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Market Timing, Forecast Ability and Information Flow in Petroleum Futures MarketsBuchanan, William K. 12 1900 (has links)
Three petroleum futures contracts are examined over a ten-year period from 1986 to 1996. Intertemporal changes in futures prices and the net open interest positions of three trader types are compared to determine what, if any, market timing ability the traders have. Seasonal variation is considered and a simple trading rule is adopted to determine the dollar-return potential for market participation and
shed light on issues of market efficiency.
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When to correct errors when teaching a new task to children with autismCochrane, Angela J. 12 1900 (has links)
The purpose of this experiment was to investigate Tosti's proposal about the timing of feedback. The study examined whether it is better to correct immediately after the error occurs or whether it is better to wait until immediately before the next opportunity to respond. In addition, it aimed to determine whether corrections delivered at different times produced different learner affects. Four children with autism were taught to label two sets of pictures under the two different conditions. Results showed that the timing of the feedback yields similar results in regards to number of correct responses and total trial count. However, in regards to time spent in teaching and learner affect, correcting errors before the next opportunity to respond showed to be the more efficient procedure and produced more favorable affect.
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Magic Formula och Graham Screener på Small, Mid och Large Cap : Hur investeringsstrategier presterar på Stockholmbörsens undergrupperingarBakircioglu Eriksson, Benjamin, Svensson, Karl January 2020 (has links)
Most of the Swedish people are saving their money in savings accounts with limited yield potential. This study examines how the two investment strategies Magic Formula and Graham Screener performs on the Swedish stock market subgroups Large, Mid and Small Cap. With a focus to determine which strategy who suits the private investor best and yield the highest return, with the risk taken into account. The study also examines if it is possible to time the market during a long period of time to yield the highest return possible. After calculating the return on each month and market, the result from this study shows us that Magic Formula is the preferred strategy to use. It was able to yield a higher return over time compared to Graham Screener on each market and with less risk involved. However, Graham Screener should nonetheless be regarded as a qualitative investment decision for the investor. The result also showed us that it is difficult to time the market over time which implicates that return based on a specific month occurs random and should be neglected by the private investor.
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Time Synchronization of TDOA Sensors Using a Local Reference SignalHult, Alfred January 2020 (has links)
Synchronization of distributed time difference of arrival (TDOA) sensor networks can be performed using reference signals from GPS satellites. This method provides high accuracy, but is vulnerable to jamming, and is not reliable enough to be used in military applications. A solution that does not depend on any signals transmitted from external actors is preferred. One way to achieve this is to use reference signals transmitted from a UAV. A UAV is suitable since only local synchronization for a geographically restricted area is necessary. The local synchronization is achieved by estimating the time-delay between the transmission and reception of a reference signal. The estimated time-delay can be used to detect drifts in the clocks of the TDOA sensors. This thesis analyzes com- mon reference signals, to evaluate which provide high accuracy for time-delay estimation, and what properties of the signals influence the estimation accuracy the most. The simulations show that the time-delay estimation performance can reach the same accuracy as synchronization against GPS for different types of signals. An increased bandwidth is more important than an increased signal length or signal-to-noise ratio to improve the estimation accuracy.
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Elevers uppfattning om laborationer i naturkunskapsundervisningen. / Students’ View on Laboratory Work in Science Studies.Kryh Öberg, Hanna January 2021 (has links)
Laborationer är centrala i den naturvetenskapliga undervisningen, inte minst i naturkunskap i gymnasieskolan. Skolforskningsinstitutet betonar i en forskningsöversikt vikten av att lära sig utföra naturvetenskap. Det är dock oklart huruvida lärare och elever har samma uppfattning beträffande laborationens betydelse. Syftet med denna studie är därför att ta reda på hur gymnasieelever uppfattar att laborationer bör vara designade, avseende graden av öppenhet samt timing, för att optimera lärprocessen. Studien utgår från en fenomenografisk ansats i kombination med deskriptiv statistik för att söka kartlägga elevernas olika uppfattningar i frågan. Empirin består dels av enkätsvar från två parallellklasser i naturkunskap 1b som fått utföra en laboration om DNA-extraktion vid olika tidpunkt inom ämnesområdet, dels av intervjuer med elever som läser fördjupningskursen naturkunskap 2 för att möjliggöra en djupare analys. Resultaten visar att en majoritet av eleverna anser att laborationer är till hjälp för deras förståelse, dock skiljer sig uppfattningen om hur en laboration bäst ska utformas samt när i ett arbetsområde den bör vara placerad. En del elever efterfrågar en mer styrd struktur, medan andra elever uppskattar den frihet som ges vid en öppen laboration och beskriver att de då lär sig mer. Likaså vad gäller timingen föredrar vissa elever att först lära sig det teoretiska och således ha laborationen förhållandevis sent, medan andra elever istället vill ha laborationen tidigt i ett mer intresseväckande syfte. Den här studien kan förutom att vara till hjälp för yrkesverksamma lärare vid deras planering av laborationer, även leda till vidare undersökningar av elevers självkänsla och bemästrande av kritiska kunskapsförmågor i samband med laborationer.
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Blade tip timing to determine turbine blade fatigue in high backpressure conditionsVisagie, Willem Johannes January 2020 (has links)
This dissertation presents an approach to use blade tip timing measurements with finite element analysis to predict the fatigue life of a low pressure steam turbine last stage blade under high backpressure and low flow conditions. Material fatigue properties were determined through the extended universal material law for FV566 material, along with different temper scenarios. A finite element model of a blade with damping pins was developed, using the principle of cyclic symmetry for a perfectly tuned model. Pre-stress modal analysis was conducted, incorporating damping via friction and plasticity for initial 20% overspeed test. The finite element model was verified by two experimental tests: the first being a blade impact test and the second a telemetry strain gauge test in a balance pit. Fatigue life analysis was conducted under the assumption that non-synchronous vibration is experienced by the blade and that only one mode is dominant in the vibration. The results from the fatigue analysis corresponded to the location of the cracks experienced on the blades. The results show twelve orders of magnitude lower life at low load, high backpressure conditions, compared to high load high pressure conditions. The research was further extended to check the same vibratory response on the first three modes, up to their tenth nodal diameters. This was done to analyse fatigue life in a case that a different mode was excited. / Dissertation (MEng)--University of Pretoria, 2020. / Eskom Rotek Industries / Mechanical and Aeronautical Engineering / MEng / Unrestricted
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THE ROLE OF CUSTOMER NON-COMPLIANCE AND COMMUNICATION TIMING IN THE MANAGEMENT OF TARGETED PROMOTIONAL PROGRAMSSeong kyoung Shin (12464442) 27 April 2022 (has links)
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<p>The objective of the two essays is to understand how to enhance the targeted promotional programs. The first essay focuses on the importance of considering non-compliance to evaluate the target marketing and draw meaningful business implications. The second essay investigates the crucial impact of communication timing to improve the efficiency of promotional programs.</p>
<p>The first essay, “Addressing Customer Non-compliance in Causal Studies”: Although numerous studies have examined how to reveal the causal relationship between targeting and customer’s conversion, focusing on the selection bias induced by targeting, the non-compliance issue remains sparse in the marketing literature. To fill this gap, I investigate the importance of addressing non-compliance in target program evaluation. Specifically, I propose a method to infer the causality, given the high proportion of non-compliers. I use propensity score matching and instrument variable method and show about 59% of the target message effects are nullified by non-compliance. Nevertheless, our findings suggest that firms carefully investigate whether compliance induces enough conversion to offset the marketing expense when deploying a multi-channel strategy because the level of customer awareness moderates the effect of the marketing message.</p>
<p>The second essay “When Do You Talk to Your Customers? An Empirical Study of the Impacts of Communication Timing in the Prescription Delivery Service Market”: I investigate how to improve the marketing communication of the prescription delivery service that has been rapidly emerging, especially focusing on communication timing. I identify the causal relationship between the communication timing and targeting effect while controlling the potential endogeneity with the instrument method. Interestingly, my findings show contacting patients at the early prescription cycle is far more effective than at the end, despite no need for the refill, but well-awareness of the service can moderate the impact of communication timing. I also show that timing is vital for targeting effectiveness and a firm’s profitability by optimizing call allocation. Specifically, optimal timing targeting generates at least 4.3 times more conversion, inducing 6.6 times more net profits. </p>
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Data Link Layer Security for Spacecraft Communication Implementation on FPGASundberg, Sarah January 2020 (has links)
With increasing awareness of potential security threats there is a growing interest in communication security for spacecraft control and data. Traditionally commercial and scientific missions have relied on their uniqueness to prevent security breaches. During time the market has changed with open systems for mission control and data distribution, increased connectivity and the use of existing and shared infrastructure. Therefore security layers are being introduced to protect spacecraft communication. In order to mitigate the perceived threats, the Consultative Committee for Space Data Systems (CCSDS) has proposed the addition of communication security in the various layers of the communication model. This thesis describes and discuss their proposal and look into how this application should be implemented into the data link layer of the communication protocol to protect from timing attacks. An implementation of AES-CTR+GMAC is constructed in software to compare different key lengths and another implementation is constructed in synthesized VHDL for use on hardware to investigate the impact on area consumption on the FPGA as well as if it is possible to secure it from cache-timing attacks.
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Self-organized Criticality in Neural Networks by Inhibitory and Excitatory Synaptic PlasticityEhsani, Masud 25 January 2022 (has links)
Neural networks show intrinsic ongoing activity even in the absence of information processing and task-driven activities. This spontaneous activity has been reported to have specific characteristics ranging from scale-free avalanches in microcircuits to the power-law decay of the power spectrum of oscillations in coarse-grained recordings of large populations of neurons. The emergence of scale-free activity and power-law distributions of observables has encouraged researchers to postulate that the neural system is operating near a continuous phase transition. At such a phase transition, changes in control parameters or the strength of the external input lead to a change in the macroscopic behavior of the system. On the other hand, at a critical point due to critical slowing down, the phenomenological mesoscopic modeling of the system becomes realizable. Two distinct types of phase transitions have been suggested as the operating point of the neural system, namely active-inactive and synchronous-asynchronous phase transitions.
In contrast to normal phase transitions in which a fine-tuning of the control parameter(s) is required to bring the system to the critical point, neural systems should be supplemented with self-tuning mechanisms that adaptively adjust the system near to the critical point (or critical region) in the phase space.
In this work, we introduce a self-organized critical model of the neural network. We consider dynamics of excitatory and inhibitory (EI) sparsely connected populations of spiking leaky integrate neurons with conductance-based synapses. Ignoring inhomogeneities and internal fluctuations, we first analyze the mean-field model. We choose the strength of the external excitatory input and the average strength of excitatory to excitatory synapses as control parameters of the model and analyze the bifurcation diagram of the mean-field equations. We focus on bifurcations at the low firing rate regime in which the quiescent state loses stability due to Saddle-node or Hopf bifurcations. In particular, at the Bogdanov-Takens (BT) bifurcation point which is the intersection of the Hopf bifurcation and Saddle-node bifurcation lines of the 2D dynamical system, the network shows avalanche dynamics with power-law avalanche size and duration distributions. This matches the characteristics of low firing spontaneous activity in the cortex. By linearizing gain functions and excitatory and inhibitory nullclines, we can approximate the location of the BT bifurcation point. This point in the control parameter phase space corresponds to the internal balance of excitation and inhibition and a slight excess of external excitatory input to the excitatory population. Due to the tight balance of average excitation and inhibition currents, the firing of the individual cells is fluctuation-driven. Around the BT point, the spiking of neurons is a Poisson process and the population average membrane potential of neurons is approximately at the middle of the operating interval $[V_{Rest}, V_{th}]$. Moreover, the EI network is close to both oscillatory and active-inactive phase transition regimes.
Next, we consider self-tuning of the system at this critical point. The self-organizing parameter in our network is the balance of opposing forces of inhibitory and excitatory populations' activities and the self-organizing mechanisms are long-term synaptic plasticity and short-term depression of the synapses. The former tunes the overall strength of excitatory and inhibitory pathways to be close to a balanced regime of these currents and the latter which is based on the finite amount of resources in brain areas, act as an adaptive mechanism that tunes micro populations of neurons subjected to fluctuating external inputs to attain the balance in a wider range of external input strengths.
Using the Poisson firing assumption, we propose a microscopic Markovian model which captures the internal fluctuations in the network due to the finite size and matches the macroscopic mean-field equation by coarse-graining. Near the critical point, a phenomenological mesoscopic model for excitatory and inhibitory fields of activity is possible due to the time scale separation of slowly changing variables and fast degrees of freedom. We will show that the mesoscopic model corresponding to the neural field model near the local Bogdanov-Takens bifurcation point matches Langevin's description of the directed percolation process. Tuning the system at the critical point can be achieved by coupling fast population dynamics with slow adaptive gain and synaptic weight dynamics, which make the system wander around the phase transition point. Therefore, by introducing short-term and long-term synaptic plasticity, we have proposed a self-organized critical stochastic neural field model.:1. Introduction
1.1. Scale-free Spontaneous Activity
1.1.1. Nested Oscillations in the Macro-scale Collective Activity
1.1.2. Up and Down States Transitions
1.1.3. Avalanches in Local Neuronal Populations
1.2. Criticality and Self-organized Criticality in Systems out of Equilibrium
1.2.1. Sandpile Models
1.2.2. Directed Percolation
1.3. Critical Neural Models
1.3.1. Self-Organizing Neural Automata
1.3.2. Criticality in the Mesoscopic Models of Cortical Activity
1.4. Balance of Inhibition and Excitation
1.5. Functional Benefits of Being in the Critical State
1.6. Arguments Against the Critical State of the Brain
1.7. Organization of the Current Work
2. Single Neuron Model
2.1. Impulse Response of the Neuron
2.2. Response of the Neuron to the Constant Input
2.3. Response of the Neuron to the Poisson Input
2.3.1. Potential Distribution of a Neuron Receiving Poisson Input
2.3.2. Firing Rate and Interspike intervals’ CV Near the Threshold
2.3.3. Linear Poisson Neuron Approximation
3. Interconnected Homogeneous Population of Excitatory and Inhibitory Neurons
3.1. Linearized Nullclines and Different Dynamic Regimes
3.2. Logistic Function Approximation of Gain Functions
3.3. Dynamics Near the BT Bifurcation Point
3.4. Avalanches in the Region Close to the BT Point
3.5. Stability Analysis of the Fixed Points in the Linear Regime
3.6. Characteristics of Avalanches
4. Long Term and Short Term Synaptic Plasticity rules Tune the EI Population Close to the BT Bifurcation Point
4.1. Long Term Synaptic Plasticity by STDP Tunes Synaptic Weights Close to the Balanced State
4.2. Short-term plasticity and Up-Down states transition
5. Interconnected network of EI populations: Wilson-Cowan Neural Field Model
6. Stochastic Neural Field
6.1. Finite size fluctuations in a single EI population
6.2. Stochastic Neural Field with a Tuning Mechanism to the
Critical State
7. Conclusion
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Výpočtový model řetězového pohonu jako modul virtuálního motoru / Chain Drive Computional Model as Virtual Engine ModuleVlastník, Jan January 2010 (has links)
his work deals with the methods of creating computational models for the analysis of the chain drive of camshafts in combustion engines. Methods are compared of the simulation of the drive mechanism; a new method is also presented for the simulation of the tensioning and guide bar by means of a modal reduction of an elastic body in the Multibody system. The work describes individual parts of the chain gear and the mathematical formulation of differential equations of motion. Algorithms are also indicated describing the mutual interaction of bodies in contact. Computations are here described for the determination of individual parameters necessary for setting up a chain drive model. The tensile characteristics of the chain is determined by the FEM programme. The chain model is analyzed in several alternatives of arrangement. FEM calculations are described here of the rigidity of contacts between the chain and the chain wheels and between the chain and the guide bars. The computational model has been created in the MSC ADAMS programme. The computation is carried out for a stabilized speed of the crankshaft of 3,000, 4,500 and 6,000 rpm and for a continuous start from the idle state up to the speed of 6,000 rpm with a constant load of the crankshafts by the torsion moment. Computation is also carried out for loading the crankshafts with a torsion moment deduced from the cam shape. The courses of the quantity obtained are processed by means of FFT; Campbell diagrams have been constructed for their evaluation. The results have been compared with the modal analyses of the individual parts of the chain gear for the determination of their mutual interaction.
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