Impact of Lighting Arrangements and Illuminances on Different Impressions of a Room

Cataloged from PDF version of article.This study explores whether different lighting arrangements (general lighting, wall washing and cove lighting) and different illuminances (500 and 320 lux) could affect the perception of the same space. An experimental study was conducted to investigate how the qualitative aspects of space (the impressions of a space) could be enhanced with lighting. Hundred participants were first asked to choose the most suitable lighting arrangement for each impression (clarity, spaciousness, relaxation, privacy, pleasantness and order) under the 500 lux illuminance. In the second stage, they were asked to compare the two illuminances (500 and 320 lux) for the lighting arrangement they selected in the first stage. There was a statistically significant relation between impressions and lighting arrangements, also between impressions and lighting levels. Thus, different lighting arrangements and lighting levels could be used to enhance the clarity, spaciousness, relaxation, privacy, pleasantness and order of a room. The results of this study found most suitable lighting arrangements with their illuminances for each impression, which is reported in the paper

Prevalence of dental caries in Hadrianapolis medieval population (X. century)

Dental caries has been one of the major oral health problems of the human race since the Stone Age. The skeletal remains were found during the archeological excavations in Hadrianapolis region by Edirne Museum between 2002 and 2003. These were linked to Eastern Roman-Byzantium period. Thirty-seven skeletal remains out of total 139 were studied. The aim of this study was to determine the number of teeth with cavities and the prevalence of dental caries in the skeletal remains of Hadrianapolis inhabitants from X. century using the DM(F)T index

Prevalence of dental caries in Hadrianapolis medieval population (X. century)

Dental caries has been one of the major oral health problems of the human race since the Stone Age. The skeletal remains were found during the archeological excavations in Hadrianapolis region by Edirne Museum between 2002 and 2003. These were linked to Eastern Roman-Byzantium period. Thirty-seven skeletal remains out of total 139 were studied. The aim of this study was to determine the number of teeth with cavities and the prevalence of dental caries in the skeletal remains of Hadrianapolis inhabitants from X. century using the DM(F)T index

Introducing ISO 9000 to the Kazakhstan Banking Industry:A Case Study

Banks in Kazakhstan have experienced a lengthy period of political stability and economic growth. Together with rational approach to banking and finance policy, this has helped to push Kazakhstan’s banking system to a higher level of development. It is now widely known that the Kazakh market is highly attractive to foreign investors. The scope for profits is growing, and country risk is comparatively low. As the Kazakh banks face a shortage of long-term funds and access to existing resources is influenced by political factors, capital drawn from the international markets will play a decisive role in their growth

Periodontal diseases in Antiquity

Periodontal disease has been one of the major oral health problems of the human race since the Stone Age. Many studies conducted on skeletal remains of populations from different time periods have established the presence of destructive periodontal diseases with alveolar bone loss and/or tooth loss. The aim of this review article is to present several studies, covering a wide range of time periods, localities and populations, that paint a picture of the severity and prevalence of historic periodontal conditions

Business Excellence in Kazakh Higher Education Institutions

The aim of this paper is to deepen and to encourage further research for sustaining quality improvement in Kazakh Higher Education Institutions. This paper is explaining the Kazakh education system and is also trying to figure out whether if it fits to the European Foundation for Quality Management (EFQM) excellence model. The paper is based on literature concerning the Kazakh Higher Education system.  The pros and cons are also mentioned in the paper. In accordance to this it is easier to find the strengths and weaknesses of the system and finally a list of factors are given in order to be a guide of excellence for the Kazakh Higher Education Institutes

Periodontal diseases in Antiquity

Periodontal disease has been one of the major oral health problems of the human race since the Stone Age. Many studies conducted on skeletal remains of populations from different time periods have established the presence of destructive periodontal diseases with alveolar bone loss and/or tooth loss. The aim of this review article is to present several studies, covering a wide range of time periods, localities and populations, that paint a picture of the severity and prevalence of historic periodontal conditions

Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks

Sign languages are multi-channel visual languages, where signers use a continuous 3D space to communicate.Sign Language Production (SLP), the automatic translation from spoken to sign languages, must embody both the continuous articulation and full morphology of sign to be truly understandable by the Deaf community. Previous deep learning-based SLP works have produced only a concatenation of isolated signs focusing primarily on the manual features, leading to a robotic and non-expressive production. In this work, we propose a novel Progressive Transformer architecture, the first SLP model to translate from spoken language sentences to continuous 3D multi-channel sign pose sequences in an end-to-end manner. Our transformer network architecture introduces a counter decoding that enables variable length continuous sequence generation by tracking the production progress over time and predicting the end of sequence. We present extensive data augmentation techniques to reduce prediction drift, alongside an adversarial training regime and a Mixture Density Network (MDN) formulation to produce realistic and expressive sign pose sequences. We propose a back translation evaluation mechanism for SLP, presenting benchmark quantitative results on the challenging PHOENIX14T dataset and setting baselines for future research. We further provide a user evaluation of our SLP model, to understand the Deaf reception of our sign pose productions

Adversarial Training for Multi-Channel Sign Language Production

Sign Languages are rich multi-channel languages, requiring articulation of both manual (hands) and non-manual (face and body) features in a precise, intricate manner. Sign Language Production (SLP), the automatic translation from spoken to sign languages, must embody this full sign morphology to be truly understandable by the Deaf community. Previous work has mainly focused on manual feature production, with an under-articulated output caused by regression to the mean. In this paper, we propose an Adversarial Multi-Channel approach to SLP. We frame sign production as a minimax game between a transformer-based Generator and a conditional Discriminator. Our adversarial discriminator evaluates the realism of sign production conditioned on the source text, pushing the generator towards a realistic and articulate output. Additionally, we fully encapsulate sign articulators with the inclusion of non-manual features, producing facial features and mouthing patterns. We evaluate on the challenging RWTH-PHOENIX-Weather-2014T (PHOENIX14T) dataset, and report state-of-the art SLP back-translation performance for manual production. We set new benchmarks for the production of multi-channel sign to underpin future research into realistic SLP

Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation

Automatic Sign Language Translation requires the integration of both computer vision and natural language processing to effectively bridge the communication gap between sign and spoken languages. However, the deficiency in large-scale training data to support sign language translation means we need to leverage resources from spoken language. We introduce, Sign2GPT, a novel framework for sign language translation that utilizes large-scale pretrained vision and language models via lightweight adapters for gloss-free sign language translation. The lightweight adapters are crucial for sign language translation, due to the constraints imposed by limited dataset sizes and the computational requirements when training with long sign videos. We also propose a novel pretraining strategy that directs our encoder to learn sign representations from automatically extracted pseudo-glosses without requiring gloss order information or annotations. We evaluate our approach on two public benchmark sign language translation datasets, namely RWTH-PHOENIX-Weather 2014T and CSL-Daily, and improve on state-of-the-art gloss-free translation performance with a significant margin.Comment: Accepted at ICLR202