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Purpose: Lean Manufacturing is widely regarded as a potential methodology to improve productivity and decrease costs in manufacturing organisations. The success of lean manufacturing demands consistent and conscious efforts from the organisation, and has to overcome several hindrances. Industry 4.0 makes a factory smart by applying advanced information and communication systems and future-oriented technologies. This paper analyses the incompletely perceived link between Industry 4.0 and lean manufacturing, and investigates whether Industry 4.0 is capable of implementing lean. Executing Industry 4.0 is a cost-intensive operation, and is met with reluctance from several manufacturers. This research also provides an important insight into manufacturers’ dilemma as to whether they can commit into Industry 4.0, considering the investment required and unperceived benefits. Design/methodology/approach: Lean manufacturing is first defined and different dimensions of lean are presented. Then Industry 4.0 is defined followed by representing its current status in Germany. The barriers for implementation of lean are analysed from the perspective of integration of resources. Literatures associated with Industry 4.0 are studied and suitable solution principles are identified to solve the above mentioned barriers of implementing lean. Findings: It is identified that researches and publications in the field of Industry 4.0 held answers to overcome the barriers of implementation of lean manufacturing. These potential solution principles prove the hypothesis that Industry 4.0 is indeed capable of implementing lean. It uncovers the fact that committing into Industry 4.0 makes a factory lean besides being smart. Originality/value: Individual researches have been done in various technologies allied with Industry 4.0, but the potential to execute lean manufacturing was not completely perceived. This paper bridges the gap between these two realms, and identifies exactly which aspects of Industry 4.0 contribute towards respective dimensions of lean manufacturing.

This dissertation focuses on several questions. How should we demarcate our concepts of cognitive endorsements (where “cognitive endorsements” include belief, acceptance, supposition, presupposition, and hypothesizing)? Are cognitive endorsements inherently normative states? Finally, how do cognitive endorsements factor into rationality and understanding?In addressing these questions, I argue for several theses. I first show that belief, acceptance, supposition, presupposition, and hypothesizing are unique cognitive endorsements with distinct features concerning (i) their conceptual links to the truth, (ii) their rational basis, and (iii) their connection to an agent’s will. Second, I argue that consciously formed cognitive endorsements engender distinct cognitive commitments that normatively constrain how one ought to treat the target propositions of these states. Third, I defend the view that diachronic belief-formation is governed by semantic commitments. Semantic commitments are normative constraints to form new beliefs depending on one’s current beliefs, cognitive abilities, conceptual resources, and the logical relations that hold between propositions and the contents of one’s current beliefs. Fourth, I argue that these commitments factor into rationality. More precisely, I defend a view called, “Robust Rationality.” On this view, epistemic rationality consists of external, mind-independent rules and internal, mind-dependent doxastic commitments that govern beliefs. Finally, I argue that rational cognitive endorsements can facilitate cognitive achievements of understanding. Understanding, I contend, comes in different species: veridical understanding, conjectural understanding, and narrative understanding. The type of understanding an agent possesses will depend on the underlying cognitive endorsement and the degree and quality of the relevant rational support.This project has important consequences for epistemology and philosophy of mind. It establishes a taxonomy of cognitive endorsements and their conditions of rationality. This taxonomy can be employed for theoretical work mapping the plurality of ways rational agents can endorse and employ propositions in thought. Second, it is shown that both acceptance and supposition play an important role in manifesting rational agency and shaping our epistemic lives. Third, this project illuminates the normative structure of our thinking, reasoning, and processes of inquiry. For it shows that our cognitive endorsements are inherently normative states. Furthermore, this project advances our understanding of epistemic rationality and understanding.

4 ESEA placed few restrictions on the use of Title I funding, allowing, but not requiring, schools to use it to implement supplemental services that addressed students' needs, such as medical and dental services, parental counseling services, and meal plans.5 While the statute allowed these services and even encouraged them, studies demonstrated that schools rarely implemented programs only tangentially related to education and that the achievement gap between lowincome and middle-income children did not improve.6 Beginning with the Brown v. Board of Education decision in 1954, society addressed education from an equity perspective, asking whether students were receiving an equal education.7 After the San Antonio Independent School District v. Rodriguez decision, the paradigm began to shift to an adequacy perspective, whereby the central focus became whether or not every child received an adequate education.8 Understanding the sufficiency of one's education as adequate, however, means only that the education meets some minimal standard and does not breach the issue of an achievement gap.9 During the 1980's and 1990's, the trend toward adequacy continued in the form of standardsbased reform with the passage of NCLB.10 III. First and foremost, several states and critics complain that the federal funding under Title I is not sufficient to cover the cost of the statute's requirements.21 While the statute allows the implementation of comprehensive poverty-related programming in schools,22 the money only sometimes covers the cost of administering the standardized tests that are the primary focus of the legislation.23 Some criticize the statute because it discourages higher quality teachers from teaching at lower-performing schools.24 Teachers will want to teach in schools that offer them both a steady job and a degree of autonomy over what and how they teach.25 Under NCLB, sanctioned schools are burdened with restructuring, which can include changing staff and faculty.26 Higher quality teachers that have tiieir choice of schools will tend to accept fewer jobs from schools that are in danger of a faculty overhaul.

My commitment has long been to the construction and exhibition of art that help correct the imbalance of power that exists in our society. The works titled Part of Something Bigger is a grouping of Small political prints used to construct instillations that convey overwhelming problems that we are constantly reminded of through advertisement and social media. The small prints are also collaged together to create deeper conversations about the complexity of the issues. These prints show a large range of issues plaguing society and how these issues often overlap and block out each other sometimes competing for attention; while still showing the history and long-term fights that have raged alongside them. Printmaking has tremendous power to move people towards social change with its long history as a voice for the people. As a medium for social awareness it has the ability to challenge and confront the biggest issues of our time in how it promotes an equal and balanced society, in which people are accountable for their own actions. This drew me to printmaking and its ability to reach a larger audience, as an art form historically for the masses. My work is democratic in nature, in that it's affordable and meant to be seen in public spaces; places where large groups gather. This work is meant to shines a light on the darker sides of society; art that challenges the \"so called normal\" social world and enacting meaningful change by have viewers to confront their own biases and opinions on social topics. It promotes a large range of outcomes—healing, increased awareness, attitudinal change, more diverse thinking and increased civic participation, it could be called movement building, but the works exists primarily to promote the asking of the questions.

Though many representations of Appalachian religious practices describe conservative, stagnant, xenophobic, and backward traditions, some authors present Christian practices in Appalachia as a potential source of social and individual progressiveness. Denise Giardina in Storming Heaven and The Unquiet Earth, Jim Wayne Miller in “Brier Sermon: ‘You Must Be Born Again,’” and Lee Smith in Fair and Tender Ladies all represent “mountain religion” practices that offer relevancy not only to the characters in the novel, but also to the reader. Analysis of these works through their symbolic representations of uniquely Appalachian religious traditions reveals the authors' commitment to sacralizing social and individual struggle through the sacred and mimetic transformations of characters and communities. By reusing and reinterpreting sacred patterns, both biblical and more contemporary regional patterns, the authors associate their works with sacred and regional traditions, demonstrating the viability, the flexibility, and the vitality of regional religious practices.

Reducing the computational cost of running large scale neural networks using sparsity has attracted great attention in the deep learning community. While much success has been achieved in reducing FLOP and parameter counts while maintaining acceptable task performance, achieving actual speed improvements has typically been much more difficult, particularly on general purpose accelerators (GPAs) such as NVIDIA GPUs using low precision number formats. In this work we introduce PopSparse, a library that enables fast sparse operations on Graphcore IPUs by leveraging both the unique hardware characteristics of IPUs as well as any block structure defined in the data. We target two different types of sparsity: static, where the sparsity pattern is fixed at compile-time; and dynamic, where it can change each time the model is run. We present benchmark results for matrix multiplication for both of these modes on IPU with a range of block sizes, matrix sizes and densities. Results indicate that the PopSparse implementations are faster than dense matrix multiplications on IPU at a range of sparsity levels with large matrix size and block size. Furthermore, static sparsity in general outperforms dynamic sparsity. While previous work on GPAs has shown speedups only for very high sparsity (typically 99\\% and above), the present work demonstrates that our static sparse implementation outperforms equivalent dense calculations in FP16 at lower sparsity (around 90%). IPU code is available to view and run at ipu.dev/sparsity-benchmarks, GPU code will be made available shortly.

We present GPS++, a hybrid Message Passing Neural Network / Graph Transformer model for molecular property prediction. Our model integrates a well-tuned local message passing component and biased global attention with other key ideas from prior literature to achieve state-of-the-art results on large-scale molecular dataset PCQM4Mv2. Through a thorough ablation study we highlight the impact of individual components and find that nearly all of the model's performance can be maintained without any use of global self-attention, showing that message passing is still a competitive approach for 3D molecular property prediction despite the recent dominance of graph transformers. We also find that our approach is significantly more accurate than prior art when 3D positional information is not available.

This technical report presents GPS++, the first-place solution to the Open Graph Benchmark Large-Scale Challenge (OGB-LSC 2022) for the PCQM4Mv2 molecular property prediction task. Our approach implements several key principles from the prior literature. At its core our GPS++ method is a hybrid MPNN/Transformer model that incorporates 3D atom positions and an auxiliary denoising task. The effectiveness of GPS++ is demonstrated by achieving 0.0719 mean absolute error on the independent test-challenge PCQM4Mv2 split. Thanks to Graphcore IPU acceleration, GPS++ scales to deep architectures (16 layers), training at 3 minutes per epoch, and large ensemble (112 models), completing the final predictions in 1 hour 32 minutes, well under the 4 hour inference budget allocated. Our implementation is publicly available at: https://github.com/graphcore/ogb-lsc-pcqm4mv2.

A communication system for communicating over high-latency, low bandwidth networks includes a communications processor configured to receive a collection of data from a local system, and a transceiver in communication with the communications processor. The transceiver is configured to transmit and receive data over a network according to a plurality of communication parameters. The communications processor is configured to divide the collection of data into a plurality of data streams; assign a priority level to each of the respective data streams, where the priority level reflects the criticality of the respective data stream; and modify a communication parameter of at least one of the plurality of data streams according to the priority of the at least one data stream.