nils-herrmann/clean_scirepeval huggingface dataset:
Ternary and Hybrid Event based Particle Filtering forDistributed State Estimation in Cyber Physical Systems
Year: 2018

The thesis is motivated by recent advancements and developments in large, distributed, autonomous, and self aware Cyber Physical Systems (CPSs) which are emerging engineering systems with integrated processing, control, and communication capabilities. Efficient usage of available resources (communication,computation, bandwidth, and energy) is a pre requisite for productive operation of CPSs, where security, privacy, and/or power considerations limit the number of information transfers between neighbouring sensors. In this regard, the focus of the thesis is on information acquisition, state estimation, and learning in the context of CPSs by adopting an Event based Estimation (EBE) strategy, where information transfer is performed only in the occurrence of specific events identified via the localized triggering mechanisms. In particular, the thesis aims to address the following identified drawbacks of the existing EBE methodologies: (i) At one hand, while EBE using Gaussian based approximations of the event triggered posterior has been fairly investigated, application of non linear, non Gaussian filtering using particle filters is still in its infancy, and; (ii) On the other hand, the common assumption in the existing EBE strategies is having a binary (idle and event) decision process where during idle epochs, the sensor holds on to its local measurements while during the event epochs measurement communication happens. Although the binary event based transfer of measurements potentially reduces the communication overhead, still communicating raw measurements during all the event instances could be very costly. To address the aforementioned shortcomings of existing EBE methodologies, first, an intuitively pleasing event based particle filtering (EBPF) framework is proposed for centralized, hierarchical, and distributed (iii)state estimation architectures. Furthermore, a novel ternary event triggering framework, referred to as the TEB PF, is proposed by introducing the ternary event triggering (TET) mechanism coupled with a non Gaussian fusion strategy that jointly incorporates hybrid measurements within the particle filtering framework. Instead of using binary decision criteria, the proposed TET mechanism uses three local decision cases resulting in set valued, quantized, and point valued measurements. Due to a joint utilization of quantized and set valued measurements in addition to the point valued ones, the proposed TEB PF simultaneously reduces the communication overhead, in comparison to its binary triggering counterparts, while also improves the estimation accuracy especially in low communication rates.
Resource and Cost Aware Glowworm Mapreduce Optimization Based Big Data Processing in Geo Distributed Data Center
Venue: Wirel. Pers. Commun.
Year: 2021

Handling large data in geographically distributed information centers with resource and cost optimization is a key challenge. With several approaches being designed, handling a large volume of data in multiple datacenters in an inappropriate manner yet is considered to be a time consuming process. To address these issues, a Multivariate Metaphor based Metaheuristic Glowworm Swarm Map Reduce Optimization (MM MGSMO) technique is presented. Here, with search space and large data volume as input for geo distributed datacenters, glowworm (i.e. virtual machine) population is initialized. With each glowworm possessing a certain amount of luciferin (i.e. objective function) multiple objective functions (i.e. bandwidth, storage capacity, energy and computation cost) are defined for each virtual machine. Next, the glowworm position is updated according to the neighboring factor by means of probability. Followed by this, MapReduce function identifies the optimal virtual machine and accordingly allocation is performed, therefore improving data allocation efficiency. Besides, the workload is assigned across datacenters, reduction in computation cost and storage capacity is guaranteed. Experimental evaluation of MM MGSMO approach with existing methods attained improved performances with factors such as data allocation efficiency, false positive rate, storage capacity compared with other cutting edge technologies such as Joint optimization algorithm and Game theory based dynamic resource allocation strategy.
Super high speed electric motor with amorphous magnetic circuit for the hydrogen fuel cell air supply system
Year: 2018

Hydrogen fuel cells are one of the important directions of development of the global energy. Hydrogen fuel cells are being actively implemented in the aviation systems, for example in Airbus A320. Boeing and Airbus announced creation of an auxiliary power unit fuel cell with capacity up to 200 kW in 2017 2018. In the automotive industry hydrogen fuel cells are also widely used. But the efficient use of hydrogen fuel cells is not possible without establishment of effective systems related to their operation. Therefore, our article proposes a new topology of high speed motor for compressor of the hydrogen fuel cell. An original solution to raise the energy efficiency of high speed motor presented in our article, the novelty of which is the use of amorphous alloys. Research of the new design methods of computer modeling in Ansys Maxwell was conducted; optimal geometric dimensions of the high speed motor with two pole and four pole magnetic system were obtained in this article. In the modeling losses on eddy currents in permanent magnets and iron of the rotor for two pole and four pole magnetic systems were taken into account. All the theoretical results have been experimentally verified. For this purpose the layout of the high speed motor with the perforated winding was created. Design of the experimental model is also described in this article. The high speed motor testing and analysis of test data take a special place in this article. In the experimental tests was found that the efficiency of our topology is 92.8% and the power density of our high speed motor is 0.21 kg/kW with air cooling. These experimental tests prove the effectiveness of our topology compared to the known world analogues. Also in the article was proven that the use of our topology allows minimizing the mass of a hydrogen fuel cell with improved energy efficiency. This is especially important for the aerospace applications and automotive industry.
Transient characterization techniques for resistive metal oxide gas sensors
Year: 2011

We present three different time domain characterization techniques for resistive metal oxide gas sensors. They are based on electric resistance transients induced by small step changes in either temperature, bias voltage, or concentration of reducing gas. Conduction model of granular semiconductors and an electronic trapping (adatom ionization) rate equation at the grain boundaries are employed. Fitting of the presented analytical transient models to the experimental data allows calculation of the time constant of the electronic trapping process, the height of the grain boundary potential barrier, the relative change of the occupied grain boundary states, the resistance coefficient, and the effective number of grain boundaries between the electrodes of the sensor. These values can be further used for studying the underlying physicochemical phenomena and increasing the selectivity of the sensor. Fitting of a simple model to the measured transient values yields the energies associated with the electronic trapping process and the reducing gas reaction with the preadsorbed oxygen, as well as the rate constant of the trap releasing and the reducing gas parameter. The use of the proposed techniques is verified in experiments with commercial resistive WO 3 and SnO 2 based gas sensors in clean and humid air and in acetone and isopropyl alcohol vapours. The experiments were performed using a pulsing system for chemical vapours and a sensor temperature control system based on a field programmable gate array (FPGA) processor. In the SnO 2 based sensor the grain boundary potential barrier is 0.35 V at 270 degC and 0.49 V at 350 degC. At 80% relative humidity these values increase to 0.41 V and 0.52 V. In dry clean air the electronic trapping and releasing energies are 0.94 eV and 0.86 eV.
WGANSing: A Multi Voice Singing Voice Synthesizer Based on the Wasserstein GAN
Venue: 2019 27th European Signal Processing Conference (EUSIPCO)
Year: 2019

We present a deep neural network based singing voice synthesizer, inspired by the Deep Convolutions Generative Adversarial Networks (DCGAN) architecture and optimized using the Wasserstein GAN algorithm. We use vocoder parameters for acoustic modelling, to separate the influence of pitch and timbre. This facilitates the modelling of the large variability of pitch in the singing voice. Our network takes a block of consecutive frame wise linguistic and fundamental frequency features, along with global singer identity as input and outputs vocoder features, corresponding to the block of features. This block wise approach, along with the training methodology allows us to model temporal dependencies within the features of the input block. For inference, sequential blocks are concatenated using an overlap add procedure. We show that the performance of our model is competitive with regards to the state of the art and the original sample using objective metrics and a subjective listening test. We also present examples of the synthesis on a supplementary website and the source code via GitHub.
Turkey Indonesia Tax Treaty Post MLI
Venue: SSRN Electronic Journal
Year: 2020

As part of the G20 countries, Indonesia and Turkey have shown their commitments to the OECD/G20 BEPS Project since the very beginning, including the MLI Project. Along with the other 66 jurisdictions, Indonesia and Turkey signed the MLI on 7 June 2017. Indonesia and Turkey already have a tax treaty in force. In its MLI's position as of 7 June 2017, Indonesia included its tax treaty with Turkey as one of CTAs and vice versa. Therefore, once both countries have completed all the procedural requirements of the MLI, the MLI provisions will have effect on the existing tax treaty. This article is intended to give a picture for the readers on how the MLI impacts the existing tax treaty between Indonesia and Turkey. This article may also serve as a projection on what a synthesised text might look like even though it has not been published yet by the competent authority of either country. For the MLI changes to apply effectively to the Indonesia Turkey tax treaty, both countries must adopt the same provisions (unless an asymmetrical adoption is allowed in particular cases) The Authors concluded that considering both countries' positions at this moment, some of the MLI provisions will affect the existing Indonesia Turkey tax treaty, i.e. Article 6, 7, 9, 12, 13, 15, and 16 of the MLI. New provisions to be adapted will contribute to preventing BEPS concerns, e.g. through treaty shopping. The authors then recommend that both countries should also need to revise their domestic laws in order to accommodate new features in treaty post MLI, for instance, the introduction of PPT rule as GAAR in tax treaty should also be accompanied by a comprehensive set of guidelines for tax authorities and must be administered transparently. Following the intention of both countries to increase the trading volume, the Indonesia Turkey tax treaty post MLI will play an important role in the future.
"We're Continually Comparing Ourselves to Something" Navigating Body Image, Media, and Social Media Ideals at the Nexus of Appearance, Health, and Wellness
Year: 2020

In modern Western society, women commonly encounter media that conflates appearance and health. However, this phenomenon is seldom explored qualitatively from the perspective of the women who encounter and internalize these messages. The present study describes how a group of women perceive appearance, health, and wellness ideals promoted through media and social media as well as how they attempted to challenge and negotiate these. Qualitative data were collected from in depth semi structured interviews with 25 women (aged 22 72 years) who embraced a holistic health perspective in Perth, Western Australia. Thematic analysis of the data revealed multiple overarching themes, including the women's recognition of unrealistic ideals in the media, the potential for harmful social comparisons, their desire to achieve the appearance of health and wellness, and the use of various strategies to modify their exposure to such media and uphold a positive body image. Some participants were challenged by media claiming a more "holistic" orientation in which ideals of appearance, health, and wellness are closely intertwined. The findings from our research provide timely guidance on mechanisms to promote positive body image amidst a rapidly changing media landscape, including the use of critical media literacy and social media literacy interventions. Such interventions should encourage critical appraisal of appearance ideals that are promoted under the guise of health and wellness.
Change in supply networks: a case study in the automotive components industry
Year: 2018

The purpose of this paper is to analyze the evolution of a supply network and the causes of network change and stability. It presents the study of a supply network of Delphi Braga (Portugal) one of the largest European plants producing car radios, navigation system and other related products, in order to understand how it changed over time. The paper contributes to the understanding of network management.,The case study was carried out on a network of five suppliers of Delphi Braga adopting a relational view of networks meaning that both parties of the relationships were studied. Data and results are based on document sources and interviews with managers both from Delphi and the studied suppliers.,The causes of network change and stability are both exogenous and endogenous. They are multiple and have different impacts on network structures and processes. The paper analyses several causes of network change and their impact on the studied supplier network.,The research is based on a single case study. Although the studied supplier network comprises several firms, it should be pointed out that each network has its own dynamics and structures. Therefore, though the paper makes a relevant contribution for network management, the results cannot be generalized for other networks and firms.,Managers should be aware of the dynamics of their supplier networks and understand the different impacts of both their firm's decisions as well as the environment changes. By doing this, managers can anticipate changes in the structure and dynamics of their supplier networks.,This case study contributes to our current understanding of relationship development both at the dyadic and network level by analyzing the case of a supply network in a major European plant of car radios and navigation systems. It discusses implications and proposes further research to advance knowledge on the topic of network change.
Analise da estabilidade global de edificios com multiplos pavimentos em concreto armado com diferentes tipos de lajes e inclusao de nucleos rigidos
Year: 2017

The use of different types of slabs in the execution of high buildings has been increasing a lot in recent years in the Brazilian market. The buildings have a bold and slender architecture, they bring to the engineering the challenge of executing a structure with different models and executive methods, and as a consequence arise the difficulties in guaranteeing the overall stability of the buildings. The choice of slab type and the inclusion of a rigid core in multi floor building structures is an important choice, and global stability analysis of buildings are directly influenced by this choice. The evaluation of the global stability of reinforced concrete structures, normalized by the Brazilian standard ABNT NBR 6118: 2014, is performed through the global stability parameters parameter a (alpha) and coefficient gz (Range Z) in addition to the iterative P Delta process. In this research, we tried to study the global stability in multifloor buildings with different types of slabs and inclusion of rigid cores. For the modeling, the commercial CAD TQS program was used. The results showed that the structure with solid slab was more rigid compared to structures with prefabricated slab and ribbed slab, obtaining lower values of Coefiente Gama Z and the inclusion of the rigid core considerably increased the rigidity of all structures analyzed.
Clinical assessment of sensory processing sensitivity
Year: 2020

This chapter covers four topics. First, we explore assessment of sensory processing sensitivity (SPS) (in one individual, as opposed to conclusions drawn in research settings) including the best use of the highly sensitive person (HSP) scale; sorting out the trait from other similar traits such as high sensation seeking (which is independent of high sensitivity) and taking into consideration the person's history, which greatly affects presentation of symptoms. Second, we examine specific issues arising when working with HSPs. For example, the advantages and disadvantages of both client and therapist having this trait, versus the therapist not having it. Third, we consider how to approach the three most common problems reported by HSP clients, namely, issues due to being easily overstimulated, having strong emotional responses, and exhibiting low self esteem. Finally, we discuss issues that often occur for HSPs in their relationships and at work, and provide strategies that may be especially beneficial for the highly sensitive in a therapeutic context. Overall, working with these clients can provide considerable rewards, often by simply helping them see how their sensitivity has been affecting their lives, for better and for worse.
RC SSFL: Towards Robust and Communication efficient Semi supervised Federated Learning System
Venue: ArXiv
Year: 2020

Federated Learning (FL) is an emerging decentralized artificial intelligence paradigm, which promises to train a shared global model in high quality while protecting user data privacy. However, the current systems rely heavily on a strong assumption: all clients have a wealth of ground truth labeled data, which may not be always feasible in the real life. In this paper, we present a practical Robust, and Communication efficient Semi supervised FL (RC SSFL) system design that can enable the clients to jointly learn a high quality model that is comparable to typical FL's performance. In this setting, we assume that the client has only unlabeled data and the server has a limited amount of labeled data. Besides, we consider malicious clients can launch poisoning attacks to harm the performance of the global model. To solve this issue, RC SSFL employs a minimax optimization based client selection strategy to select the clients who hold high quality updates and uses geometric median aggregation to robustly aggregate model updates. Furthermore, RC SSFL implements a novel symmetric quantization method to greatly improve communication efficiency. Extensive case studies on two real world datasets demonstrate that RC SSFL can maintain the performance comparable to typical FL in the presence of poisoning attacks and reduce communication overhead by $2 \times \sim 4 \times
Learning to select data for transfer learning with Bayesian Optimization
Venue: EMNLP
Year: 2017

Domain similarity measures can be used to gauge adaptability and select suitable data for transfer learning, but existing approaches define ad hoc measures that are deemed suitable for respective tasks. Inspired by work on curriculum learning, we propose to learn data selection measures using Bayesian Optimization and evaluate them across models, domains and tasks. Our learned measures outperform existing domain similarity measures significantly on three tasks: sentiment analysis, part of speech tagging, and parsing. We show the importance of complementing similarity with diversity, and that learned measures are to some degree transferable across models, domains, and even tasks.
Introduction to professor HE Pu ren's three edged needle therapy techniques
Year: 2015

He's bloodletting therapy utilizing three edged needles is one of his "three adjusting methods of acupuncture" During his 70 years of clinical practice, he developed the theory that most diseases are caused by qi stagnation, and in order to restore qi circulation one needs to improve the blood circulation first. Based on this theory, in combination with empirical insights from clinical practice, he has developed a unique technique for using three edged needles. He has also categorized and extended the application of bloodletting therapy with three edged needles to cover over 150 diseases. In addition, Dr. He's bloodletting therapy with three edged needles is an innovation that may inspire other physicians to develope and expand the use of acupuncture related therapies to treat disease.
Advances in adjuvant endocrine therapy for postmenopausal women.
Venue: Journal of clinical oncology official journal of the American Society of Clinical Oncology
Year: 2008

Hormone receptor positive cancers are the most common tumor subtype among postmenopausal women with breast cancer. Despite substantial improvements in disease free survival and overall survival with tamoxifen and chemotherapy, recurrences still occur, and may ultimately lead to death from breast cancer. Importantly, disease recurrence includes both early and late events, with over half of all recurrences detected more than 5 years from initial breast cancer diagnosis. In recent years, a number of large, randomized trials have evaluated the role of the aromatase inhibitors (AIs) in postmenopausal women with hormone receptor positive breast cancer. These studies have tested one of three approaches: (1) an upfront AI, (2) a sequential approach after 2 3 years of tamoxifen, and (3) extended endocrine therapy beyond 5 years. Results of these studies have challenged the previous standard of a 5 year course of tamoxifen alone. While the AIs have become a standard component of treatment for most postmenopausal women, many questions remain as to how best tailor endocrine treatment to individual patients. In addition, despite the gains achieved with the AIs, many recurrences are not prevented, and novel strategies are urgently needed, particularly for those women at high risk of recurrence. In this article, we review the efficacy and toxicity data from the available trials of endocrine therapy in the postmenopausal setting. We outline controversies in choosing the optimal endocrine approach, and we discuss selected ongoing studies. Finally, we highlight future research directions, such as the need to understand host and tumor heterogeneity.
The Influence of Nurse Manager Leadership Style on Staff Nurse Work Engagement.
Venue: The Journal of nursing administration
Year: 2017

Nursing literature supports the importance of an engaged nursing workforce as a means to positively influence performance. Nurse manager leadership style plays a critical role in engaging staff nurses. These relationships have been minimally studied in nurse managers and staff nurses.  The aim of this study is to evaluate the influence of nurse manager leadership style factors on staff nurse work engagement.  Using a descriptive correlational research design, 441 staff nurses working in 3 acute care hospitals were surveyed. Survey instruments included the Utrecht Work Engagement Scale and the Multifactorial Leadership Questionnaire 5X short form.  Transactional and transformational leadership styles in nurse managers positively influenced staff nurse work engagement. Passive avoidant leadership style in nurse managers negatively influenced staff nurse work engagement.  Nurse managers who provide support and communication through transformational and transactional leadership styles can have a positive impact on staff nurse work engagement and ultimately improve organizational outcomes.