Miracle-dz/UniFAR-FTUs huggingface dataset:
SEASONAL VARIABILITY OF AEROSOL COMPOSITION IN SWITZERLAND: A MODELLING STUDY

In this study, we applied the MM5/CAMx model system over Switzerland for winter and summer periods in 2006. The focus is on the formation and transport of aerosols and the contribution of various sources to the aerosol formation both in winter and summer seasons. Our model system uses three nested domains with 27 km (Europe), 9 km (central Europe) and 3 km (Switzerland) resolutions. The concentrations of aerosol components are calculated for particle sizes smaller than 2.5 μm. The model’s capability to reproduce the aerosol concentrations is investigated by comparing the model results with the measurements performed during the same periods. In general, the modelled concentrations of inorganic aerosols agree quite well with the AMS measurements, whereas organic aerosols are underestimated. The chemical composition of aerosols in summer differs from that in winter. Both measurements and model predictions indicate that organic aerosols and particulate nitrate are the major components of the winter aerosol composition in Switzerland. In summer, organic aerosols dominate the aerosol composition and they are mostly secondary organic aerosols formed from the biogenic precursors. Recent measurements suggest that wood-burning emissions might contribute significantly to the aerosol concentrations, especially in winter. The lack of wood burning emissions in emission inventory could cause partly the underestimation of organic aerosols. The secondary organic aerosol (SOA) formation will be soon improved by using a new model version where oligomerization and SOA formation from isoprene and sesquiterpenes are implemented.
Modeling Service Oriented Architectures of Mobile Applications by Extending SoaML with Ambients

Mobile applications need to dynamically adapt to requirements of new environments (or locations) as users and their devices continuously move. Service Oriented Architecture (SOA) is a recent approach for designing and developing open and distributed systems. However, SOA has to be extended in order to fully accommodate the requirements of mobile services. This paper presents an approach called AmbientSoaML, which introduces ambients in Service oriented architecture Modeling Language (SoaML) [8] proposed by the OMG in order to allow its models to include mobility primitives. Ambients are considered to be the service providers and the service consumers for providing/consuming mobility services. They also represent the boundaries that services have to cross when moving from one location to another. This paper demonstrates the use of SoaML for modeling SOA of a mobile application in order to motivate the problem our research purports to address.
A MARKOV MODEL FOR WEB REQUEST PREDICTION

Increasing web content and Internet traffic is making web prediction models popular. A web prediction model helps to predict user requests ahead of time, making web servers more responsive. It caches these pages at the server side or pre-sends the response to the client to reduce web latency. Several prediction techniques have been tried in the past; Markov based prediction models being the most popular ones. Among these, the All-K -order Markov model has been found to be most effective. In this project, a Markov tree is designed, which is a fourth order model but behaves like an All-K-order Markov model because of its ability to recognize different order models according to the height of the tree. It has dual characteristics of good applicability and predictive accuracy. A Markov tree gives a complete description on the frequency with which a particular state occurs, and the number of times a path to a particular state is used, to access its child nodes. Further, the model can be pruned to eliminate states that have very little contribution towards the accuracy of the model. In this work, an evolutionary model is designed that makes use of a fitness function. The fitness function is a weighted sum of precision and the extent of coverage that the model offers. This helps to generate a model with reduced complexity. Results indicate that this model performs consistently with good predictive accuracy among different log files. The evolutionary approach helps to train the model to make predictions commensurate to current web browsing patterns.
Item response modeling of DSM-IV mania symptoms in two representative US epidemiological samples

Background There is considerable debate surrounding the effective measurement of DSM-IV symptoms used to assess manic disorders in epidemiological samples. Method Using two nationally representative datasets, the National Epidemiological Survey of Alcohol and Related Conditions (NESARC, n=43 093 at wave 1, n=34 653 at 3-year follow-up) and the National Comorbidity Survey – Replication (NCS-R, n=9282), we examined the psychometric properties of symptoms used to assess DSM-IV mania. The predictive utility of the mania factor score was tested using the 3-year follow-up data in NESARC. Results Criterion B symptoms were unidimensional (single factor) in both samples. The symptoms assessing flight of ideas, distractibility and increased goal-directed activities had high factor loadings (0.70–0.93) with moderate rates of endorsement, thus providing good discrimination between individuals with and without mania. The symptom assessing grandiosity performed less well in both samples. The quantitative mania factor score was a good predictor of more severe disorders at the 3-year follow-up in the NESARC sample, even after controlling for a past history of DSM-IV diagnosis of manic disorder. Conclusions These analyses suggest that questions based on some DSM symptoms effectively discriminate between individuals at high and low liability to mania, but others do not. A quantitative mania factor score may aid in predicting recurrence for patients with a history of mania. Methods for assessing mania using structured interviews in the absence of clinical assessment require further refinement.
A study about the personalized recommendation system of TV program based on user behaviors

Human behavior can be a direct reflection of their interest and purposes; therefore, we can take advantage of user behavior to predict their interest in the recommendation system. This paper analyzed the relationship between user behavior and interest in the recommender system of personalized video program, and summarized three potentially useful observations: selection, duration, repetition. Implicit feedback, inferred on the three behaviors, is introduced into the system. Then the paper presented a method of measuring user interest from implicit feedback, based on which constructed user preferences model by combining all implicit feedback.
Prefetching in Visual Simulation

This project examines the problem of visual simulation of virtual environment that is too large to fit into the main memory of a PC. We broadly classify the problem into three subproblems: render, query and prefetch, which correspond, respectively, to processing data to be displayed, identifying and organizing data to be retrieved, and retrieving (identified) data into main memory in anticipation of the need to render them in the near future. Unlike the first two subproblems, there is little existing work that reports the prefetch subproblem in detail. Some existing applications adopt advanced data indexing and layout in an application specific way but leave the operating system to do the actual fetching (paging) of data during runtime (see, for example, [LiPa02]). There are also approaches that use speculative prefetching based on the viewer’s current position and velocity to prefetch data needed for future frames (see, for example, [CGLL98]). These are sometimes coupled with sophisticated occlusion culling techniques that reduce the amount of geometry that needs to be fetched from disk (see, for example, [VaMa02]). On the whole, the focus of current approaches is in solving the render and query subproblems but it is not clear how these methods can provide specific quality-of-service guarantee with respect to page fault rates. The general lack of quantitative work on the prefetch subproblem underlies our motivation to study it in detail.
urban Scalable Geospatial Proposal for Calculating a Social Capital Score for the Labor Market: İşgücü Piyasası İçin Bir Sosyal Sermaye Puanı Hesaplama Önerisi

Isgucu piyasasi acisindan sosyal sermaye, isgucu ile isveren arasindaki guvene dayali iliskilerden dogan bir degerdir. Sosyal sermaye birikimine sahip olan universite mezunlarinin, is arama surelerinin kisalmasi ve niteliklerine uygun islerle eslesmesi ve daha gorunur hale gelmesi beklenmektedir. Bu baglamda, mezunlarin sosyal sermaye birikimini ogrencilikleri suresince edinmeleri gerekliligi on plana cikmakta ve boylece universitelere, bu birikimi kazandiracak kanallarin olusturulmasi sorumlulugu yuklenmektedir. Isgucu piyasasinin talep tarafinda, isverenler istihdam karari alirken; adayin akademik ortalamasindan ote, bireyin sosyal sermaye birikimi ve bu yolla alanda edindigi deneyim ve tecrubeleri ve hatta sosyal yasamindaki sosyal sermaye ve etkinlikleri fazlasiyla onemsemektedir. Ancak adayin alana ozgu sosyal sermayesini gosteren somut bir gostergenin olmamasi, isverenin secim yapmasini guclestirmekte, cogu zaman akraba, yakin cevre gibi sinirlayici nitelikte sosyal sermaye kanallarini isletmesine ve boylece isgucu piyasasinin etkinliginin bozulmasina neden olmaktadir. Boyle bir gostergenin elde edilmesi isverenin daha etkin karar verebilmesini saglayacaktir.Calismadamezunlarin alanlarina dair sosyal sermaye birikimini belirlemeye yonelik bir puanin hesaplanmasi hedeflenmektedir. Bununicin Analitik Hiyerarsi Prosesi (AHP) yontemi kullanilmistir. AHP, farkli onceliklere sahip birden fazla kriterin sistematik olarak karsilastirilip degerlendirilmesini saglamaktadir. Genellikle AHP secenekler icinden en iyisinin belirlenmesinde kullanilan bir teknik olmasina ragmen bu calismada yaygin kullanimindan farkli olarak mezunlarin sosyal sermaye birikimlerini degerlendirmekte kullanilabilecek birden cok kriterin onem derecelerini goz onunde bulundurarak birlestirilmesi ve tek bir puana donusturulmesinde kullanilmistir.
Non-Perturbative Approach to the Effective Potential of the λϕ4 Theory at Finite Temperature

We construct a non-perturbative method to calculate the effective potential of the >. cp4 theory at finite temperature. We express the derivative of the effective potential with respect to the mass squared in terms of the full propagator. We reduce this equation to a partial differential equation for the effective potential using an approximation. We numerically solve this equation and obtain the effective potential non-perturbatively. We find that the phase transition is second order, as it should be. We determine several critical exponents.
Computational Phenomena Occurring Solving the Binary Quadratic Assignment Problem

Computational phenomena occurring whilst solving the binary quadratic assignment problem using simulated annealing is investigated. The presence of phenomena such as self organisation and emergent computation are searched for in both the optimisation process and the solutions. Implicit emergent computation is shown to be facilitated by a simple perturbation operator. The potential for the application of the research is discussed
Social choice theory , belief merging and elections

Intelligent agents have to be able to merge inputs received f rom different sources in a coherent and rational way. Several propo sals have been made for the merging of structures in which it is possible to encod e thepreferencesof sources [5, 4, 12, 16, 17, 1]. Information merging has much in common with the goals ofsocial choice theory : to define operations reflecting the preferences of a society from the individual preferences of the members of th e society. Given this connection it seems reasonable to require that any framewor k for the merging of information provide satisfactory ways of dealing with th e problems raised in social choice theory. We investigate the link between the me rging of epistemic statesand two important results in social choice theory. We show th at Arrow’s well-known impossibility theorem [2] can be circumvented w hen the preferences of sources are represented in terms of epistemic states. Thi s is achieved by providing a consistent set of properties for merging from which Arr ow-like properties can be derived. We extend this to a consistent framework whic h in ludes properties corresponding to the notion of being strategy-proof . The existence of such an extended framework can be seen as a circumvention of the impo ssibility result of Gibbard and Satterthwaite [8, 21, 22] and related results [6 , 3].
Planning One-Eye-in-Arm Robot for Object Localization

Locating known objects is an important task for robots. When a robot has a single camera located in its arm, the robot can use it to get pictures from multiple points of view. These pictures can be used for locating in 3D a desired object, when the object is found on the floor within a bounded distance from the robot. Here we propose a technique for planning a sequence of arm positions to be used for capturing the camera snapshots that can locate the object with given precision. Heuristics are used to reduce the number of steps (i.e., camera snapshot taking operations) performed by the robot following the obtained contingency plan.
Secure sparse network coding for reliable routing in large scale DTMN

Security issue occupies an important part in all communication system and especially for new generation networks. Among these networks, we find Delay Tolerant Mobile Networks (DTMNs) which are a class of useful but challenging networks. Combining Network Coding (NC) and clustering for routing in such networks gives more efficiency and copes with routing reliability problem among large scale networks. Our work's concern is to build a secure network coding scheme in the presence of eavesdroppers in large-scale DTMNs. Therefore, we used a cluster based routing protocol dedicated to DTMN specificities. In addition, we used Sparse Random Linear Network Coding (SRLNC) to feat low computational capabilities requirement in such networks. Furthermore, we addressed the packets retransmission decision problem for SRLNC with a fair trade-off throughput/overhead. The results are very encouraging and the proposed routing scheme has the advantage to be reliable as well as secure for large scale DTMN.
Spontaneous Unitary Synaptic Activity in CA1 Pyramidal Neurons during Early Postnatal Development: Constant Contribution of AMPA and NMDA Receptors

Maturation of the glutamatergic synapse is thought to require the incorporation of AMPA receptors at pure NMDA synapses, also called “silent” synapses. However, the relative number of silent synapses at different developmental stages, and even the concept that silent synapses lack AMPA receptors, is actively debated. In the present work, spontaneous synaptic events were used to investigate the relative contribution of synaptic AMPA and NMDA receptor-mediated transmission in CA1 pyramidal cells during the early postnatal development. Spontaneous postsynaptic currents, mediated by AMPA and NMDA receptors, were recorded from visualized CA1 pyramidal neurons over the first postnatal week. AMPA/NMDA ratio for frequency was close to one, and, importantly, it was constant over the first postnatal week. These findings suggest that the vast majority of nascent glutamatergic synapses express both functional AMPA and NMDA receptors in the neonatal hippocampus.
The Effects of Enterprise Risk Management on Firm Performance

We study the effect of adoption of enterprise risk management (ERM) principles on firms' long-term performance by examining how financial, asset and market characteristics change around the time of ERM adoption. Using a sample of 106 firms that announce the hiring of a Chief Risk Officer (an event frequently accompanied by adoption of Enterprise Risk Management) we find that firms adopting ERM experience a reduction in stock price volatility. We also find that firms hiring Chief Risk Officers (CRO) when compared to similar, non-CRO appointing firms in their industry group, exhibit increased asset opacity, a decreased market to book ratio and decreased earnings volatility. In addition, we find a negative relationship between the change in firms' market to book ratio and earnings volatility. We also find banks increase leverage after ERM adoption. Overall, our results fail to find support for the proposition that ERM is value creating, although further study is called for.
Effect of Pulse Shaping On Ber Performance of QAM Modulated OFDM Signal

— Pulse shaping of a signal at base-band forms a more important tool in controlling and analyzing the parameters like ISI, the modulated signal envelope uniformity, the phase continuity as these parameters lead to the efficient spectral confinement of a binary signal which is a future and nowadays a major important aspect in the design of a wireless cellular communication system. In this paper, different time-limited waveform are discussed which are basically available as windows functions and comparing the performance of Rectangular, Raised cosine and BTRC and prove that the BTRC pulse is supposed to be a batter pulse shaping for OFDM in terms of obtaining better BER performance and proposed two pulse shapes which are giving better E[ ρ i2] in respective cases which in turn provides better BER as compared to BTRC which was considered as one of the best pulse shape.
A novel ρ-q/Distortion model for H.264 rate control algorithm

Rate control aims to maximize reconstructed video quality while adapting coding bit rate to the fluctuating network bandwidth. This paper proposes an easy rate control algorithm for H.264 video coding based on a novel ρ-q/Distortion model, whose data line shows quite a pleasing goodness-of-fit. Experimental results have demonstrated that, compared with rate control mechanism suggested in H.264 reference software, the proposed model provides a better reconstructed visual quality with a coding gain up to 0.37dB as well as much smaller bit rate control error with a maximum reduced bit rate up to 2.04kbps.
The long-period Galactic Cepheid RS Puppis I. A geometric distance from its light echoes

Context: The bright southern Cepheid RS Pup is surrounded by a circumstellar nebula reflecting the light from the central star. The propagation of the light variations from the Cepheid inside the dusty nebula creates spectacular light echoes that can be observed up to large distances from the star itself. This phenomenon is currently unique in this class of stars. Aims: For this relatively distant star, the trigonometric parallax available from Hipparcos has a low accuracy. A careful observation of the light echoes has the potential to provide a very accurate, geometric distance to RS Pup. Methods: We obtained a series of CCD images of RS Pup with the NTT/EMMI instrument, covering the variation period of the star (P=41.4d). This allowed us to track the progression of the light wavefronts over the nebular features surrounding the star. We measured precisely the phase lag of the photometric variation in several regions of the circumstellar nebula. Results: From our phase lag measurements, we derived a geometric distance of 1992 +/- 28 pc to RS Pup. This distance is affected by a total uncertainty of 1.4%, and corresponds to a parallax of pi = 0.502 +/- 0.007 mas and a distance modulus of mu = 11.50 +/- 0.03. Conclusions: The geometric distance we derived is by far the most accurate to a Cepheid, and among the most accurate to any star. RS Pup appears both as somewhat neglected and particularly promising to investigate the mass-loss history of Cepheids. Thanks to its highly accurate distance, it is also bound to become an important luminosity fiducial for the long period part of the period-luminosity diagram.
Efficiency ranking in fuzzy two-stage DEA: A mathematical programming approach

Data envelopment analysis (DEA) is a useful tool for efficiency measurement of firms and organizations. Two-stage DEA models show the performance of individual processes, thus is more informative than the conventional one-stage models for making decisions. When input and output data are fuzzy numbers, the derived efficiencies become fuzzy as well. This paper proposes a method to rank the fuzzy efficiencies when the exact membership functions of the overall efficiencies derived from fuzzy two-stage model are unknown. By incorporating the fuzzy two-stage model with the fuzzy number ranking method, a pair of nonlinear program is formulated to rank the fuzzy overall efficiency scores of DMUs. Solving the pair of nonlinear programs determines the efficiency rankings.
Learning to Find Topic Experts in Twitter via Different Relations

Expert finding has become a hot topic along with the flourishing of social networks, such as micro-blogging services like Twitter. Finding experts in Twitter is an important problem because tweets from experts are valuable sources that carry rich information (e.g., trends) in various domains. However, previous methods cannot be directly applied to Twitter expert finding problem. Recently, several attempts use the relations among users and Twitter Lists for expert finding. Nevertheless, these approaches only partially utilize such relations. To this end, we develop a probabilistic method to jointly exploit three types of relations (i.e., follower relation, user-list relation, and list-list relation) for finding experts. Specifically, we propose a Semi-Supervised Graph-based Ranking approach (SSGR) to offline calculate the global authority of users. In SSGR, we employ a normalized Laplacian regularization term to jointly explore the three relations, which is subject to the supervised information derived from Twitter crowds. We then online compute the local relevance between users and the given query. By leveraging the global authority and local relevance of users, we rank all of users and find top-N users with highest ranking scores. Experiments on real-world data demonstrate the effectiveness of our proposed approach for topic-specific expert finding in Twitter.
On the Need for a Theory of Integration of Knowledge Sources for Spoken Language Understanding

In the Spoken Language Understanding(SLU) community we are seeing a renewedinterest both in the theoretical issues and prac-tical problems of melding our understanding ofhuman language use with the traditional signalprocessing emphasis of Speech Recognition(SR). Although the Hearsay II Speech Under-standing System demonstrated an early aware-ness of the potential — and pitfalls — ofintegrating multiple knowledge sources forSLU, SR systems demonstrated since thenhave achieved better short-term results bystressing search-oriented and stochastic meth-ods (Waibel & Lee, 1990). As SR techniquesmature, however, attention is once again drawnto the potential performance improvements ofincorporating the growing understanding ofhuman language use in our systems.Existing SLU systems are largely designedaround the Speech Recognizer. This paperreviews existing integration architectures andnotes that we lack adequate computationalmodels for either extending the existing sys-tems or for judging their correctness. We thenturn to an overview of research that may illu-minate the interrelationships of knowledgesources in spoken language understanding.Finally, we suggest that many questionsremain to be answered before we will have aprincipled basis for constructing an integratedSLU system and report on our initial steps toanswer these questions.