Gap Problem Research Articles

The foundations of spectral computations via the Solvability Complexity Index hierarchy

The problem of computing spectra of operators is arguably one of the most investigated areas of computational mathematics. However, the problem of computing spectra of general bounded infinite matrices has only recently been solved. We establish some of the foundations of computational spectral theory through the Solvability Complexity Index (SCI) hierarchy, an approach closely related to Smale’s program on the foundations of computational mathematics and McMullen’s results on polynomial root finding with rational maps. Infinite-dimensional problems yield an intricate infinite classification theory, determining which spectral problems can be solved and with what types of algorithms. We provide answers to many longstanding open questions on the existence of algorithms. For example, we show that spectra can be computed, with error control, from point sampling operator coefficients for large classes of partial differential operators on unbounded domains. Further results include: computing spectra of (possibly unbounded) operators on graphs and separable Hilbert spaces with error control; determining if the spectrum intersects a compact set; the computational spectral gap problem and computing spectral classifications at the bottom of the spectrum; and computing discrete spectra, multiplicities, eigenspaces and determining if the discrete spectrum is non-empty. Moreover, the positive results with error control can be used in computer-assisted proofs. In contrast, the negative results preclude computer-assisted proofs for classes of operators as a whole. Our proofs are constructive, yielding a library of new algorithms and techniques that handle problems that before were out of reach. We demonstrate these algorithms on challenging problems, giving concrete examples of the failure of traditional approaches (e.g., “spectral pollution”) compared to the introduced techniques.

Impacts of polarizable continuum models on the SCF convergence and DFT delocalization error of large molecules.

Advances in algorithm developments have enabled density functional theory (DFT) description of large molecules, including whole proteins, but the self-consistent field (SCF) convergence issues often hamper practical applications. The conductor-like polarizable continuum model (CPCM), although initially introduced as an implicit solvent model, was reported to improve SCF convergence in some large molecules. However, the underlying mechanisms and applicable use cases were unclear. We investigated the impacts of CPCM on the SCF convergence of 25 peptides and found that the CPCM only effectively reduced the SCF iterations for molecules with charge separations (e.g., the zwitterionic form of peptides) but had little effect on non-charge-separated molecules. We observed that CPCM increased the HOMO-LUMO gap of both the zwitterionic and non-charge-separated molecules, but only the charge-separated molecules suffered from the vanishing HOMO-LUMO gap problem in the gas phase, which is the origin of the convergence issue. We revealed CPCM's gap-opening mechanism as the selective stabilization/destabilization of molecular orbitals (MOs) based on their local electrostatic environment. Compared to level-shifting, a traditional SCF improvement technique, CPCM has superior performance because the stabilization/destabilization of MOs is consistent through SCF iterations. Finally, we examined CPCM's impacts on DFT density delocalization error (DDE) when used as an SCF accelerator. CPCM can mitigate the DDE and reproduce the density-derived properties (e.g., dipole moments) matching high-level methods when a very low dielectric constant is used but tends to over-localize the electron density at higher dielectric constants.

The capital logic of platform economy globalisation and it’s critique and transcendence

PurposeTo realise the shared development of the digital economy, people need to transcend the capital logic and advocate the logic of cooperative development, i.e. “co-construction, benefit-sharing and co-governance”. This study aims to discuss the aforementioned statement.Design/methodology/approachPlatform economy is a new economic form produced by the transformation of the social production patterns in the era of digital capitalism. In the neo-imperialist stage, a new stage of capitalist development, capital logic promotes the global expansion of the platform economy and influences its development process, organisational form, contradictions and dilemmas and internal transcendence. Having the spatiotemporal chain of capital circulation repaired, the globalisation of the platform economy is reshaping how the means of production are combined with labour, affecting the local changes in the general relations of production and “international relations of production”.FindingsIn the accumulation of digital capitalism, the social contradictions and fundamental contradictions in the capitalist world have been further intensified, making exploitation, income distribution gap, monopoly and other problems increasingly severe. The imbalance and inequality in the global development of the digital economy are increasingly prominent.Originality/valueRegarding the global governance of the digital economy, China, as a major responsible country, will strive to encourage all countries to co-build a community with a shared future in cyberspace. In the new international development pattern of digital economy globalisation, China must take effective measures to actively safeguard its national security and development interests to meet specific challenges.

Zero-Shot Learning via Structure-Aligned Generative Adversarial Network.

In this article, we propose a structure-aligned generative adversarial network framework to improve zero-shot learning (ZSL) by mitigating the semantic gap, domain shift, and hubness problem. The proposed framework contains two parts, i.e., a generative adversarial network with a softmax classifier part, and a structure-aligned part. In the first part, the generative adversarial network aims at generating pseudovisual features through the guiding generator and discriminator play the minimax two-player game together. At the same time, the softmax classifier is committed to increasing the interclass distance and reducing intraclass distance. Then, the harmful effect of domain shift and hubness problems can be mitigated. In another part, we introduce a structure-aligned module where the structural consistency between visual space and semantic space is learned. By aligning the structure between visual space and semantic space, the semantic gap between them can be bridged. The performance of classification is improved when the structure-aligned visual-semantic embedding space is transferred to the unseen classes. Our framework reformulates the ZSL as a standard fully supervised classification task using the pseudovisual features of unseen classes. Extensive experiments conducted on five benchmark data sets demonstrate that the proposed framework significantly outperforms state-of-the-art methods in both conventional and generalized settings.

DLnet With Training Task Conversion Stream for Precise Semantic Segmentation in Actual Traffic Scene.

Many successful semantic segmentation models trained on certain datasets experience a performance gap when they are applied to the actual scene images, expressing weak robustness of these models in the actual scene. The training task conversion (TTC) and domain adaption field have been originally proposed to solve the performance gap problem. Unfortunately, many existing models for TTC and domain adaptation have defects, and even if the TTC is completed, the performance is far from the original task model. Thus, how to maintain excellent performance while completing TTC is the main challenge. In order to address this challenge, a deep learning model named DLnet is proposed for TTC from the existing image dataset-based training task to the actual scene image-based training task. The proposed network, named the DLnet, contains three main innovations. The proposed network is verified by experiments. The experimental results show that the proposed DLnet not only can achieve state-of-the-art quantitative performance on four popular datasets but also can obtain outstanding qualitative performance in four actual urban scenes, which demonstrates the robustness and performance of the proposed DLnet. In addition, although the proposed DLnet cannot achieve outstanding performance in real time, it can still achieve a moderate performance in real time, which is within an acceptable range.

STRATEGI PENINGKATAN KUALITAS PELAYANAN UNTUK KEPUASAN PELANGGAN DENGAN INTEGRASI METODE SERVQUAL, QFD DAN TOPSIS

Minimarket "X" is a business engaged in retail sales of daily necessities. In providing services there are complaints that occur in October of 11.06%, November of 12.52% and December of 13.27% in 2021. Complaints that make customers feel dissatisfied are price suitability, availability of empty products, price tag, parking space and employee friendliness. The purpose of this study is to make customers feel satisfied when shopping by improving service quality. In this study using the SERVQUAL method of calculation to determine the level of customer satisfaction and gap problems that occur. The QFD method is used in planning, service development and evaluating service performance as well as integrating with the TOPSIS method to rank each alternative solution. Based on the results of research conducted from the SERVQUAL method, there are 9 service attributes from Minimarket "X" that have met customer expectations and 21 service attributes require improvement. So that the improvement of service quality using the QFD method obtained 11 technical responses for improvement and using the TOPSIS method, priority was obtained on the technical response that would be used as a policy in developing services by taking into account 5 criteria, namely, budget (C1), policy suitability with customer needs (C2), accessibility of implementation policy (C3), enthusiasm in policy implementation (C4), capability towards policy implementation (C5). So that the results of the integration of service quality improvement indicate the priority of service policies that must be carried out first, namely the policy of providing services in accordance with procedures. Keywords: Service, Satisfaction, SERVQUAL, QFD, TOPSIS

Generational Inclusion: Getting Older Adults Ready to Own Safe Online Identities

This article presents an initiative that addresses the problem of the digital literacy generational gap, targeting older adults that struggle to integrate the digital world and are unaware of the dangers of the online environment. The article has a European scope but with a special attention to the Portuguese context. The methodological approach started with a theoretical research on digital and online literacy of adults, followed by the design of an innovative training program specifically designed for this target group and finished with the results of the evaluation of the impact of the training. The overall conclusion, based on the achieved results, leads us to think that it is possible to improve the digital literacy of older adults so that they become effective online users while being alert to the dangers of the online world. Therefore, the work conducted is expected to contribute to a greater awareness of the importance and socio-economic possibilities that arise from the digital and technological investment for stimulating the integration of the older generation in the digital context.

BLACK BY GOD | The West Virginian

BLACK BY GOD | The West Virginian

Reinforcement Learning for Bipedal Gait with MAX-E2 Humanoid Robot

We consider the whole-body humanoid gait control model via reinforcement learning, where an initial predefined parametric gait policy is optimized by employing the augmented random search algorithm realizing most of the experiments in simulation and verifying the results onto the real robot. In our proposal, we take into account the reality gap problem, also known as Sim to real problem, for the development of the experiments and the policy guaranteeing functional results in the real robot employing a simplified custom simulator. We show that our proposed learning algorithm allows the humanoid robot MAX-E2 to walk efficiently in virtual and real environments.

Guest Editorial: UPSKILLING in a Lean Working Environment

_ A pervasive shortage of technical skills is costing the energy sector billions of dollars every year in lost value. One global oil and gas recruiting firm estimated last year that 41% of this skills shortage is due to lack of adequate education and training. So, why are operators struggling so much to acquire and retain a skilled workforce? There are several reasons, but two in particular stand out to us since they have recently emerged within the continuing education landscape. 1. The significant—and likely permanent—headcount reduction resulting from the pandemic. 2. Conditions where technical skill requirements are rapidly evolving due to the clean energy transition and net-zero initiative. The combination of these two new and indisputable realities has created an environment wherein, if left unchecked, the skills gap will almost certainly get worse. A seemingly obvious solution to the skills gap problem would be for energy companies to ramp up their investment in skill development and training. But this ignores the constraints energy producers currently face. For instance, despite current favorable economic conditions, investors remain supportive of the producers’ focus on increasing return on capital vs. increasing their general and administrative (G&A) budget. In addition to the pressure to drive cashflow, a more pressing constraint is time. When I ask upstream professionals whether they feel they are doing enough to upskill in their career, most say no. The reason is usually time, or lack thereof. Today’s positive economics combined with lean operations mean that time for training is extremely limited. Avenues for Learning Suppose the above conditions don’t change. Suppose we will continue to run lean as an industry, and as a result, time and budget for training will always be a problem. What can we do as an industry to reduce the skills gap? What are the available avenues for upskilling? The baseline option is to do nothing. In other words, we can learn by doing. To its credit, a great deal of technological advancement has resulted from this approach. The advantage of doing nothing is that learning will always take place on the job. It could be argued that this is also an efficient option since the learnings from the work are directly applicable to the work. However, this “do nothing” approach carries both cost and risk. Risk comes in the form of mistakes that could have been avoided with proper training. The associated costs can be high and include drilling into a depleted zone or a botched completion. The industry has many examples to draw on where neglecting knowledge- and experience-sharing has proven to be enormously inefficient and costly. An alternative is to insource all training. This is considered to be a low-cost avenue since it relies on using subject matter experts already within the company to teach other employees. Hence, existing stores of wisdom and company best practices can be disseminated with no additional investment.

A Study on the Dynamic Relationship between Wealth Gap and Economic Growth in China

Abstract With the economic globalization, the relationship among all countries has become more and more closed (this phenomenon is often called “global village”). The wealth also flows more freely than that of before in the world. Due to this, there is a better improvement in our everyday life. But it also raises many livelihood issues such as the wealth gap. At present, the wealth gap problem has become one of the biggest serious problems in each country, especially, in the developing countries. Because of this, quantities of scholars and economists spare no effects to explore the dynamic relationship between wealth gap and economic growth. In this, this paper sets China who is the biggest developing country in the world with bigger wealth gap as an example. The annual time series data from 1980 to 2016 is applied to analyze the dynamic operating mechanism between wealth gap and economic growth in China. All datum are sourced from the National Bureau of Statistics of the People’s Republic of China. Using the vector error correction model to conduct an empirical analysis, the dynamic operating mechanism between them will be fully understood. Then, the results of this empirical study will provide some ideas as reference for China’s government to settle the wealth gap.

The Role of The Supreme Audit Institutions in Counteracting VAT Gap in the European States. A Cross-Country Comparative Study

This study follows the research conducted so far on the multi-dimensional role of supreme audit institutions (SAIs) in strengthening social capital and improving the functioning of public organisations. It has been found that international organisations established by SAIs, should include the problem of the VAT gap in their audit strategies. In addition, they should tighten international cooperation, including training cooperation, considering that irregularities in VAT settlements occurring in all Member States of the European Union are favoured by the specific nature of intra-community transactions. Institutional weaknesses in tax collection prove the low potential of the state. Due to the lack of publicly available information, it has not been established whether the SAIs from the studied countries with the largest size of the VAT gap – Malta and Greece – analysed the reasons for its creation. SAIs from other countries – Great Britain, Germany, Romania and Italy analysed the reasons for the ineffective reduction of the VAT gap by national tax systems. However, there is no information about audits involving human resource management in tax offices. Meanwhile, this issue is crucial not only from the point of view of the effectiveness of tax prevention but, more broadly, to strengthen the social capital necessary to create an organisational domestic and international environment based on reliability that will bring tax accountability. The formulated directional proposals for examining the tax system in terms of the effectiveness of reducing the VAT gap, due to their universality, can be applied in various countries.

Exploiting an Intermediate Latent Space between Photo and Sketch for Face Photo-Sketch Recognition.

The photo-sketch matching problem is challenging because the modality gap between a photo and a sketch is very large. This work features a novel approach to the use of an intermediate latent space between the two modalities that circumvents the problem of modality gap for face photo-sketch recognition. To set up a stable homogenous latent space between a photo and a sketch that is effective for matching, we utilize a bidirectional (photo → sketch and sketch → photo) collaborative synthesis network and equip the latent space with rich representation power. To provide rich representation power, we employ StyleGAN architectures, such as StyleGAN and StyleGAN2. The proposed latent space equipped with rich representation power enables us to conduct accurate matching because we can effectively align the distributions of the two modalities in the latent space. In addition, to resolve the problem of insufficient paired photo/sketch samples for training, we introduce a three-step training scheme. Extensive evaluation on a public composite face sketch database confirms superior performance of the proposed approach compared to existing state-of-the-art methods. The proposed methodology can be employed in matching other modality pairs.

Gender Equality and Employment Regulation in the New Labour Years, 1997–2010: The Problem of the Gender Pay Gap

There has been little agreement about how to describe the forms of employment regulation adopted by New Labour governments from 1997 to 2010. It is often assumed that policy relating to women and employment falls under the broad heading of ‘partnership’ or ‘voluntary pluralism’. This rests on the view that female workers’ interests were articulated by trade unions and brought into the sphere of policy formulation through a process of dialogue via labour market organizations representing employers and employees; it also refers to the influence of European Union’s ‘social partnership’. The article instead views employment regulation during the New Labour years as hybridized, and subject to party management of unions. It argues that Labour could have done more to ‘call organized business’s bluff’ to strengthen work–family measures or equal-pay legislation. Its reluctance to do so led to missed opportunities for progressive social change, despite gains made by women within the Labour leadership circle and trade-unionists at key junctures.

Revisiting the dataset gap problem – On availability, assessment and perspective of mobile forensic corpora

Digital forensic corpora are essential for education, academic research, tool development and testing. Due to the increasing pervasiveness of mobile devices like smartphones or tablets, the need for mobile forensic datasets is growing, too. However, publications in the IT forensic community show that there is a large gap in publicly available datasets. In this work we focus on mobile digital forensic corpora as one of the main fields of missing datasets and aim at shifting the focus of the digital forensic community on this topic. In order to do so, we provide three main contributions. We first perform a structured search for mobile forensic corpora and show that 31 publicly available mobile forensic corpora exist, 9 of them more than 5 years old and 18 of them more than 3 years old. Second, we assess these datasets with respect to its content compared to an ordinary real mobile image and conclude that most of the 31 datasets contain too few traces to be considered as realistic. Finally, we propose how to proceed to solve the presumable problem of missing mobile forensic datasets.

Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic Segmentation

Semantic segmentation is a popular research topic in computer vision, and many efforts have been made on it with impressive results. In this paper, we intend to search an optimal network structure that can run in real-time for this problem. Towards this goal, we jointly search the depth, channel, dilation rate and feature spatial resolution, which results in a search space consisting of about \(2.78\times 10^{324}\) possible choices. To handle such a large search space, we leverage differential architecture search methods. However, the architecture parameters searched using existing differential methods need to be discretized, which causes the discretization gap between the architecture parameters found by the differential methods and their discretized version as the final solution for the architecture search. Hence, we relieve the problem of discretization gap from the innovative perspective of solution space regularization. Specifically, a novel Solution Space Regularization (SSR) loss is first proposed to effectively encourage the supernet to converge to its discrete one. Then, a new Hierarchical and Progressive Solution Space Shrinking method is presented to further achieve high efficiency of searching. In addition, we theoretically show that the optimization of SSR loss is equivalent to the \(L_{0}\)-norm regularization, which accounts for the improved search-evaluation gap. Comprehensive experiments show that the proposed search scheme can efficiently find an optimal network structure that yields an extremely fast speed (175 FPS) of segmentation with a small model size (1 M) while maintaining comparable accuracy.

Research on the measurement method of fuel feeding temperature during circulating fluidized bed boiler's start‐up

AbstractCirculating fluidized bed (CFB) boiler is a high‐efficiency and clean combustion technology that has been developed rapidly in recent years. During the start process, only after the furnace temperature is heated up with fuel oil higher than the fuel feeding temperature, fuel can be fed into it, otherwise, it will easily lead to deflagration accidents in the furnace. While adding fuel too late will increase the unnecessary cost of fuel oil. There are three main methods for measuring fuel feeding temperature in the CFB boiler. The thermogravimetric analysis‐derivative thermogravimetry (TG‐DTG method has the problem of a large gap between the measurement results and the actual boiler fuel feeding temperature. Although the measurement results in the CFB test rig are more accurate, its procedure is more complex and costly. The method of on‐site debugging and measurement has disadvantages such as high measurement cost and poor measurement repeatability. For this reason, this paper designs a simple method to measure fuel feeding temperature in CFB boiler, which has standard operability and lower test cost. The measurement results of variable fuel types were compared with the measurement results of the above three methods, which prove that the results of all samples are close to those in the actual CFB boiler with error within 40°C. It is confirmed that this method can accurately measure the CFB boiler fuel feeding temperature, which is of great significance to the operation of the CFB boiler.

The local matters: Working with teachers to rethink the poverty and achievement gap discourse

This paper is concerned with the current achievement gap policy agenda and associated material and discursive power that shape teachers’ work in schools with high child poverty rates. More specifically, it explores how a university/school research collaboration – Local Matters – can disturb such forms of subjectivation by enabling educators to resist such policy agendas/discourses by drawing on locally contextualized knowledge and place-based evidence. Based on fieldwork undertaken over the past three years at over forty schools with eighty-four teachers across five Local Authority regions in Northern England, we provide a critical discourse analysis of a series of semi structured interviews and focus group activities of those who participated in the project. Based on an interdiscursive and linguistic analysis of the data we show how educators wrestle with the tensions between attempting to enact a social justice, collaborative and a democratic pedagogic approach and dealing with policy requirements that focus on the achievement gap problem and associated ‘what works’ discourse solution. Through the enactment of the program we show how educators, in collaboration with activist researchers, can develop forms of principled resistance that shake up and unsettle dominant forms of child poverty practice and discourses in schools.

Teachers’ perceptions about collaboration as a strategy to address key concepts in mathematics

Background: The aim of the study is to investigate teachers’ perceptions about peer collaborative work in designing lessons as a team helped them to identify threshold concepts in the teaching and learning of foundation phase mathematics in Motheo District of Education.Methods: A qualitative approach, with a case study design, was used to combine data from observation and focus group discussions, interviews and group task sheets.Classroom observation was conducted during a workshop conducted by a subject advisor from the Motheo District of Education in collaboration with the researcher. Teachers were purposively selected from seven schools in the Motheo District of Education based on cluster sampling as a way of reviving their professional development through acquisition of mathematical teaching skills involving innovative approaches to teaching and learning of early childhood mathematics. Seven mathematics teachers, one from each school, were interviewed during the workshop.Results: Underpinned by a collaborative theory, the findings of the study revealed that peer collaboration in mathematics teaching was key to helping them (participant teachers) identify threshold concepts in mathematics that they had initially found difficult as individual teachers. This assisted them in teaching the subject effectively at the foundation phase level. The study, furthermore, established that collaboration by mathematics teachers was necessary in order to overcome the paucity of global mathematics teaching skills for early childhood mathematics, to foster learners’ knowledge of mathematical concepts and to stimulate their interest in the subject.Conclusion: It is recommended that more structured collaborative work amongst teachers in general should be encouraged to enable teachers overcome the problem of content gap in their area of specialisation.

Singlet-triplet energy gap of multiresonant molecular systems: A double hybrid time-dependent density functional theory study

Singlet–triplet energy gaps (ΔEST) for multiresonant molecular systems are investigated within time-dependent density functional theory (TDDFT), using conventional linear response TDDFT (LR-TDDFT) and double hybrid TDDFT (DH-TDDFT) schemes. LR-TDDFT methods systematically overestimate ΔEST; on the other hand, by explicitly taking double excitation characters into consideration, DH-TDDFT considerably improves the gap problem. Further theoretical analysis shows that DH-TDDFT calculations also work for the description of negative gap situations, which LR-TDDFT intrinsically fails. The present findings demonstrate the applicability of TDDFT-based methods for predicting ΔEST as a relatively low-cost computational approach, encouraging us to develop new exchange-correlation functionals suited for DH-TDDFT calculations.