Oriental Journal of Computer Science and Technology An International research journal of Computer Science and Technology

Potatoes are cultivated in several states of India. Potatoes provides a low-cost energy in human diet. Potatoes are used in industry for making dried food products. Early blight and Late blight are major disease of potato leaf. It is estimated that the major loss occurred in potato yield due to these diseases. In this research, we have collected sample of potato leaf images from Plant Village dataset. This dataset contains 2152 images of potato leaf. It has 3 class of sample of Healthy Leaf, Early Blight and Late Blight. The 76 features are extracted from these images regarding color, texture and area. The extracted features are used to develop a classifier. The developed classifier is based on neural network for prediction and classification of potato image samples. The Feed Forward Neural Network (FFNN) Model is used for prediction and classification of unknown leaf. The accuracy of model is achieved 96.5%. Classifier is helpful in early and accurate prediction of the leaf diseases of potato crop.

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Wireless sensor networks (WSNs) are a new kind of wireless networks that are becoming very popular with a large number of civilian and military applications. A wireless sensor network (WSN) is a wireless network that contains distributed independent sensor devices that are meant to monitor physical or environmental conditions. AWireless Sensor Network consists of a set of connected tiny sensor nodes, which communicate with each other we can also interchange information and data. These nodes obtain information on the environment such as temperature, pressure, or humidity and this information is stored in a base station. The latter sends the info to a wired network or activates an alarm or an action, depending on the type of data being monitored.

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Indian floriculture industry has grown by multiple folds in the past decade and has become one of the top ten leading producers of varieties of flower production. This tremendous growth of floriculture industry has proportionally also contributed to the depletion of environmental system. The current work narrows down to handle the environmental hazards of rose farming in the floriculture industry through technology-driven fertilization process. The composition and quantity of nutrients, and the period of its application is very crucial for the plant’s growth.The smart fertigation process helps in providing a balanced nutrient dose to the plants.The internet of things (IoT) is defined as a network of physical objects called as “things” that have embedded with sensors and software that allow these objects to communicate with each other. These objects areaccessed, monitored and controlled remotely. While the reduction of one of the nutrients might result in poor development of the plant, overfeeding of nutrients leads of stagnation of salts and soil wilting. The paper proposes a smart IoT-based fertilizer application infrastructure for an optimal growth of plants with under a controlled usage of fertilizers.The dependency of fertilizers and insecticides during each stage of the plant development is monitored and a smart fertigation infrastructure is built to automate the process of feeding the plants with appropriate chemicals at appropriate intervals.

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A Mobile Ad Hoc Network (MANET) is much more vulnerable to various security attacks due to its high mobility, multi-hop communication and the absence of centralized administration. In this paper, we investigate the impact of Jellyfish periodic dropping attack on MANETs under different routing protocols. This investigate is under the class of denial-of-service attack and targets closed loop flows which results in delay and data loss. In this paper, the simulation results are gathered using OPNETnetwork simulator and its effect on network performance is studied by analysing re-transmission attempts, network load and throughput. The results have shown that the impact of Jellyfish periodic dropping attack which reduces the network performance.Performance shows OLSR performs better than AODV under periodic drop attack.

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Players more often engage in excessive physical activities during exercise session as well as in the game session because results of the games highly depend over the performance of participants that can be degraded due to various factors current health status, injury history, exercise types and duration, training and game experience. A Multi agent System can analyze all these factors and the overall performance of the participants can be improved using feedback. In this paper, the role of the Artificial Intelligence, Expert System, Machine/Deep Learning/Neural Networks in the sports and healthcare industry will be explored.

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Speaking of recent advances, many computing technologies have been applied to several domains and have proved to provide more approximate and acceptable results. Fuzzy logic being one of them has been very useful in solving many real-world problems that are inherent for their uncertainty, complexity, impreciseness and a high degree of randomness. Soft computing aims to mimic human thinking and thus solve problems as a human does. The systems embedded with one or more soft computing technologies tend to make decisions quicker (reducing the processing timeframe) and more accurate in the light of uncertain and indefinite data. This paper aims at an extensive review of fuzzy logic also unraveling some of the applications of the same in the field of agricultural science and meteorology.

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Modern human activity recognAition systems are mainly trained and used upon video stream and images data that understand the features and actions variations in the data having similar or related movements. Human Activity Recognition plays a significant role in human-to-human and human-computer interaction. Manually driven system are highly time consuming and costlier. In this project, we aim at designing a cost-effective and faster Human Activity Recognition System which can process both video and image in order to recognize the activity being performed in it, thereby aiding the end user in various applications like surveillance, aiding purpose etc. This system will not only be cost effective but also as a utility-based system that can be incorporated in a large number of applications that will save time and aid in various activities that require recognition process, and save a lot of time with good accuracy Also, it will aid the blind people in availing the knowledge of their surroundings.

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Cloud computing is an emerging paradigm thatprovides computing, communication and storage resourcesas a service over a network. Data Integrity is an important aspect which ensures the quality of the data stored in the cloud. Data Replication is the key factor which restores the corrupted data stor

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The model and pattern for real time data mining have an important role for decision making. The meaningful real time data mining is basically depends on the quality of data while row or rough data available at warehouse. The data available at warehouse can be in any format, it may huge or it may unstructured. These kinds of data require some process to enhance the efficiency of data analysis. The process to make it ready to use is called data preprocessing. There can be many activities for data preprocessing such as data transformation, data cleaning,  data integration, data optimization and data conversion which are use to converting the rough data to quality data. The data preprocessing techniques are the vital step for the data mining. The analyzed result will be good as far as data quality is good. This paper is about the different data preprocessing techniques which can be use for preparing the quality data for the data analysis for the available rough data.

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Continuous striving in the development of wireless mobile networks maximizes the possibility of user services and provides experience context rich and personalized services. In this way, for the development towards fully integrated 4G‐all IP network architecture, the interoperability between future generation wireless networks and seamless vertical handover (VHO) has become a crucially important issue. The proposed work is mainly focusing on exploring interoperability issues in heterogeneous networks considering development towards 4G and emphasizing on emerging IEEE 802.21 standard. Further, Simulation results were presented to showcase vertical handover (VHO) performance using IEEE 802.21. Simulation Analysis is done using Network Simulator (NS-2) with seamless mobility package extension.

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Security has been one of the most critical concerns for wireless sensor network (WSN) systems in recent years. Application of WSN has faced criticism in several fields due to limited flexibility and security in the long term. This study aimed at reviewing the dynamic key management schemes for Heterogenous WSN systems to determine efficient management schemes. Applicability of notable schemes such as Basic scheme, and hybrid schemes under dynamic key management depends majorly on the central key controller presence

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This computer application deals with energy auditing for rice-wheat cropping system. Computing different input parameters for the crop production system in terms of energy requirement (MJ/ha) can be done by using this computer application. The developed application was found to be a simple, easy and user-friendly with appropriate output units. It works efficiently and gives the desired output in terms of energy consumption (MJ/ha). The advantage of this application is to decide the inputs on the basis of energy consumption before performing actual cultivation practice using the last season data. Moreover, using this package energy budget difference and comparison of subsequent production seasons can be achieved. The computer application was developed using Visual Basic, which allows the user to calculate total energy use efficiency, specific energy and different energy ratios in a particular cropping system.

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Simulation approach has been widely utilized for design and planning of a warehouse logistic system. As technology advances, better simulation tools have been developed. This enables decision makers to create more realistic models to represent the actual scenario. As a result, better evaluation could be made especially regarding dynamic factors within system. Thus, complex logistic problems could be solved. This paper reviews the fundamentals of warehouse logistic and the simulation tools available to analyze logistic problems.

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Fifty years ago instrumentation and control (I&C) systems at nuclear power plants (NPP) were analog and relied on a mixture of mechanical, pneumatic and electric components. Today analog technology has been replaced with digital technology. Digital I&C has over the years experienced difficulties in the licensing process, which has delayed and escalated costs of both NPP and I&C projects. In the paper it is argued that some of the difficulties are connected to misunderstandings regarding differences between analog and digital I&C. These misunderstandings have led to unrealistic expectations regarding proofs that selected I&C systems can be considered acceptable. To ensure a successful licensing process it would be necessary to agree on evidence for safety that can be considered sufficient. Such evidence should be collected both from the I&C design process and from testing intermediate and final I&C solutions. By a combination of evidence from different sources it should be possible to build a safety case that can be agreed to give sufficient proofs for acceptability. The first component in building the safety case is to make use of safety principles to provide structural evidence that certain classes of design errors have been avoided. The second component is to use simulators and targeted testing to demonstrate functionality of the I&C in different plant situations.

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Breast cancer affecting the women is known to cause high mortality unless detected in right time. Detection requires Mammography followed by biopsy of the tumour or lesions present in the breast tissue. Contemporary Mammographic hardware has incorporated digitization of output imagesfor increasing the scope for implementation of computational methods towards Computer Aided Diagnostics (CAD).CAD systems require Medical Image Processing, a multi-disciplinary science that involves development of computational algorithms on medical images. Histopathological slides are examined for determination of malignancy after biopsy is performed. Digital Images are required to be registered and enhanced prior to application of any deterministic algorithm. This paper provides both effective and efficient improvements over existing algorithms and introduces some innovative ideas based on image segmentation process to develop computer aided diagnosis tools that can help the radiologists in making accurate interpretation of the digital mammograms.

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