RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

A marketing plan for smart bengali idiomatic proverb serv

Trabalho de projecto apresentado como requisito parcial para a obtenção do grau de Mestre em Gestão de Informação, especialização em Inteligência de MarketingBengali is one of the most verbal communications, graded seventh in the globe bearing in mind the situation of the country. This paper offers an online model for smart Bengali Idiomatic proverb service as well as intelligence marketing plan for revenue. In present circumstances Google translator service is not respectable, specially proverb translator because Google is not tranquil interpreted Bengali proverb precisely and nobody has planned to provide Bengali Idiomatic proverb service that will bring revenue. Now a day’s information is actual significant for real decisions making. The information can be gained from several bases and can able to use different kinds of tools for effective decision making. Marketing Intelligence is a new topic in marketing, there are not several possessions in works. The marketing plans by using information system sustained from marketing intelligence. Kotler's definition says, Intelligence Scheme of marketing is more than a scheme of information gathering or a set of information technologies. Software marketing make vital tactical decisions to exploit profits and success of the business (Öztürk, S., Okumuş, A., & Mutlu, F. 2012). As a result, the proposed project aims to improve online Bengali Idiomatic Proverb Service Model for service of excellence as well as create a business model canvas with marketing plan to observe current market situation of proposed service model that will forecast sales of profit. Therefore, the proposed research has used technological model to get good decision for marketing plan. Good decision assists to increase high number of productivity and profitability because computerized systems which assist the marketing decision to improve marketing plan (Dragomir, C., & Surugiu, F. 2015). In this case, the proposed project has chosen four different types of steps. There are Bengali Idiomatic Proverb Service Model, Online payment model, Business Model Canvas with Marketing plan. The propose project has used visual studio.net, HTML, CSS, nine building blocks for Business model canvas and kotler’s and keller’s marketing plan to develop a model for Bengali Idiomatic proverb service

Text Line Segmentation of Historical Documents: a Survey

There is a huge amount of historical documents in libraries and in various National Archives that have not been exploited electronically. Although automatic reading of complete pages remains, in most cases, a long-term objective, tasks such as word spotting, text/image alignment, authentication and extraction of specific fields are in use today. For all these tasks, a major step is document segmentation into text lines. Because of the low quality and the complexity of these documents (background noise, artifacts due to aging, interfering lines),automatic text line segmentation remains an open research field. The objective of this paper is to present a survey of existing methods, developed during the last decade, and dedicated to documents of historical interest.Comment: 25 pages, submitted version, To appear in International Journal on Document Analysis and Recognition, On line version available at http://www.springerlink.com/content/k2813176280456k3

Hindi language text search: a literature review

The literature review focuses on the major problems of Hindi text searching over the web. The review reveals the availability of a number of techniques and search engines that have been developed to facilitate Hindi text searching. Among many problems, a dominant one is when a text formed by combinatorial characters or words is searched

Example based English to Bengali machine translation

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2008.Cataloged from PDF version of thesis report.Includes bibliographical references (page 31).In this thesis we propose a new architecture for example based English to Bengali machine translation. The proposed Example Based Machine Translation (EBMT) system has five steps: 1) Tagging 2) Parsing 3) Prepare the chunks of the sentence using sub-sentential EBMT 4) Using an efficient adapting scheme match the sentence rule 5) Translate from English to Bengali in the chunk and generate output with morphological analysis. We prepared our tag set for tagging the English sentence. Here we proposed an optimal adapting scheme for choosing sentence rule from the knowledge base of the EBMT system. Our current system can translate simple sentences. We also defined a way to translate a complex sentence using sub-sentential EBMT. As this system can add more rules in the knowledge base, eventually it can be use for general purpose English to Bengali machine translation.Khan Md. Anwarus SalamB. Computer Science and Engineering

低資源言語としてのベンガル語に対するオントロジーに基づく機械翻訳

In this research we propose ontology based Machine Translation with the help of WordNetand UNL Ontology. Example-Based Machine Translation (EBMT) for low resource language,like Bengali, has low-coverage issues. Due to the lack of parallel corpus, it has highprobability of handling unknown words. We have implemented an EBMT system for lowresourcelanguage pair. The EBMT architecture use chunk-string templates (CSTs) andunknown word translation mechanism. CSTs consist of a chunk in source-language, a stringin target-language, and word alignment information. CSTs are prepared automatically fromaligned parallel corpus and WordNet by using English chunker. For unknown wordtranslation, we used WordNet hypernym tree and English-Bengali dictionary. Proposedsystem first tries to find semantically related English words from WordNet for the unknownword. From these related words, we choose the semantically closest related word whoseBangla translation exists in English-Bangla dictionary. If no Bangla translation exists, thesystem uses IPA-based-transliteration. For proper nouns, the system uses Akkhortransliteration mechanism. CSTs improved the wide-coverage by 57 points and quality by48.81 points in human evaluation. Currently 64.29% of the test-set translations by the systemwere acceptable. The combined solutions of CSTs and unknown words generated 67.85%acceptable translations from the test-set. Unknown words mechanism improved translationquality by 3.56 points in human evaluation. This research also proposed the way to autogenerate the explanation of each concept using the semantic backgrounds provided by UNLOntology. These explanations are useful for improving translation quality of unknown words.Ontology Based Machine Translation for Bengali as Low-resource Language.本研究では、WordNet と UNL オントロジーを用いた、オントロジーに基づく機械翻訳を提案する。ベンガル語のような低資源言語 (low-resource language)に対しては、具体例に基づく機械翻訳 (EBMT)は、あまり有効ではない。パラレル・コーパスの欠如のために、多数の未知語を扱わなければならなくなるためである。我々は、低資源言語間の EBMT システムを実装した。実装したEBMT アーキテクチャでは、chunk-string templates (CSTs)と、未知語翻訳メカニズムを用いている。CST は、起点言語のチャンク、目的言語の文字列と、単語アラメント情報から成る。CST は、英語チャンカーを用いて、アラインメント済みのパラレル・コーパスとWordNet から、自動的に生成される。最初に、起点言語のチャンクが OpenNLP チャンカーを用いて自動生成される。そして、初期CST が、各起点言語のチャンクに対して生成され、すべての目的文に対するCSTアラインメントがパラレル・コーパスを用いて生成される。その後、システムは、単語アラインメント情報を用いて、CSTの組合せを生成する。最後に、WordNet を用いて、広い適用範囲を得るためにCST を一般化する。未知語翻訳に対しては、WordNet hypernym treeと、英語・ベンガル語辞書を用いる。提案システムは、最初に、未知語に対して、WordNet から意味的に関連した英単語を発見しようと試みる。これらの関連語から、英語・ベンガル語辞書にベンガル語の翻訳が存在する、意味的に最も近い語を選ぶ。もし、ベンガル語の翻訳が存在しなければ、システムはIPA-based翻訳を行う。固有名詞に対しては、システムは、Akkhor 翻訳メカニズムを用いる。CST は57 ポイントの広い適用範囲を持つように改善され、その際の人間による訳文の評価も 48.81 ポイントを得た。現在、システムのよって、64.29%のテストケースの翻訳が行える。未知語メカニズムは、人間に評価において 3.56 ポイント、翻訳の質を改善した。CST と未知語の組合せよる解法は、テストケースにおいて、67.85%の許容可能な翻訳を生成した。また、本研究では、UNL オントロジーが提供するsemantic background を用いて、各概念に対する説明を自動生成する方法も提案した。このシステムに対する入力は、１つのユニバーサル・ワード(UN)であり、システムの出力はその UN の英語や日本語による説明文である。与えられたUN に対して、システムは、最初に、SemanticWordMap を発見するが、それは、１つの特定のUN に対する、UNL オントロジーからのすべての直接的、間接的参照関係を含む。したがって、このステップの入力は、１つのUN であり、出力はWordMapグラフである。次のステップで、変換規則を用いて、WordMap グラフをUNL に変換する。この変換規則は、ユーザの要求に応じて、“From UWs only”や “From UNL Ontology”と指定できる。したがって、このステップの入力はWordMap グラフであり、出力はUNL表現である。最終ステップでは、UNL DeConverter を用いてUNL 表現を変換し、自然言語を用いて記述する。これらの表現は、未知語に対する翻訳の質の向上に有効であることがわかった。電気通信大学201

Word Searching in Scene Image and Video Frame in Multi-Script Scenario using Dynamic Shape Coding

Retrieval of text information from natural scene images and video frames is a challenging task due to its inherent problems like complex character shapes, low resolution, background noise, etc. Available OCR systems often fail to retrieve such information in scene/video frames. Keyword spotting, an alternative way to retrieve information, performs efficient text searching in such scenarios. However, current word spotting techniques in scene/video images are script-specific and they are mainly developed for Latin script. This paper presents a novel word spotting framework using dynamic shape coding for text retrieval in natural scene image and video frames. The framework is designed to search query keyword from multiple scripts with the help of on-the-fly script-wise keyword generation for the corresponding script. We have used a two-stage word spotting approach using Hidden Markov Model (HMM) to detect the translated keyword in a given text line by identifying the script of the line. A novel unsupervised dynamic shape coding based scheme has been used to group similar shape characters to avoid confusion and to improve text alignment. Next, the hypotheses locations are verified to improve retrieval performance. To evaluate the proposed system for searching keyword from natural scene image and video frames, we have considered two popular Indic scripts such as Bangla (Bengali) and Devanagari along with English. Inspired by the zone-wise recognition approach in Indic scripts[1], zone-wise text information has been used to improve the traditional word spotting performance in Indic scripts. For our experiment, a dataset consisting of images of different scenes and video frames of English, Bangla and Devanagari scripts were considered. The results obtained showed the effectiveness of our proposed word spotting approach.Comment: Multimedia Tools and Applications, Springe