Miracle-dz/UniFAR-FTUs huggingface dataset:
Elementary Modal Logics – Decidability and Complexity

Modal logic was first introduced by philosophers to study the deductive behaviour of the expressions it is necessary that and it is possible that. Nowadays, it is widely used in several areas of computer science, including formal verification and artificial intelligence. Syntactically, modal logic extends propositional logic by two unary operators: ♦ and . The formal semantics is usually given in terms of Kripke structures. Basically, a Kripke structure is a directed graph, called a frame, together with a valuation of propositional variables. Vertices of this graph are called worlds. For each world truth values of all propositional variables are defined independently. In this semantics, ♦φ means the current world is connected to some world in which φ is true; and φ, equivalent to ¬♦¬φ, means φ is true in all worlds to which the current world is connected. Basic modal logic, as defined above, is rather weak and has limited applications. Thus, numerous variations and extensions of this formalism, including temporal and description logics, have been proposed and investigated. They vary in the complexity of the satisfiability problem, which usually lies between NP and 2EXPTIME. However, even some simple extensions may lead to undecidability (see e.g. [1]). A popular approach to extend modal logic is to restrict the class of admissible Kripke frames. For example, we may require them to be reflexive and transitive (which corresponds to modal logic S4) or enforce their transition relation to be an equivalence relation (S5). There are several ways in which such restrictions can be imposed. We focus on restricting the class of the admissible frames by a first-order logic sentence that uses a single binary relation R, which is interpreted as the transition relation. Eg. , the sentence ∀xyz.xRy ∧ yRz ⇒ xRz defines the class of all transitive frames. Modal logic over a class of frames definable by a first-order logic sentence is called an elementary modal logic. The main goal of our research is to classify all elementary modal logics with respect to decidability and complexity of their satisfiability problems.
Application of a Heat Flux Sensor in Wind Power Electronics

This paper proposes and investigates the application of the gradient heat flux sensor (GHFS) for measuring the local heat flux in power electronics. Thanks to its thinness, the sensor can be placed between the semiconductor module and the heat sink. The GHFS has high sensitivity and yields direct measurements without an interruption to the normal power device operation, which makes it attractive for power electronics applications. The development of systems for monitoring thermal loading and methods for online detection of degradation and failure of power electronic devices is a topical and crucial task. However, online condition monitoring (CM) methods, which include heat flux sensors, have received little research attention so far. In the current research, an insulated-gate bipolar transistor (IGBT) module-based test setup with the GHFS implemented on the base plate of one of the IGBTs is introduced. The heat flux experiments and the IGBT power losses obtained by simulations show similar results. The findings give clear evidence that the GHFS can provide an attractive condition monitoring method for the thermal loading of power devices.
A Probabilistic Model for Melodies

We propose a generative model for melodies in a given musical genre, using symbolic representation of musical data. We first compute melodic features that represent the plausibility of sequences of three consecutive notes. Their probabilistic modeling is an interesting intermediate problem since the cardinality of such features is much lower than the number of sequences of three notes. We then introduce a probabilistic model of melodies given chords and rhythms based on these features. This model leads to significantly higher prediction rates than a simpler Input/Output Hidden Markov Model. Moreover, sampling this model given appropriate musical contexts generates realistic melodies.
A programming model and processor architecture for heterogeneous multicore computers

Heterogeneous multicore computers, those systems that integrate specialized accelerators into and alongside multicore general-purpose processors (GPPs), provide the scalable performance needed by computationally demanding information processing (informatics) applications. However, these systems often feature instruction sets and functionality that significantly differ from GPPs and for which there is often little or no sophisticated compiler support. Consequently developing applications for these systems is difficult and developer productivity is low. This thesis presents Merge, a general-purpose programming model for heterogeneous multicore systems. The Merge programming model enables the programmer to leverage different processor-specific or application domain-specific toolchains to create software modules specialized for different hardware configurations; and provides language mechanisms to enable the automatic mapping of processor-agnostic applications to these processor-specific modules. The Merge programming model has been prototyped on a heterogeneous system consisting of an Intel Core 2 Duo CPU and an Intel X3000 integrated GPU, and a homogeneous 32-way SMP system. Speedups of 3.6×-8.5× using the X3000 and 5.2×-22× using the 32-way system were achieved for a set of informatics applications relative to their single-core C reference implementations. The Merge programming model facilitates heterogeneity throughout the system, including within the processor microarchitecture itself. This thesis presents novel chip-multiprocessor (CMP) with a modular microarchitecture that supports the integration of non-trivial specialized accelerators into GPP cores. The accelerators function as "add-ons", maintaining backward compatibility with existing designs, while offering features from GPUs and other more specialized systems. The extended CMP is evaluated using execution-driven simulation; speedups of up to 2.4× were achieved relative to the base CMP architecture.
Multi-view hand tracking using epipolar geometry-based consistent labeling for an industrial application

This paper addresses a visual tracking and analysis method for automatic monitoring of an industrial manual assembly process, where each worker sequentially picks up components from different boxes during an assembling process. Automatic surveillance of assembling process would enable to reduce assembling errors by giving early warning. We propose a hand tracking and trajectory analysis method from videos captured by several uncalibrated cameras with overlapping views. The proposed method consists of three modules through single-view hand tracking, consistent labeling across views, and optimal decision from multi-view temporal dynamics. The main novelties of the paper include: (a) target model learning with multiple instances through K-means clustering applied to accommodate different levels of light reflection; (b) optimal criterion for consistent labeling of tracked hands across views, based on the symmetric epipolar distance; (c) backward correction of mis-detection by combining epipolar lines with previously tracked results; (d) a multi-view voting scheme for analyzing hand trajectory using binary hand location maps. Experiments have been conducted on videos by multiple uncalibrated cameras, where a person performs assembly operations. Test results and performance evaluation have shown the effectiveness of this method, in terms of multi-view consistent estimation of hand trajectories and accurate interpretation of component assembly actions.
Patterns of CD4/CD8 T-cell ratio in dialysis effluents predict the long-term outcome of peritonitis in patients undergoing peritoneal dialysis.

BACKGROUND The peritoneal immune compartment is a microenvironment with a particular T-cell repertoire and susceptible to local inflammation. To clarify the role of T lymphocytes in peritoneal immunity, the changes in T-cell subpopulations in peritoneal dialysis effluents (PDEs), and their influence on the response to the treatment of peritonitis and on its prognosis were studied in patients undergoing long-term, continuous ambulatory peritoneal dialysis (CAPD). METHODS A cohort of 36 patients treated with CAPD and who had histories of peritonitis were divided into a group with rapid and a group with delayed response to antibiotics, and were followed for 3 years. CD4/CD8 T-cell ratios, T-cell cytokine mRNA expression patterns and transforming growth factor-beta1 (TGF-beta1) concentrations were examined in PDE during bouts of peritonitis. The change in 4 h D/P creatinine during the peritoneal equilibration test (PET) between year 0 and year 3 was expressed as deltaD/P creatinine. RESULTS The serial changes in T-cell subsets in PDE during peritonitis showed two patterns: (i) pattern 1, manifest as a progressive increase in the CD4/CD8 ratio, and associated with a rapid response to treatment; and (ii) pattern 2, manifest as a progressive decrease in the CD4/CD8 ratio, and associated with a delayed response to treatment. The major T-cell phenotypes in PDE during peritonitis were Th1-CD4(+) and Tc2-CD8(+), determined by cloning techniques, RT-PCR and double immunofluorescence staining. TGF-beta1 in the effluent was undetectable in pattern 1 after 7-8 days, but remained detectable at 2 weeks in pattern 2. Pattern 2 patients had a significantly greater decrease (deltaD/P creatinine: -0.198+/-0.086) in solute transport than pattern 1 patients (deltaD/P creatinine: -0.036+/-0.077, P<0.05). CONCLUSIONS These results suggest that a progressive decrease of the CD4/CD8 ratio in PDE correlates with a persistent expression of TGF-beta1, and plays a pathogenetic role in the evolution of peritonitis, PET deterioration and peritoneal fibrosis. Therefore, patterns of CD4/CD8 T-cell ratio in PDE may predict clinical outcomes of peritonitis in CAPD patients.
Context-Aware Access Control Model for Cloud Computing

In view of malicious insider attacks on cloud computing environments, a new ContextAware Access Control Model for cloud computing (CAACM) was presented. According to the characteristic of cloud computing, we take spatial state, temporal state and platform trust level as context. The model establishes mechanisms of authorization from cloud management role to objects, which enables dynamic activation of role permission by associating cloud management role with context. It also achieves fine-grained access control on cloud objects by supervising the permission of management role in full life cycle. Moreover, it introduces the concept of exclusive managerial role, which extends access control from static protection on resources to dynamic authorization on managerial roles. Further, it describes the approach of role permission activation systematically. CAACM formally proves to be safe and it lays the groundwork for the deployment of CAACM in cloud computing systems.
Positive psychology techniques: three good things

This short article is the last in a series of six papers exploring positive psychology coaching techniques. The previous papers have explored the concept of positive coaching psychology and how it may be applied. The focus of this paper is a technique that encourages the mind to pay more attention to good things and develop a mind more observant of the positive in life.
The C Domain of Netrin UNC-6 Silences Calcium/Calmodulin-Dependent Protein Kinase- and Diacylglycerol-Dependent Axon Branching in Caenorhabditis elegans

Second messenger systems mediate neuronal responses to extracellular factors that elicit axon branching, turning, and guidance. We found that mutations in Caenorhabditis elegans that affect components of second messenger systems, a G-protein subunit, phospholipase Cβ, diacylglycerol (DAG) kinase, and calcium/calmodulin-dependent protein kinase (CaMKII), have no obvious effect on axon responses to UNC-6 except in animals in which the N-terminal fragment, UNC-6ΔC, is expressed. In these animals, the mutations enhance or suppress ectopic branching of certain axons. Netrin UNC-6 is an extracellular protein that guides circumferential migrations, and UNC-6ΔC has UNC-6 guidance activity. We propose that the guidance response elicited by the UNC-6 N-terminal domains involves mechanisms that can induce branching that is sensitive to CaMKII- and DAG-dependent signaling, and that the UNC-6 C domain is required incis to the N-terminal domains to silence the branching and to maintain proper axon morphology.
Molecular gas conditions in NGC 4945 and the Circinus galaxy

We present results of a multi-transition study of the dense molecular gas in the central part of the hybrid star-burst/Seyfert galaxies NGC 4945 and the Circinus galaxy. From the results of radiative transfer calculations, we estimate in NGC 4945 $n_{{\rm H}_2}=3 10^3{-}10^4$ cm -3 and $T_{\rm kin}\approx100$ K and in Circinus $n_{{\rm H}_2}=2 10^3{-}10^5$ cm -3 and $T_{\rm kin}\approx50{-}80$ K for the molecular hydrogen density and kinetic temperature, respectively. As well as density/temperature tracing molecules, we have observed C 17 O and C 18 O in each galaxy and the value of C 18 O/C$^{17}{\rm O}\approx6$ for the isotopic column density ratio suggests that both have relatively high populations of massive stars. Finally, although star formation is present, the radiative transfer results combined with the high HCN/CO and (possibly) HCN/FIR, radio/FIR ratios may suggest that, in comparison with Circinus, a higher proportion of the dense gas emission in NGC 4945 may be located in the hypothesised central nuclear disk as opposed to dense star forming cloud cores. Contrary to the literature, which assumes that all of the far-infrared emission arises from star formation, our results suggest that in NGC 4945 some of this emission could arise from an additional source, and so we believe that a revision of the star formation rate estimates may be required for these two galaxies.
Entrepreneurial intention and its influencing factors : a study among UUM undergraduate business students

The purpose of this study is to examine the relationship between risk taking propensity, need for achievement, entrepreneurship education and entrepreneurial intention among UUM undergraduate business students. 350 questionnaires were distributed to the respondents which consist of UUM School of Business Management (SBM) undergraduate students. A total of 338 questionnaires were returned, but only 335 questionnaires were useable for the further analysis. The data collected through this survey was analyzed by using the Statistical Package for Social Science (SPSS) version 22. This study used convenience sampling method where the data collected from population members who are conveniently available to participate in the study. The descriptive analysis was used to determine the respondents‟ profile. Findings of this study revealed that two of the variables, risk taking propensity and need for achievement have positive significant relationship towards entrepreneurial intention. Meanwhile, another one variable, entrepreneurship education has no significant relationship towards entrepreneurial intention. This study could assist in developing, improving and implementing an effective entrepreneurship education. Moreover, it can aid government and also societies in generating the economy through the entrepreneurial activities. Finally, this study proposes several recommendations for future research.
Employment shocks, wages and mobility: Some selected comparisons between Western Germany and the United States

This paper tries an evaluation of west German wage flexibility and mobility of labour in comparison with the United States using micro panel data. Wage regressions and a switching regression model show, that mobility and wages in western Germany react to industrial labour market conditions, while there are no reactions along regional dimensions. In contrast there exist higher degrees of mobility in the United States in both regional and industrial labour markets. Also wages in the U.S. respond to shocks to regional and industrial labour demand. As industrial mobility is higher in the United States, industrial wage respond less to shocks than German wages. Except for west German regional labour market performance, these outcomes correspond to what a competitive model of the labour market would predict. I am grateful to Michael Burda for his comments and support. Many thanks also go to Rolf Tschernig for his comments. This work was in part supported by the German Science Foundation, Sonderforschungsbereich 373 "Quantification and Simulation of Economic Processes", and has been printed using funds made available by the German Science Foundation.
Implementation of High Interaction Honeypot to Analyze the Network Traffic and Prevention of Attacks on Protocol/Port Basis

Network security deals with two types of communities black hats and white hats. The era of security has come when the white hats are not only interested in defending the networks but are keen to make fool of the black hats. Looking at the other side of the mirror, the black hats have also evolved new methods of breaching the security. The work in this paper is based on implementation of low-interaction and high-interaction honeypots along with the deployment of honeywall gateway. Honeywall gateway acts as reverse firewall that allows all type of traffic (both good and bad) to enter the system to facilitate analysis and learning. Honeywall gateway is the heart of the work that is involved in capturing, controlling, and analysis of data. The captured data is further categorized on protocol and port basis. The methodology used can be summarized into three steps: • Monitoring the attack traffic • Analyzing the attack type and method • Responding to the attacker to capture in depth information. The work is intended to analyze the attacker's activities once it is logged and captured by honeywall and accessed through the walleye interface.
The Role of IL-12 in the Induction of Intravenous Tolerance in Experimental Autoimmune Encephalomyelitis1

Intravenous administration of autoantigen is an effective method to induce Ag-specific tolerance against experimental autoimmune encephalomyelitis (EAE). IL-12 is a potent Th1 stimulator and an essential cytokine in the induction of EAE. The role of IL-12 in the induction of i.v. tolerance is not clear. In this study, we induced tolerance by i.v. administering myelin basic protein (MBP) peptide Ac1–11 (MBP1–11) in EAE. We observed significant suppression of IL-12 production by the lymph node cells of MBP1–11-injected mice. To see whether the low level of IL-12 is the cause or effect of tolerance, we administered IL-12 to the EAE mice at the time of i.v. MBP1–11 injection. Exogenous IL-12 abrogated the suppression of clinical and pathological EAE by i.v. tolerance. IL-12 blocked the suppressive effect of i.v. tolerance on the proliferative response to MBP1–11 and MBP1–11-induced production of IL-12 and IFN-γ. Furthermore, IL-12 completely blocked the i.v. tolerance-induced type 1 T regulatory cell response. These data suggest that i.v. administration of autoantigen results in the suppression of endogenous IL-12 and the consequent switching of the immune response from an immunogenic to a tolerogenic form.
Applications of Balanced-separator Approximations to Ordering Problems

We give the rst polynomial-time approximation algorithms for three problems in combina-torial optimization using approximation algorithms for nding balanced separators. The rst problem is register suuciency where, given a computation dag, we are required to nd the minimum number of registers needed to compute it. The second problem is single-processor scheduling to minimize weighted sum of completion times, subject to precedence constraints. The third problem, interval graph completion, is nding a minimum-size interval graph containing the input graph as a subgraph. All of the above problems are NP-complete; our algorithms output solutions that are within a polylogarithmic factor of optimal. We deene a notion of DAG separators and provide approximation algorithms for nding such separators by adapting the techniques due to Leighton and Rao for nding balanced separators 13]. We use such separators in approximately solving the rst two problems.
Optimizing Performance Measures for Feature Selection

Feature selection with specific multivariate performance measures is the key to the success of many applications, such as information retrieval and bioinformatics. The existing feature selection methods are usually designed for classification error. In this paper, we present a unified feature selection framework for general loss functions. In particular, we study the novel feature selection paradigm by optimizing multivariate performance measures. The resultant formulation is a challenging problem for high-dimensional data. Hence, a two-layer cutting plane algorithm is proposed to solve this problem, and the convergence is presented. Extensive experiments on large-scale and high-dimensional real world datasets show that the proposed method outperforms $l_1$-SVM and SVM-RFE when choosing a small subset of features, and achieves significantly improved performances over SVM$^{perf}$ in terms of $F_1$-score.
Internal crowdsourcing for innovation development

Innovation processes are becoming progressively more open, and companies have to explore several new paths when selecting innovation strategy. Crowdsourcing is one new type of open innovation companies are increasingly seeing the potential of. An even newer concept is that companies are beginning to utilising its existing network using internal crowdsourcing. The purpose of this thesis is to provide an overview of the concepts in relation to innovation development, and aspects to contemplate when considering different crowdsourcing alternatives. The main research question is: How does internal crowdsourcing differ from external crowdsourcing in relation to innovation development? To answer this question, the main benefits and drawbacks are identified, and recommendations are made. The method used is a literature study and an empirical study, which is analysed. These are compared to each other and analysed in order to outline the differences. The empirical study is comprised of interviews with employees of multi-national companies, and with crowdsourcing companies. As crowdsourcing can use either an internal crowd or external crowd, and crowdsourcing in relation to innovation development can be carried out either through crowdcasting or through idea jams; four Crowdsourcing Models in relation to Internal and External interaction (CMIE) are identified. Conclusively, the main differences are identified to be related to innovation strategy and culture, incentives, intangible benefits and IP. The main identified benefits with internal crowdsourcing are that it captures underutilised resources and aggregates innovation insights. It offers a possibility for social collaboration and enables an agile informal innovation department unbound by hierarchy or position. It can enhance the innovation culture and increase the transparency between management and employees. The main identified drawbacks with internal crowdsourcing include less wildcards, risk of resistance and not generating external PR or customer intimacy.