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    • 5. 发明申请
    • A PROCESS FOR PRODUCING LIPIDS SUITABLE FOR BIOFUELS
    • 生产适用于生物饮料的脂肪的方法
    • WO2013054170A3
    • 2013-06-13
    • PCT/IB2012002016
    • 2012-10-11
    • INDIAN OIL CORP LTD
    • SINGH MAHENDRA PRATAPKUMAR MANOJSINGH DHEERTULI DEEPAK KUMARMALHOTRA RAVINDER KUMAR
    • C12N1/00
    • C12P7/649C10G2300/1014C10L1/02C10L1/026C11B1/04C11B1/10C11C3/003C12N1/12C12P7/64C12R1/89Y02E50/13Y02P30/20
    • The present invention provides a cost effective biotechnological process for production of bio-fuels from isolated and characterized microalgae. The algal strains used in the present invention having higher biomass, higher lipid productivity, higher pH and temperature tolerance are selected from the group consisting of Chlorella vulgaris iOC-1, Chlorella vulgaris iOC-2, Chlorella kessleri, Botrococcus bruni, Dunaliella salina and Nannochloris oculat or a combination thereof having 95-100% similarity with 18s ribosomal nucleic acids nucleotide sequences (rDNA) given for Seq. ID I, Seq. ID 2, Seq. ID 3, Seq. ID 4, Seq. ID 5 and Seq. ID 6. The present process of bio-fuel production comprises the steps of producing lipid from green algae in bioreactors by various novel steps and extracting oil from dried algal cells and ultimately producing biodiesel by transesterification of the said extracted oil.
    • 本发明提供了用于从分离和表征的微藻生产生物燃料的成本有效的生物技术方法。 具有较高生物量,较高脂质生产力,较高pH和温度耐受性的本发明中使用的藻类菌株选自小球藻iOC-1,寻常型小球藻iOC-2,小球藻,布鲁氏菌,杜氏盐藻和Nannochloris 眼睛或其组合与具有与Seq给出的18s核糖体核酸核苷酸序列(rDNA)具有95-100%相似性。 ID I,Seq。 ID 2,Seq。 ID 3,Seq。 ID 4,Seq。 ID 5和Seq。 本发明的生物燃料生产方法包括以下步骤:通过各种新的步骤从生物反应器中的绿藻生产脂质,并从干藻细胞中提取油,最终通过所述提取的油的酯交换生产生物柴油。
    • 8. 发明专利
    • AIML Based Smart Classifier in a Shared Memory Multiprocessor System
    • AU2021103444A4
    • 2022-05-05
    • AU2021103444
    • 2021-06-18
    • ARYA PRADEEPGUPTA SUNILSHREE TANUSINGH ARUNGUPTA PRATEEKPATTANAYAK HIMANSUKUMAR MANOJSHUKLA ANANDSINGH SATYENDRSHARMA SUNIL KUMARSAXENA SANDEEP
    • ARYA PRADEEPGUPTA SUNILSHREE TANUSINGH ARUNGUPTA PRATEEKPATTANAYAK HIMANSUKUMAR MANOJSHUKLA ANANDSINGH SATYENDRSHARMA SUNIL KUMARSAXENA SANDEEP
    • G06F9/54G06N20/00
    • AIML based Smart Classifier in a Shared Memory Multiprocessor System: Separating Data into their Corresponding Class using Biometric Dataset Machine Learning Classification Device. "AIML based Smart Classifier in a Shared Memory Multiprocessor System" is a system that is aimed at shifting the documentation of content through a biometric method and also includes instructions for receiving at least one labeled seed document. This technology receives unlabelled documents with at least one predetermined cost factor training a transductive classifier using the at least one predetermined cost factor, at least one seed document, and unlabelled documents and also classifies the unlabelled documents having a confidence level more than a set limit into several categories using the classifier. Re-categorizing at least some of the existing documents into the categories using the classifier and outputting identifiers to at least one of a user, another system, and another process. The system for separating documents is also shown. Systems and articles of manufacture for searching documents are shown alongside it. A method and system for creating a decision-tree classifier corresponding to a shared-memory multiprocessor system are revealed and the processors primarily create a list for each record attribute in the shared memory. Each attribute list is then allocated to a processor. The processors freely ascertain the best splits for their particular assigned lists, and compliantly find the best global split from all attribute lists. These lists are then allocated again to the processors and divided on the basis of the best global split into the lists for child nodes. Through this invention, the split attribute lists are allocated again to the processors and the process is continuously repeated for each new child node till the point when each attribute list for the new child nodes comprises tuples of a fixed number or from the same record class. This technology also develops new systems, methods, and software that enables an easier manual classification of headnotes and documents and complex headnotes and/or other required data. An excellent system offers a visual UI (user interface) that simultaneously showcases a random headnote of a ranked list of one or more candidate classes along with adjacent classes of the classification system. TOTAL NO OF SHEET: 03 NO OF FIG: 03 FIGI1ET E 1 LSIIATIO FULBLDDT NAREEN IHOEICRAINO H COTATO SN CLDCOST FACTOR: H OTO FO IGA