhibiting the weakest inhibitory effects. CTX-M-55, which differs from CTX-M-15 by one substitution, A77V, displayed enhanced catalytic activity (kcat/Km) against expanded-spectrum cephalosporins (ESCs). CTX-M-55 exhibits higher structure stability, most likely by forming hydrophobic interactions between A77V and various key residues in different helices, thereby stabilizing the core architecture of the helix cluster, and indirectly contributes to a more stable active site conformation, which in turn shows higher catalytic efficiency and is more tolerant to temperature change. Analyses of the hybrids and their parental prototypes showed that evolution from CTX-M-15 to CTX-M-132, CTX-M-123, and CTX-M-64, characterized by gradual enhancement of catalytic activity to ESCs, was attributed to introduction of different substitutions to amino acids distal to the active site of CTX-M-15. Similarly, the increased hydrolytic activities against cephalosporins and sensitivity to β-lactamase inhibitors, clavulanic acid and sulbactam, of CTX-M-64 were partly due to the amino acids that were different from CTX-M-14 and located at both the C and N termini of CTX-M-64. These data indicate that residues distal to the active site of CTX-Ms contributed to their enhanced catalytic activities to ESCs.
An Extensible Model-Based Mediatior System with Domain Maps

Mediator systems federate and integrate data from disparate sources in order to elicit information that the individual sources cannot provide independently. The standard mediator architecture employs wrappers that translate heterogenous source data into a common (often semistructured) data model like XML. A “mediation engineer” provides an integrated view definition (IVD) on the wrapped XML sources. In such a system, an IVD is ideally expressed in a declarative query language for XML or semistructured data. When developing the IVD, an XML query language provides the mediation engineer only with a tree-structuredmodel of the source,i.e., the names and possible nesting structure of XML elements as defined by an XML DTD, but gives no hint on semantic relationships, class structures, not to mention application domain specific constraints. Indeed, as shown in [4, 1, 3], mediation should be lifted to the conceptual level when mediating across complex sources whose data comes from seemingly disjoint “worlds”,e.g., two neuroscience labs creating information on neurotransmitters and protein distributions, respectively. 1