A fractionally integrated ECOGARCH process

In this article, novel mixture of conditional volatility models of Generalized Autoregressive Conditional Heteroscedasticity (GARCH); Exponential GARCH (EGARCH); Glosten, Jagannathan, and Runkle GARCH (GJR-GARCH); and dependent variable-GARCH (TGARCH) were thoroughly expounded in a Bayesian paradigm. Expectation-Maximization (EM) algorithm was employed as the parameter estimation technique to work-out posterior distributions of the involved hyper-parameters after setting-up their corresponding prior distributions. Mode was considered as the stable location parameter instead of the mean, because it could robustly adapt to symmetric, skewedness, heteroscedasticity and multimodality effects simulteanously needed to redefine switching conditional variance processes conceived as mixture components based on shifting number of modes in the marginal density of Skewed Generalized Error Distribution (SGED) set as the prior random noise. In application to ten (10) most used cryptocurrency coins and tokens via their daily open, high, low, close and volume converted and transacted in USD from the same date of inception. Binance Coin (BNB) via its daily lower units transacted in USD (that is, low-BNB), yielded the most reduced Deviance Information Criteria (DIC) of 3651.1935. The low-BNB process yielded a two-regime process of TGARCH, that is, Mixture dependent variable-GARCH (TGARCH (2: 2, 2)) with stable probabilities of 33% and 66% respectively. The first regime was attributed with low unconditional volatility of 16.96664, while the second regime was traded with high unconditional volatility of 585.6190. In summary, Binance Coin (BNB) was a mixture of tranquil market conditions and stormy market conditions. Implicatively, this implies that the first regime of the low-BNB was characterized with strong fluctuating reaction to past negative daily returns of low-BNB converted to USD, while the second regime was attributed with weak fluctuating reaction. Additionally, the first regime was attributed with low repetitive volatility process, while the second regime was characterized with high persistence fluctuating process. For financial and economic decision-making, crypocurrency users and financial bodies should look-out for financial and economic sabotage agents, like war, exchange rate instability, political crises, inflation, browsing network fluctuation etc. that arose, declined or fluctuated doing the ten (10) years to study of the coins and tokens to ascertain which of this/these agent(s) contributed to the volatility process. Mixture models from a Bayesian perspective were of interest because; some of the classical (traditional) models cannot accommodate and absolve regime-switching traits, and as well contain prior information known about cryptocurrency coins and tokens. In light of model performance, DIC values were compared on the basis of most performed to less perform via lower to higher values of DICs.

A wide body of animal and human research suggests that MDMA/ecstasy use is associated with lasting serotonergic neurotoxicity, particularly in mediotemporal and frontostriatal brain regions (Benningfield, 2013; Green, Mechan, Elliott, O'Shea, & Colado, 2003). Serotonin is important for a wide range of neurocognitive and psychobiological processes, and therefore neurotoxicity in these regions may have significant functional implications for ecstasy users. The objective of this thesis was to examine the neurocognitive and psychobiological effects of ecstasy that may be associated with serotonergic damage to mediotemporal and frontostriatal regions. Specifically, we examined this using an overnight memory consolidation paradigm. Overnight memory consolidation refers to the process of memory enhancement and increased resistance to interference that occurs across an episode of sleep, relative to a similar time-frame of wakefulness (Stickgold & Walker, 2013). The consolidation of declarative material in healthy participants is associated with prefrontal slow wave activity normally observed during deep sleep (Mander et al., 2013). The findings outlined above of serotonergic dysfunction in frontostriatal regions, coupled with evidence that ecstasy users have disrupted sleep architecture (Ogeil, Rajaratnam, & Broadbear, 2012) led us to hypothesise that ecstasy users will show impairments in the overnight consolidation of memory. We examined this hypothesis in two overnight consolidation studies. The first explored the overnight consolidation of emotional material using a visual recognition task delivered in an online environment. We found that compared to drug-naive controls (N=16), ecstasy users (N=15) tested after a period of sleep had stronger memory for negative visual images relative to neutral visual images. We suggest that this is due to a negative attribution bias, whereby material with negative content is preferentially consolidated and better recalled relative to material with neutral or positive content. The second overnight consolidation study utilised a verbal memory task to explore overnight memory consolidation in a laboratory setting. The task assessed whether sleep protects against interference from similar material, a phenomenon that has been confirmed in several studies among drug-naive controls (e.g. Ellenbogen, Hulbert, Jiang, & Stickgold, 2009). The results indicated that ecstasy users (N=12) did not show the same resistance to interference that was conferred to control participants (N=13) by overnight consolidation processes. Furthermore, our objective measurement of sleep architecture indicated that ecstasy users spent less time in deep sleep relative to controls, indicating that less time was spent in sleep stages that are known to be important for overnight memory consolidation. Together, this data suggests that ecstasy users experience dysfunctional sleep leading to impaired overnight memory consolidation. Finally, additional functional implications of disrupted mediotemporal and frontostriatal circuitry were examined using neurocognitive tasks that recruit these regions. Consistent with past research, we found reduced performance in a (same day) declarative long term memory task in ecstasy users. We also found that ecstasy users were selectively impaired on tasks of encoding, proactive interference memory, updating of working memory and complex planning, and therefore propose that executive functioning tasks engaging a higher cognitive load might reveal more subtle neurocognitive impairments experienced by ecstasy users. This thesis highlights the presence of selective neurocognitive executive dysfunction among ecstasy users. Furthermore, this thesis provides a unique contribution to the literature by demonstrating the key role of disrupted overnight consolidation processes in subsequent dysfunctional memory recall.

Global commodity markets, particularly crude oil markets, are inherently characterized by pronounced price volatility driven by geopolitical tensions, macroeconomic shocks, financial speculation, and structural changes in energy demand and supply.Accurately modeling and forecasting such volatility is essential for policymakers, investors, and risk managers seeking to design effective stabilization, hedging, and investment strategies.This study provides a comprehensive empirical investigation of oil price volatility by applying three prominent members of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family-namely the standard GARCH, Threshold GARCH (TGARCH), and Exponential GARCH (EGARCH) models-to monthly West Texas Intermediate (WTI) crude oil prices over the period from January 2008 to June 2024.The selected timeframe captures multiple episodes of extreme market turbulence, including the global financial crisis, oil price collapses, the COVID-19 pandemic, and recent geopolitical disruptions.The analysis proceeds through a structured econometric methodology, beginning with the transformation of price levels into return series, followed by stationarity testing, descriptive statistical analysis, and volatility modeling.Empirical results reveal strong volatility clustering and persistence in WTI oil returns, confirming the suitability of GARCH-type models for capturing oil price dynamics.While asymmetric specifications (TGARCH and EGARCH) provide valuable insights into the differential effects of positive and negative shocks, the findings indicate that the GARCH(1,1) model offers the most 207 -www.imcra.az.org,

The a4a initiative aims to provide timely and cost effective advice for the circa. 250 fish stocks that,\nthrough the EU Data Collection Framework, will have at least 10 years of data by the year 2020. Current\nprocesses for assessing the state of and managing fish stocks are intensive processes, each stock\nrequiring the attention of one or more stock assessment scientist to produce preliminary catch advice,\nwhich is subsequently reviewed by one or two committees before the final catch advice is published.\nIngrained in the development of these processes has been the development of more and more complex\nstock assessment models which typically require highly skilled personnel to set up and run.

Lack of memory safety in C/C++ has resulted in numerous security vulnerabilities and serious bugs in large software systems. This paper highlights the challenges in enforcing memory safety for C/C++ programs and progress made as part of the SoftBoundCETS project. We have been exploring memory safety enforcement at various levels - in hardware, in the compiler, and as a hardware-compiler hybrid - in this project. Our research has identified that maintaining metadata with pointers in a disjoint metadata space and performing bounds and use-after-free checking can provide comprehensive memory safety. We describe the rationale behind the design decisions and its ramifications on various dimensions, our experience with the various variants that we explored in this project, and the lessons learned in the process. We also describe and analyze the forthcoming Intel Memory Protection Extensions (MPX) that provides hardware acceleration for disjoint metadata and pointer checking in mainstream hardware, which is expected to be available later this year.

This study was carried out to analyze traditional methods of milk processing and preservation by local farmers in Kashongi Sub County Kiruhura district. Milk producers in Kashongi Sub County own small and widely scattered farms, making access to markets a big challenge, given lack of well-developed infrastructure. Substantial amounts of milk remain at the farms, justifying preservation to avert total wastage. The study established the methods, equipment and materials used by the local farmers in milk processing, established the effectiveness of milk preservation methods used in the sub county and identified the possible areas of improvement on milk processing in the sub-county. The research design was descriptive in nature and therefore used qualitative methods to analyze the magnitude of the problem. It was partly quantitative because the findings were tallied, tabulated and calculated to percentages. A total of 160 respondents was targeted for this study. The category of the respondents that was selected are specifically cattle keepers, who have reared cattle for a long time. This category of people were selected because; they have reared cattle for a long time and know many aspects on the cow. Cattle keepers were specifically used because they directly deal with cattle products. The study findings revealed that quite number of local methods have been used to store, process and preserve milk. Some of these include; natural air cooling, boiling, traditional vessels like wooden churn and gravitational among others. These methods were used because they were favored these farmers. Focusing on Kashongi Sub County, these methods are widely used to preserve and store milk. However these local methods are not in line to preserve milk for long hours, and days, it is well known that these methods cannot go three to four days of preservation. Some strategies like provision of modern processing equipment, extension of agricultural services to train farmers on how to improve on handling milk should be provided by the government. Dairy products that can be manufactured by small scale dairies include fermented milk (Bongo - similar to yoghurt) and ghee. Some technologies for their improvement have been adapted to suit local conditions and some of the modified processing techniques have been tried successfully in Kashongi Sub-County areas to some farmers.

The overall aim of the current thesis was to explore three key components of future-oriented thinking, namely episodic future thinking (EFT), episodic foresight, and prospective memory (PM), in middle childhood. The developmental literature examining each of these future-oriented abilities has generally focused on their emergence in the preschool years, with less known about how these abilities present in middle childhood. In addition, research investigating what cognitive mechanisms may drive these abilities in this age band is limited and findings of those studies that have been conducted are inconsistent. Lastly, the literature has predominantly examined EFT, episodic foresight, and PM in isolation, and research has only just begun to explore interrelations between these future-oriented constructs. The first empirical study therefore aimed to investigate whether EFT ability was associated with age and to examine what cognitive mechanisms may contribute to this skill. The second empirical study aimed to examine, for the first time, whether episodic foresight was associated with age across middle childhood. A second aim of this study was to provide the first investigation of the cognitive mechanisms that may contribute to episodic foresight in this age group, with the particular interest in whether EFT contributed to episodic foresight. The final empirical study aimed to explore whether age was associated with children’s PM performance across event-based and time-based PM tasks. An additional aim of this study was to explore the cognitive abilities that contribute to children’s performance on both event-based and time-based PM tasks, with a particular interest in the contribution of EFT. A single sample of 80 children aged 8 to 12 years were recruited for this research project. Study 1 indicated greater EFT ability was associated with age, consistent with some of the limited studies previously conducted with this age group. Study 1 also demonstrated strong evidence regarding the contribution from episodic memory to children’s EFT and a lack of contribution from executive functions. Study 2 was the first study to examine episodic foresight beyond the preschool years. Results of this study provided the first evidence of an association between age and better episodic foresight performance across the ages of 8 to 12 years. In addition, Study 2 identified age and IQ as significant contributors to successful episodic foresight performance, while retrospective memory, executive functions, and EFT were not found to contribute. The lack of contribution from EFT may have been due to the specific form of episodic foresight task used in this study, which did not require a specific scenario to be envisaged. Further research is now required to investigate whether EFT contributes to other types of episodic foresight task that involve clear scenarios that can be envisaged. The results of Study 3 indicated age was significantly correlated with performance on both event-based and time-based PM tasks. The findings also clearly revealed age, retrospective memory, and EFT were significant contributors to event-based PM performance, while retrospective memory was the only significant contributor to time-based PM performance. Furthermore, the results clearly demonstrated a lack of contribution from executive functions to performance on both task types. Importantly, Study 3 demonstrated that EFT selectively contributed to children’s event-based PM performance. This finding is consistent with the only other study in this age band and used a more comprehensive set of predictors than this previous study. The current research provided novel insights into the profile of children’s future-oriented thinking across the middle childhood period. The findings regarding age-related improvements in EFT, episodic foresight, and PM help to bridge the gap in understanding of the development of these abilities between their emergence in the preschool years and their presentation later in development. Longitudinal research that extends from early childhood to adulthood is now needed to provide a thorough understanding of the developmental trajectory of these abilities across the lifespan. In addition, the current research revealed a clear pattern of results regarding the cognitive mechanisms that contribute to each of these abilities, providing some clarity to the previously mixed findings in the children’s future oriented-thinking literature. Results regarding the inter-relationships between the future-oriented constructs also provided an important extension to current understanding of future-oriented thinking as a broader taxonomy. Furthermore, the current findings bring attention to the need for further theoretical distinction between different forms of episodic foresight and the cognitive processes that contribute to this skill. Overall, the findings from the current thesis have important implications for children’s daily living. In particular, greater understanding of future-oriented thinking in the middle childhood period gained from this thesis may assist in fostering the development of these abilities early in life. This in turn will enable parents and teachers to create reasonable expectations regarding children’s capacity to use these skills in their everyday functioning, thereby maximising success and minimising failure.

An exploration into the assessment of hip extension strength and its importance for performance in professional soccer.

This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches from previous work, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams [13, 15]. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This research project is motivated by the MI6 project of the Computer Vision research group, which is located at the Bonn-Rhein-Sieg University of Applied Sciences. The intent of the MI6 project is the tracking of a user in an immersive environment. The proposed solution is to attach a light emitting device to the user for tracking the created light dots on the projection surface of the immersive environment. Having the center points of those light dots would allow the estimation of the user’s position and orientation. One major issue that makes Computer Vision problems computationally expensive is the high amount of data that has to be processed in real-time. Therefore, one major target for the implementation was to get a processing speed of more than 30 frames per second. This would allow the system to realize feedback to the user in a response time which is faster than the human visual perception. One problem that comes with the idea of using a light emitting device to represent the user, is the precision error. Dependent on the resolution of the tracked projection surface of the immersive environment, a pixel might have a size in cm2. Having a precision error of only a few pixels, might lead to an offset in the estimated user’s position of several cm. In this research work the development and validation of a detection and tracking system for BLOBs on a Cyclone II FPGA from Altera has been realized. The system supports different input devices for the image acquisition and can perform detection and tracking for five to eight BLOBs. A further extension of the design has been evaluated and is possible with some constraints. Additional modules for compressing the image data based on run-length encoding and sub-pixel precision for the computed BLOB center-points have been designed. For the comparison of the FPGA approach for BLOB tracking a similar implementation in software using a multi-threaded approach has been realized. The system can transmit the detection or tracking results on two available communication interfaces, USB and RS232. The analysis of the hardware solution showed a similar precision for the BLOB detection and tracking as the software approach. One problem is the strong increase of the allocated resources when extending the system to process more BLOBs. With one of the applied target platforms, the DE2-70 board from Altera, the BLOB detection could be extended to process up to thirty BLOBs. The implementation of the tracking approach in hardware required much more effort than the software solution. The design of high level problems in hardware for this case are more expensive than the software implementation. The search and match steps in the tracking approach could be realized more efficiently and reliably in software. The additional pre-processing modules for sub-pixel precision and run-length-encoding helped to increase the system’s performance and precision.

Flash memory cells typically undergo a few thousand Program/Erase (P/E) cycles before they wear out. However, the programming strategy of flash devices and process variations cause some flash cells to wear out significantly faster than others. This paper studies this variability on two commercial devices, acknowledges its unavoidability, figures out how to identify the weakest cells, and introduces a wear unbalancing technique that let the strongest cells relieve the weak ones in order to lengthen the overall lifetime of the device. Our technique periodically skips or relieves the weakest pages whenever a flash block is programmed. Relieving the weakest pages can lead to a lifetime extension of up to 60% for a negligible memory and storage overhead, while minimally affecting (sometimes improving) the write performance. Future technology nodes will bring larger variance to page endurance, increasing the need for techniques similar to the one proposed in this work.

Cluster computing has recently gone through an evolution from single processor systems to multicore/multi-socket systems. This has resulted in lowering the cost/performance ratio of the compute machines. Compute farms that host these machines tend to become heterogeneous over time due to incremental extensions, hardware upgrades and/or nodes being purchased for users with particular needs. This heterogeneity is not surprising given the wide range of processor, memory and network technologies that become available and the relatively small price difference between these various options. Different CPU architectures, memory capacities, communication and I/O interfaces of the participating compute nodes present many challenges to job scheduling and often result in under or over utilization of the compute resources. In general, it is not feasible for the application programmers to specifically optimize their programs for such a set of differing compute nodes, due to the difficulty and time-intensiveness of such a task. The trend of heterogeneous compute farms has coincided with resurgence in the virtualization technology. Virtualization technology is receiving widespread adoption, mainly due to the benefits of server consolidation and isolation, load balancing, security and fault tolerance. Virtualization has also generated considerable interest in the High Performance Computing (HPC) community, due to the resulting high availability, fault tolerance, cluster partitioning and accommodation of conflicting user requirements. However, the HPC community is still wary of the potential overheads associated with virtualization, as it results in slower network communications and disk I/O, which need to be addressed. The live migration feature, available to most virtualization technologies, can be leveraged to improve the throughput of a heterogeneous compute farm (HC) used for HPC applications. For this we mitigated the slow network communication in Xen; an open source virtual machine monitor. We present a detailed analysis of the communication framework of Xen and propose communication configurations that give 50% improvement over the conventional Xen network configuration. From a detailed study of the migration facility in Xen, we propose an improvement in the live migration facility specifically targeting HPC applications. This optimization gives around 50% improvement over the default migration facility of Xen. In this thesis, we also investigate resource scheduling in heterogeneous compute farm with the perspective of dynamic resource re-mapping. Our approach is to profile each job in the compute farm at runtime, and propose a better resource mapping compared to the initial allocation. We then migrate the job(s) to the best-suited homogeneous sub-cluster to improve overall throughput of the HC. For this, we develop a novel heterogeneity and virtualization-aware profiling framework, which is able to predict the CPU and communication characteristics of high performance scientific applications. Our experimental setup consists of a 32 node virtualized cluster with machines having CPU frequency between 2 GHz to 3 GHz. The framework was tested with a subset of NAS parallel benchmarks with the workload generated from Dror Feitelson’s workload archives. The prediction accuracy of our performance estimation model is over 80%. The framework implementation is lightweight, with an overhead of 3%. Our experiments show that we are able to improve the throughput of the compute farm by 25% and the time saved by the HC with our framework is over 30%. The framework can be readily extended to HCs supporting a cloud computing environment.

The research aims to contribute to the review process of the specific ecodesign requirements on the durability of the hose and the operational motor lifetime of the vacuum cleaner (VC) product group. For this purpose a comprehensive method for the environmental and economic assessment of extending the lifetime of VCs has been developed and applied, based on the former indexes developed within the ‘REAPro’ method (Ardente and Mathieux, 2014). The starting point of the analysis was the performing of a Life Cycle Assessment of an exemplary VC, complemented with the analysis of the literature. The functional unit was a bagged canister VC with an operating time of 10 years. A sensitivity analysis has been implemented considering potential changes in the manufacturing, repair, maintenance and energy consumption. Successively, the potential extensions of the lifetime of the VC have been analysed through the application of Durability indexes. The research showed that extending the lifetime of VCs generally implies benefits, from both environmental and economic perspectives, for the large majority of scenarios considered. In general, these benefits already exist for small extensions of lifetime, and they become significant if the lifetime is extended further. These results could be used to promote the design of more durable products, e.g. via more ambitious policy measures. The research also highlighted the relevance of repairability of VCs from both environmental and economic points of view. Repairability could be promoted for instance through a proper ‘design for repairing’ of products but also the availability of information and tools for the repair and/or replacement of some components. Finally, the importance of the role of consumers has been confirmed, in terms of proper use of VCs during their operation phase and

We study the asymtotic behaviour of a viscoelastic fluid in a porous medium obtained by removing from an open set small obstacles of size periodically distributed on a hyperplane H which intersects . We establish that the fluid behave differently depending on whether the size is greater than or smaller than a critical size . If , a convolution term appears in the limit problem. This corresponds to a long memory effect. If is smaller than , the fluid behaves as if there where no obstacles. If is greater than or is of the order of the period, the fluid adheres on the hyperplane H which plays a thin solid plate role and the fluid behaves separately on each side of this plate.

The concept of fractional cointegration, whereby deviations from an equilibriun relationship are allowed to follow a fractionally integrated process, has attracted some attention in the literature of late. The long memory Eispect of the fractional process is seen as an appropriate characterization of slow reversion to an equilibrium relationship. This paper presents a Bayesian method for conducting inference within the context of a fractional cointegration model. The analysis is based on an approximate likelihood function, which is motivated by the need both to solve a fundamental identification problem and to produce a posterior density with a relatively simple algebraic form. Inferences are based on the associated marginal posterior densities, estimated by a hybrid of the Gibbs and Metropolis Markov Chain Monte Carlo methods.

Reinforcement Learning (RL) Markov Decision Processes is studied with an emphasis on the well-studied exploration problem. We first formulate and discuss a definition of “efficient” algorithms that is termed Probably Approximately Correct (PAC) in RL. Next we provide general sufficient conditions for such an algorithm that applies to several different modeling assumptions. The conditions can be used to demonstrate that efficient learning is possible in finite MDPs, with either a model-based or model-free approach, in factored MDPs, and in continuous MDPs with linear dynamics. In the reinforcement-learning (RL) problem (Sutton & Barto 1998), an agent acts in an unknown or incompletely known environment with the goal of maximizing an external reward signal. In the most standard mathematical formulation of the problem, the environment is modeled as a Markov Decision Process (MDP) and the goal of the agent is to obtain near-optimal discounted return. Over the years, many algorithms have been proposed for this problem, but analyses of their performances have been relatively scarce. In fact, until recently, most theoretical guarantees have been that certain algorithms will discover an optimal policy in the limit, after an infinite amount of experience. In contrast, several attempts have been made to study “Probably Approximately Correct” or PAC-MDP algorithms, which exhibit near-optimal behavior in polynomial time and experience. This paper discusses several extensions of those results. We present a theorem that provides sufficient conditions for an algorithm to be PAC-MDP. We examine these conditions and show how they can be applied to prove that efficient learning is possible in three interesting scenerios: finite MDPs (i.e. the “Tabular case”),