Multiple Facts Research Articles

Applications of Multi-Objective OPF Solutions with Optimal Placement of Multiple and Multi-Type FACTS Units to IEEE System: Comparison of Different Approaches

Optimal power flow (OPF) problem and its implications for power system stability and efficiency is investigated in this study. OPF, a restricted optimization query with non-linearity and non-convexity, is one of the most challenging and fascinating problems in the recent power system. Based on these parameters, researchers have been working hard over the past few decades to identify the best solutions to the OPF issue that maintain system stability. This work presents multi-objective OPF solutions utilizing Newton's technique with numerous multi-type FACTS units. First, the GA is applied to identify the perfect size and location of the FACTS units. Next, the generator and FACTS settings are optimized. In this instance, four scenarios are taken into consideration and three OFs are employed to see how the OFs affect the positioning and dimensions of FACTS devices. The OF is suggested to consider the reduction of both generation costs and transmission losses while also optimizing the power transfer capacity of designated corridors. A full analysis relating to the IEEE-30 bus system is presented and analyzed.

Generative and active engagement in learning neuroscience: A comparison of self-derivation and rephrase

It is crucial to identify cognitive mechanisms that support knowledge growth. One such mechanism that is known to improve learning outcomes is generative processing: the construction of novel information beyond what is directly taught. In this study of college students, we investigate the learning outcomes associated with the generative process of self-derivation through integration, the integration of multiple related facts to generate novel information. We compare the effects of self-derivation versus an active rephrase control condition on retrieval, application, and organization of neuroscience classroom content. In the self-derivation condition, learners were prompted to generate inferences based on integration of two explicitly-taught facts. In the rephrase condition, learners were explicitly provided these inferences and asked to rephrase them. We found few overall differences between learning manipulation conditions. However, we found that, regardless of the learning manipulation condition to which learners were exposed, learners generated their own information on some trials. This generation predicted success on retrieval and application of learned information. Further, self-derivation, when successful, led to particularly high rates of retrieval when compared with active rephrase. These findings inform theory on generative processing, and demonstrate that self-derivation is a mechanism of knowledge growth that may be useful for retrieval.

Determining Teachers' Views and Behaviors Towards Current Physical Education in the Changing Understanding of Education: A Phenomenological Study

The aim of this study is to present multiple facts and reveal an in-depth understanding by examining teachers' views and behaviors towards current physical education from a holistic perspective. The study was conducted with 21 physical education teachers. The phenomenology design was used. The data were collected using the interview technique and a semi-structured interview form. As a result of the content analysis, three themes were identified: Physical Education Course Content, Distance Physical Education and Technology Use and Health-Based Physical Education. As a result, although the distance education process is described as a difficult experience by the teachers, it has provided some gains in terms of health-based physical education and the use of technology in physical education. We recommend creating sharing environments that will unite in-service and pre-service teachers. Schools should follow approaches that will encourage healthy living and physical activity for everyone along with the task of bringing talented children together with sports.

Towards Automated Infographic Authoring From Natural Language Statement With Multiple Proportional Facts

Towards Automated Infographic Authoring From Natural Language Statement With Multiple Proportional Facts

Optimal allocation of multiple FACTS devices considering power generation pricing for optimal reactive power dispatch using kinetic gas molecule optimisation

Optimal allocation of multiple FACTS devices considering power generation pricing for optimal reactive power dispatch using kinetic gas molecule optimisation

Technology Utilization and Physical Engagement Among Children with Disabilities in Nepal

This study aims to explore how the utilization of modern technology by children with disabilities may lead to sedentary behaviors. This study is informed by the interpretive paradigm. An explorative qualitative research design was adopted to approach the phenomenon. This study has covered three different disability groups: visual impairment, hearing impairment, and physical disability. In order to cover these groups, three integrated schools were purposively selected for the study. Altogether, 22 participants—head teachers, teachers, students, parents, and members of Disabled People Organization— were purposively selected. In-depth interview guidelines and key informant interview guidelines were used as data collection tools. The obtained data were analyzed and interpreted thematically by using multiple facts and critical views. Children with disabilities were found to be interested in participating in various kinds of physical activities. Children are increasingly attracted to the newest forms of technology. With the exponential development of smartphones and tablets, the use of technology devices has become unavoidable and is now viewed as an integral part of life. Digital technology was found to be one of the main causes of physical inactivity among children with disabilities. The entire group of stakeholders is advised to increase outdoor activities to promote physical fitness and health of children with disabilities.

Stop the Immigration Bill: Fighting to End Human Rights Violations and Xenophobia in Japan

Abstract In March 2023, the Japanese Cabinet submitted a controversial amendment bill to the Immigration Control and Refugee Recognition Law to the ordinary Diet session. As an association working with refugees and foreign workers living in Japan, we strategically formed a protest movement against the bill both inside and outside the parliament. The parliament ignored opposition voices and approved the bill, but this result was far from the opposition’s defeat. The protest movement helped reveal multiple facts that had been concealed by Immigration and caused a drastic increase in recognition of Immigration issues in Japan.

Chronological simulation and Quantitative Evaluation of System Reliability in a Complex Restructured Power System

Ensuring the provision of high-quality and dependable power supply to customers stands as a paramount responsibility within the realm of power systems. The concept of restructuring the power system emerges as an efficient approach to deliver economically viable and uninterrupted power supply. The assessment of power system reliability hinges on various factors, with the reliability index serving as a pivotal metric, dependent on both system security and adequacy. To enhance the reliability index, strategically locating FACTS devices becomes essential, a task facilitated through power flow analysis with specified constraints, pinpointing the weakest points through Genetic Algorithm-driven fast-acting device placement. The correlation between DG establishment and the reliability index was meticulously calculated, further bolstered by the introduction of a Derated Forced Outage Rate for enhanced performance assessment. In the pursuit of heightened power system reliability, sequential simulations prove invaluable, particularly in minimizing Expected Energy Not Supplied (EENS) and improving overall system reliability. The results obtained through sequential simulations underscore the effectiveness of this approach within bulk electrical systems. The installation of multiple FACTS devices in the system's weakest areas facilitated EENS computation, coupled with the assessment of related reliability indices such as system frequency and system duration. This approach not only enhances system reliability but also promotes the economic operation of both transmission and distribution.The simulation results substantiate the alignment of power system reliability objectives in deregulated power systems with the required standards, advocating for the restructuring of power networks. The reliability assessments, driven by the optimal placement of DGs and FACTS devices, reveal substantial improvements in system reliability, underscoring the pivotal role of these technologies in enhancing overall power system dependability.

Coordinated design of PSS and multiple FACTS devices based on the PSO-GA algorithm to improve the stability of wind–PV–thermal-bundled power system

Coordinated design of PSS and multiple FACTS devices based on the PSO-GA algorithm to improve the stability of wind–PV–thermal-bundled power system

Generative processes and knowledge revision

Which learning processes best support revision of educationally-relevant misconceptions in college students? In this study, we investigated the generative process self-derivation through memory integration, the integration of multiple facts to generate novel, never-directly-taught information. Specifically, we examined whether self-deriving correct information supported revision of misconceptions above and beyond an active, yet non-generative, learning process: rephrasing directly-provided correct information. We found that misconception revision occurred across both conditions, but at higher rates in the rephrase condition. However, the two learning processes led to equal success in revising misconceptions when only correct, generative self-derivation trials were considered. Thus, correctly generating one’s own information was critical for success in the self-derivation condition. These findings contribute to our understanding of generative learning processes such as self-derivation. The results also offer insight into scaffolding misconception revision, particularly highlighting the benefit of directly exposing learners to corrective information.

A Combination of Appropriate Placement and size of Multiple FACTS Controllers to reduce Voltage Sag and Swell

Today's power system is going through a power quality crisis as a result of rising power demand and an increase in industrial facilities. The forms must be pure sinusoidal and harmonic-free, and the power source must always be reachable within voltage and frequency restrictions. This study uses numerous FACTS controllers in a radial distribution system to handle power quality concerns. Placement of FACTs controllers in the distribution system under various load conditions presents the biggest challenge. The system is run while deploying single and multiple FACTS controllers at the critical buses in order to avoid conflicts. This paper presents on the installation of a DSTATCOM, Integrated Dynamic Voltage Restorer-Ultra Capacitor (IDVR-UC), and UPQC to reduce power quality issues for conventional IEEE-33 bus distribution systems.

Transformer-Based Multi-Hop Question Generation (Student Abstract)

Question generation is the parallel task of question answering, where given an input context and, optionally, an answer, the goal is to generate a relevant and fluent natural language question. Although recent works on question generation have experienced success by utilizing sequence-to-sequence models, there is a need for question generation models to handle increasingly complex input contexts to produce increasingly detailed questions. Multi-hop question generation is a more challenging task that aims to generate questions by connecting multiple facts from multiple input contexts. In this work, we apply a transformer model to the task of multi-hop question generation without utilizing any sentence-level supporting fact information. We utilize concepts that have proven effective in single-hop question generation, including a copy mechanism and placeholder tokens. We evaluate our model’s performance on the HotpotQA dataset using automated evaluation metrics, including BLEU, ROUGE and METEOR and show an improvement over the previous work.

Question Decomposition Tree for Answering Complex Questions over Knowledge Bases

Knowledge base question answering (KBQA) has attracted a lot of interest in recent years, especially for complex questions which require multiple facts to answer. Question decomposition is a promising way to answer complex questions. Existing decomposition methods split the question into sub-questions according to a single compositionality type, which is not sufficient for questions involving multiple compositionality types. In this paper, we propose Question Decomposition Tree (QDT) to represent the structure of complex questions. Inspired by recent advances in natural language generation (NLG), we present a two-staged method called Clue-Decipher to generate QDT. It can leverage the strong ability of NLG model and simultaneously preserve the original questions. To verify that QDT can enhance KBQA task, we design a decomposition-based KBQA system called QDTQA. Extensive experiments show that QDTQA outperforms previous state-of-the-art methods on ComplexWebQuestions dataset. Besides, our decomposition method improves an existing KBQA system by 12% and sets a new state-of-the-art on LC-QuAD 1.0.

Multi-hop Question Generation without Supporting Fact Information

Question generation is the parallel task of question answering, where given an input context and optionally, an answer, the goal is to generate a relevant and fluent natural language question. Although recent works on question generation have experienced success by utilizing sequence-to-sequence models, there is a need for question generation models to handle increasingly complex input contexts with the goal of producing increasingly elaborate questions. Multi-hop question generation is a more challenging task that aims to generate questions by connecting multiple facts from multiple input contexts. In this work we apply a transformer model to the task of multi-hop question generation, without utilizing any sentence-level supporting fact information. We utilize concepts that have proven effective in single-hop question generation, including a copy mechanism and placeholder tokens. We evaluate our model's performance on the HotpotQA dataset using automated evaluation metrics and human evaluation, and show an improvement over the previous works.

Exploration of Malady and Trepidation in Bird Box: A Psychoanalytic Study

This study confronts the dichotomies of exploring psychoanalytical theory in the novel Bird Box. It is conducted by using qualitative methods of research. The theoretical framework of psychoanalysis put forward by Sigmund Freud provides a concrete base for this study. The research work scrutinizes data through the theoretical lens of psychoanalysis and false societal perceptions. It examines the malignant after-effect of anxiety by observing that this anxiety is orchestrating the origination of some anxiety disorders among the people. The aim of the study is to analyze the origination, sources, and aftermath of malady and trepidation on the main protagonist Malorie and the inhabitants of River bridge. Additionally, the study explores and sensitively tackles the multiple facts of psychoanalysis along a metaphorical path that submerged into the depths of ignorance as forced behavior. Finally, it digs out that regression, repression, and rationalization are some of these defense mechanisms that govern the unconscious of these people which finds an expression through their conscious actions. The study ends up with a concise conclusion, followed by the list of references.

Punishment extraction from Dutch criminal cases in courts of first instance

This paper explores the merits of a pattern- and rule-based approach for the automated extraction of punishments from Dutch criminal cases in courts of first instance. Automated extraction of case outcomes leverages the increasing amount of information becoming available through digital technologies and aids the creation of big data sets for work in legal informatics and AI & Law. This work addresses domain-specific challenges, in particular that Dutch criminal case decisions may impose a single combined sentence for multiple facts or impose multiple sentences in the same decision. Manual evaluation of the developed method shows that the use of interpretable methods is a viable approach in the legal domain.

Efficient Multi-hop Question Generation

Question generation is the parallel task of question answering, where given an input context and optionally, an answer, the goal is to generate a relevant and fluent natural language question. Although recent works on question generation have experienced success by utilizing sequence-to-sequence models, there is a need for question generation models to handle increasingly complex input contexts with the goal of producing increasingly elaborate questions. Multi-hop question generation is a more challenging task that aims to generate questions by connecting multiple facts from multiple input contexts. In this work we apply a transformer model to the task of multi-hop question generation, without utilizing any sentence-level supporting fact information. We utilize concepts that have proven effective in single-hop question generation, including a copy mechanism and placeholder tokens. We evaluate our model's performance on the HotpotQA dataset using automated evaluation metrics and human evaluation, and show an improvement over the previous works.

The Influence of Soviet Religious Policy on the Orthodox Communities in Western Siberia in the Late 1940s — Early 1950s

Based on the documents of the State Archive of the Altai Republic, the State Archive of the Novosibirsk Region, the State Archive of the Russian Federation, the Historical Archive of the Omsk Region, the article examines the implementation of the confessional policy of the Soviet state in Western Siberia in the first post-war years. Since the end of 1947, the state’s confessional policy had been gradually changing, as a result of which the religious communities of the country were increasingly subjected to administrative pressure from the Soviet authorities. During the registration procedure, believers faced numerous difficulties due to the unwillingness of local authorities to have operating parishes on their territory. The Orthodox communities of Western Siberia were no exception. In the territory under consideration in 1948–1953, multiple facts of administrative harassment by regional authorities were recorded, which led to low church attendance and an increase in the number of religious rites performed by believers at home. Often religious communities were placed in conditions under which the further functioning of the parish became impossible. Therefore, believers were forced to stop using houses of prayers. In addition, in the late 1940s — early 1950s, the functioning of churches was influenced by the processes of migration of rural population to the city, as well as by social and socio-cultural transformations in Soviet villages, as a result of which the population tried to avoid public visits to religious sites. The above factors led to an increase in the activities of unregistered ministers of worship, around whom a permanent circle of believers was formed. This, in turn, provoked the emergence of a large number of illegally functioning religious groups whose activities could hardly be controlled by the Soviet authorities in Western Siberia.

Will peak talent arrive before peak oil or peak demand?: Exploring whether career choices of highly skilled workers will accelerate the transition to renewable energy

Peak oil and peak demand hypotheses have generated significant research attention as claims that identify and explain pathways to decarbonization, but perspectives from human capital have been less prominent. We outline a peak talent hypothesis based on the idea that current and future oil and gas talent – comprising managerial, professional, and technical positions requiring a university degree – are opting to leave fossil fuels for careers in renewable energy. This phenomenon responds to multiple facts and arguments relating to climate change and, in turn, may accelerate decarbonization trends by encouraging more rapid change in oil and gas firms toward investments in renewable energy as well as increasing the number of workers choosing to work for renewable energy firms. This labor mobility effect may increase the shift from oil and gas to renewable energy. We propose areas of research that focus on the decision-making and motivations of talented workers, the strategies of firms to attract and retain talent, and the academic degree programs that train talented workers. Consideration of peak talent also motivates a deeper analysis of labor in social science studies of energy.

Effect of nootropic dipeptide noopept on CA1 pyramidal neurons involves α7AChRs on interneurons in hippocampal slices from rat

Noopept (NP) is a proline-containing dipeptide with nootropic and neuroprotective properties. We have previously shown that NP significantly increased the frequency of spontaneous IPSCs in hippocampal CA1 pyramidal cells mediated by the activation of inhibitory interneurons in stratum radiatum. The cholinergic system plays an important role in the performance of cognitive functions, furthermore multiple behavioral and clinical facts link NP with the cholinergic system. The present study was undertaken to reveal the possible interaction of NP with neuronal nicotinic acetylcholine receptors (nAChRs). Currents were recorded from rat hippocampal neurons using the whole-cell, patch-clamp technique. NP (5 µM) increased the action potential firing frequency recorded from GABAergic interneurons in the stratum radiatum (SR) of CA1 region. This effect was almost completely abolished by the application of the α7 nAChR-selective antagonists α-bungarotoxin (α-BGT; 6 nM) and methyllycaconitine (MLA; 20 nM). The increase in the frequency of spontaneous IPSCs in CA1 pyramidal cells induced by NP was also eliminated by α7 nAChRs antagonists. These results imply the involvement of α7 nAChRs in the modulation of hippocampal neuronal activity caused by NP and indicate that a7 nAChRs are an important site of action of NP.