International Journal of Advances in Agricultural Science and Technology
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Agricultural Production and Development in Northeast Jilin Province of China
Get PDFThis paper presented the status of agricultural production, research efforts and developments in agriculturein China northeast province of Jilin. The province is a major agricultural province with rich farmingresources in China. Jilin province climate, soil and other natural conditions are conducive to quality cornproduction. Available statistics showed that through the years Jilin has ranked first in China in terms of totalmaize/corn output share, corn export volume and the amount of corn processed into other products. This isin addition to playing leading role in satisfying the food needs of the population
Agrotechnological Options for Upscaling Productivity of Underutilized Wetlands Under Impending Climate Change Situations: A Review
Get PDFThis review article scrutinizes some of the vibrant technologies developed/ refined/ adopted toimprove agricultural system productivity of underutilized wetlands/waterlogged/lowland areas inthe Eastern Indo Gangetic plains. Efficient agronomic research and technological developmentfor improving wetlands productivity in eastern region are the only options to feed our people, togenerate income and employments under this difficult situation. These tested and refinedtechnologies are not only capable of improving wetlands ecosystem productivity in a sustainablemanner but are equally efficient in minimizing the outbreak of insects and disease pests. Amongdifferent approaches for enhancing productivity of wetlands Makhana based cropping system isan efficient approach. Important agrotechnology developed and refined for Eastern Regionconditions are briefly discussed in this article
INTRUSION DETECTION SYSTEM WITH SUPERVISED LEARNING AND FEATURE SELECTION
Get PDFTwo machine learning techniques, namely SVM (Assist Vector Machine) and ANN (Artificial Neural Networks), are evaluated in this study for their efficiency. The presence or absence of regular or anomalous signatures in the request data will be determined using machine learning techniques. Internet intrusion detection systems (IDS) monitor request data and check if it contains typical or assault signatures; if it does, demand is reduced. This is necessary because nowadays all services are accessible online and malicious individuals can attack client or web server machines through this net. When new request signatures come, the IDS will be educated with all possible strikes signatures using AI techniques and then used to determine whether the new request comprises regular or assault trademarks. Here, we compare and contrast two AI algorithms, Support Vector Machines (SVM) and Artificial Neural Networks (ANN), and we find, experimentally, that ANN is more accurate than the current state-of-the-art SVM. Examining how well SVM and ANN work is the focus of this article. By utilising Relationship Based and Chi-Square Based function option formulas, the author has reduced the dataset dimension, eliminated irrelevant data, and loaded the model with important attributes. As a result of these features choice formulas, the dataset dimension will decrease and the forecast accuracy will increase
SOCIO -ECONOMIC FACTORS AND CONSTRAINTS INFLUENCING PRODUCTIVITY AMONG CASSAVA FARMERS IN TARABA STATE, NIGERIA
Get PDFThis study determined the socio-economic factors and problems influencing cassava production inTaraba state, Nigeria. Data were collected from 115 respondents using a structured questionnairecovering 2010/2011 farming season. The data were analyzed using descriptive However, cassavaproduction have some constraints, prominent among which are; inadequate finance accounting for50.43 %, unattractive price of cassava recording 24.3 %, and high cost of inputs, like fertilizer,herbicides, improved cassava cuttings accounting for 8.7 %. Others are labour shortage, inadequateextension agents, pests and disease infestation. The research recommended public private partnership(PPP) to sensitize and educate farmers to enable them benefit from the new innovations andtechnology that abound in the agricultural sector
Web Image Interpretation Using Graph Grammar
Get PDFWeb knowledge extraction becomes a hot topic once the invention of World Wide Web, as a result of the massivequantity of information on the online makes it difficult to retrieve helpful information. Thanks to the varied stylesand show of information on completely different websites, it’s onerous to implement a general idea to extractknowledge completely different websites. This paper presents a unique technique supported graph grammar to extract the constant sort of data from completely different Web sites without the requirement of coaching or adjustment. Our approach formalizes a standard Web pattern as a graph grammar. Then, based on the visual layout andHTML DOM structure, a Web page is abstracted as a spatial graph that highlights the essential spatial relationsbetween data objects. According to the defined graph grammar, a spatial parsing is performed on the spatial graphto extract structured records. We’ve evaluated our approach on twenty completely different Web sites, and achievedthe Final Score as 97.47% which shows promising performance
Effect of dietary coconut oil supplementation on some blood biochemical indices in yearling rams
Get PDFThe research set out to examine how adding coconut oil to the diet of yearling rams affected a number ofclinically significant biochemical variables in their blood. The experiment used nine male Blackhead Plevenyearling rams, with an average starting weight of 45.2 kg. A two-period experimental design was used. Thefirst group of yearling rams were given 1 kilogram of barley and 1 kg of grass hay (ration I) during the firstperiod. The second group got 0.800 kg of barley, 0.200 kg of sunflower meal, and 1 kg of grass hay (rationII). The third group also received 0.800 kg of barley, 0.200 kg of sunflower expeller, and 1 kg of grass hay(rating III). As part of the morning feeding routine throughout the trial, all groups received 0.02 kg ofcoconut oil via cannulas. Including coconut oil in ration II led to higher blood total and HDL cholesterol 2.5hours after consumption (p<0.001). Despite the increased rumen lipid content, serum triglyceride levels inanimals given Rations I and II were unaffected. Coconut oil significantly reduced blood ASAT activity inall three diets, both before and after feeding (p<0.05 and p<0.001, respectively). Animals given ration II hada reduction in serum alkaline phosphatase both before (p<0.001) and after feeding (p<0.05) after the additionof coconut oil. 
An efficient Machine Learning Techniques for Early Detection of Hearing Loss
Get PDFBy 2050, over 700 million people will have severe hearing loss. Audiologists and otolaryngologists are in shortsupply in underdeveloped and emerging countries, where a considerable part of the population suffers fromincapacitating hearing loss. Most hearing impairments are untreated for long periods of time due to a scarcity ofspecialists. In this study, we present automated hearing impairment diagnosis software based on machinelearning to help audiologists and otolaryngologists consistently and effectively identify and classify hearingloss.We discuss the architecture, implementation, and performance evaluation of the two-module automatedprogram for diagnosing hearing impairments: a machine learning model and a module for creating hearing testdata. To train and evaluate the machine learning model, the Data Acquisition Module generates a sizable andcomprehensive dataset. The kind, degree, and arrangement of hearing loss can be accurately predicted by themodel in real time using multiple classes and multi-label classification algorithms that learn from hearing testdata.With a log loss reduction rate of 98.48%, a prediction time of 634 ms, and macro and micro precisions of100%, our proposed machine learning model shows promise and can help audiologists and otolaryngologistsquickly and accurately classify the type, degree, and configuration of hearing loss
Securing Image Retrieval: A Blockchain-Based Encrypted Approach
Get PDFMalicious cloud servers can pose a hazard to encrypted picture retrieval, leading to incomplete or incorrect results.The majority of current systems do not verify the completeness of search results, instead concentrating on retrievalperformance and accuracy. We explore properties of blockchains including decentralization and tamper-proofing toachieve transparency and dependability in search results, and we suggest a blockchain-based encrypted pictureretrieval system. Using the blockchain consensus process and the smart contract's search function, this methodmaintains the encrypted index on the Ethereum blockchain, guarantees the accuracy and integrity of search results. Itthen uses a cloud server to host the corresponding encrypted images in order to save storage costs. Finally, it creates adouble-layer index structure by utilizing a simhash and a bag of visual word model in the image similarity indexprocess. Experiments demonstrate that the scheme's accuracy, high retrieval efficiency, and dependability also have apositive impact on privacy protection
A novel application for analysing customer revies using Blockchain
Get PDFConsumers can make informed purchase decisions and learn more about things by sharing their experiences withothers through user reviews. To enhance their business, internet retailers and service providers may modifycustomer evaluations by adding false positive remarks and removing negative ones. Customer reviews that havebeen edited may mislead customers and alter the original content of the reviews. Modern systems lack a safe,effective, and user-friendly consumer review system. In this work, we provide RevBloc, a highly efficient, secure,and easy-to-use customer review system. Because RevBloc is built on blockchain technology, user evaluationscan be maintained in a distributed ledger, preventing a single or small number of unfriendly parties frominfluencing the reviews. We implement a RevBloc proof-of-concept prototype and describe its performance toillustrate the strategy's practicality. 
NUTRITIONAL AND SENSORY IMPACT OF OAT MILK AND CARROT JUICE FORTIFICATION IN LOW-FAT VANILLA ICE CREAM
Get PDFIce cream, a popular frozen dessert, is constantly evolving to meet the demands of healthconscious consumers while maintaining its indulgent appeal. This study explores theformulation and quality evaluation of ice cream infused with oat milk and carrot juice,complemented by vanilla flavoring. Oat milk, known for its creamy texture and nutritionalbenefits, serves as a non-dairy alternative rich in fiber, vitamins, and minerals. Carrots,abundant in beta-carotene and antioxidants, are incorporated to enhance nutritional contentand introduce a unique flavor profile. The experimental design involves varyingconcentrations of oat milk and carrot juice, with vanilla flavoring providing a complementarytaste. Quality parameters including sensory attributes, texture and nutritional properties areassessed to ensure the acceptability and stability of the final product. The incorporation of oatmilk and carrot enhances the creaminess and nutritional value of the ice cream whileimparting a subtle sweetness and earthy undertones. The addition of vanilla flavor contributesto a well-balanced taste profile, appealing to a wide range of consumers. Furthermore, textureanalysis reveals that the ice cream maintains its desired consistency and exhibits satisfactorymelting characteristics. In conclusion, the development of oat milk, carrot and vanillaflavored ice cream offers a promising approach to meet the evolving preferences of healthconscious consumers without compromising on taste and indulgence.