Showing papers in "International Journal of Advance Research, Ideas and Innovations in Technology in 2018"

IoT based Smart Garbage and Waste Collection Bin

Abstract: Squander administration is turning into a hotly debated issue in strategy urban communities. Municipal governments, which are to a great extent in charge of building and keeping up squander transfer systems, are quick to discover methods for limiting the cost of discarding waste and the sheer measure of waste society produces. Sadly, market and corporatist methodologies don't think about waste administration, rather leaving waste administration to nearby experts, and without government compulsion will as a rule not worry about condition benevolent item configuration, squander minimization or the reuse, re-assembling or reusing of the item toward the finish of its life cycle. We propose a framework which will have fundamental sensor like IR sensor to identify the measure of junk canister filled and discharge flag to the line following bot to gather the effectively isolated fluid and strong waste. The isolated waste will be simpler to dispose. Standard gathering of waste will make the encompassing a cleaner put.

Resolving Multi-party Privacy Conflicts in Social Media

Abstract: Information shared through Social Media may affect more than one user’s privacy e.g., Information that depicts different users, comments that mention different users, events in which different users are invited, etc. Many types of privacy management support in present mainstream Social Media foundation makes users unable to appropriately control the sender and receiver. Computational mechanisms that are able to merge the privacy preferences of different users into a single policy for an item can help solve this problem. Merging different user’s personal preferences is difficult hence conflicts occur in privacy preferences, so methods to resolve conflicts are needed. Moreover, these techniques need to consider how users’ would actually reach an engagement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the information to be shared. present approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. Here, we introduce the basic computational procedure to overcome problems in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach answers to the conflicts. The present results of a user study in which our introduced mechanism outperformed other present approaches in terms of how many times each approach matched users’ action. Computational mechanisms that are able to merge the privacy preferences of multiple users into a single policy for an item can help solve this problem. However, merging multiple users’ privacy preferences is not an easy task, because privacy preferences may conflict, so methods to resolve conflicts are needed. Moreover, these methods need to consider how users’ would actually reach an agreement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the item to be shared. Current approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. In this project, we propose the first computational mechanism to resolve conflicts for multi-party privacy management in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach a solution to the conflicts. We also present results of a user study in which our proposed mechanism outperformed other existing approaches in terms of how many times each approach matched users’ behavior.

Internet of things based intelligent street lighting system for smart city

Abstract: This project aims for designing and executing the advanced development in embedded systems for energy saving of street lights. Currently, we have a manual system where the street lights will be switched ON in the evening before the sunsets and they are switched OFF in the next day morning after there is sufficient light on the outside[1]. But the actual timing for these lights to be switched ON is when there is absolute darkness. With this, the power will be wasted up to some extent. This project gives solution for electrical power wastage [2]. Also, the manual operation of the lighting system is completely eliminated. The proposed system provides a solution for energy saving. This is achieved by sensing and approaching a vehicle using an IR transmitter and IR Receiver couple. Upon sensing the movement the sensor transmits the data to the microcontroller which furthermore the Light to switch ON [4]. Similarly, as soon as the vehicle or an obstacle goes away the Light gets switched OFF as the sensor senses an object at the same time the status(ON/OFF) of the street light can be accessed from anywhere and anytime through the internet. This project is implemented with the smart embedded system which controls the street lights based on detection of vehicles or any other obstacles on the street.W he never the obstacle is detected on the street within the specified time the light will get automatically ON/OFF according to the obstacle detection and the same information can be accessed through the internet. The real-time information of the street light(ON/OFF Status) can be accessed from any time, anywhere through internet.

IoT based smart energy meter

Abstract: Energy meter reading is a tedious and an expensive affair. The meter reader has to go and take the reading manually to issue the bill, which will later be entered into the software to automate the billing and payment system. This paper proposes a new network communication system for energy meter reading by internet communication technology and software system along with the existing meters. An IoT modem will be integrated with electronic energy meter to read the usage of electricity and uploaded on server or website. Energy meter delivers the reading details and it is uploaded to the website instantly. This communication system is further useful for electricity regional/sub-regional office, who can monitor the power consumption, and they cut the power supply for any specific house, who had not paid the electric bill using the EB Office Login. Moreover, this power cut control system is done by using the same website which is used for monitoring. In this project each customer is differentiated using address or ID, this ID is used for identification by the consumer and as well as my office to monitor the reading and payment details. The user can also monitor their usage from anywhere using the user login. An additional feature is provided to the user for controlling the power supply during in terms of emergency case.

Estimation of Land Surface Temperature using LANDSAT 8 Data

Abstract: Land surface temperature (LST) is an important factor in many areas like climate change, urban land use/land cover, heat balance studies and also a key input for climate models. LANDSAT Data has given a lot of possibilities to study the land processes using remote sensing. This study has been made to estimate LST using Arc GIS over Hosur, Krishnagiri district, Tamil Nadu, India, using LANDSAT 8 satellite data. The LST has been estimated with respect to Normalized Difference Vegetation Index (NDVI) values determined from the Red and Near Infrared bands. The Land Surface Emissivity (LSE) is retrieved directly from the Thermal Infrared bands. The present study focuses on ArcGIS Raster functions and Raster calculation using the LANDSAT 8 April and November, thermal Bands (10 & 11). The results are feasible to Calculate NDVI, LSE and LST with appropriate accuracy.

5G wireless technology

Abstract: 5G technology will be changing the way of most high-speed bandwidth many users can be accessed mobiles.5G networks will provide a \"fiber-like\" experience to the mobile user. 5G Technology is offered in the services of the product engineering, documentation, supporting electronics transaction (e-payment and e-transaction) etc. In this technology is heterogeneous mobile environment changes all in, either old or new wireless technologies and it is not possible of them. So, each and every solution towards the next generation smart mobiles and wireless devices should implement the service stratum, while the radio stratum accessing technology belong to transport stratum of the regarding the next generation of networks which are coming futures. A 5G cellular network is expected to meet high-speed requirements.

Credit card fraud detection using Naïve Bayes model based and KNN classifier

Abstract: Machine Learning is the technology, in which algorithms which are capable of learning from previous cases and past experiences are designed. It is implemented using various algorithms which reiterate over the same data repeatedly to analyze the pattern of data. The techniques of data mining are no far behind and are widely used to extract data from large databases to discover some patterns making decisions. This paper presents the Naive Bayes improved K-Nearest Neighbor method (NBKNN) for Fraud Detection of Credit Card. Experimental results illustrate that both classifiers work differently for the same dataset. The purpose is to enhance the accuracy and enhance the flexibility of the algorithm.

Feature selection in network intrusion detection using metaheuristic algorithms

Abstract: Network Intrusion Detection (IDS) mechanism is a primary requirement in the current fast growing network systems. Data Mining and Machine Learning (DM-ML) approaches are widely used for network anomaly detection during the past few years. Machine learning based intrusive activity detector is getting popular. However, they produce a high volume of false alarms. One of the main reasons for generating false signals is redundancy in the datasets. To resolve this problem, an efficient feature selection is necessary to improve the intrusion detection system performance. For this purpose, here we use Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), K-Nearest Neighbors (KNN) and Support Vector Machine (SVM). The three abovementioned algorithms are used to select the most relevant feature set for identifying network attacks, KNN and SVM algorithms are used as classifiers to evaluate the performance of these feature selection algorithms. The standard NSL-KDD dataset is used for training and testing in this study. We used different metrics to determine which of these algorithms provide a better overall performance when they are used for feature selection in intrusion detection. Our experiments show that PSO, ACO and ABC algorithms perform better than other approaches in feature selection. Feature selection based on ABC provides 98.9% of accuracy rate and 0.78% false alarm with KNN algorithm as the classifier, which is the best result among the examined algorithms.

Smart parking system using IoT

Abstract: These day's usage of personal vehicles is increasing to commutate than depend on public transportation. Due to increasing personal vehicles, it’s a big task to find a parking space in most of the cities. To overcome this problem we are introducing the new concept of smart parking system using IoT. The main objective of this project is to find free slots in any parking area. It allows us to register a free slot with user details and then the unique id is generated for that particular slot. When the vehicle enters the parking slot it asks for the ID which was generated while booking, if the ID is valid then only it allows the entry into the parking slot. If ID is not valid it does not allow.

Fake News Detection

Abstract: Fake news, one of the biggest new-age problems has the potential to mould opinions and influence decisions.The proliferation of fake news on social media and Internet is deceiving people to an extent which needs to be stopped.The existing systems are inefficient in giving a precise statistical rating for any given news claim. Also, the restrictions on input and category of news make it less varied. This paper proposes a system that classifies unreliable news into different categories after computing an F-score. This system aims to use various NLP and classification techniques to help achieve maximum accuracy.

Optimization of Surface Roughness, Material Removal Rate and Tool Wear Rate in EDM using Taguchi Method

Abstract: In the present manufacturing scenario, EDM is the widely used non-traditional machining process which is used to machine hard materials such as alloys or composites. In the last few decades, there are lots of advancements in EDM which makes EDM more popular. There is a wide range of application of EDM in the aerospace, die-making and some other manufacturing sectors which require high precision. EDM is also called as high precision machining which can be used in the batch production where the traditional machining processes fail. In the last few years the developments in the new tool material, optimization techniques, and conductive ceramics have made some new research scopes in EDM. The aim of present study is to investigate the effect of input parameters like current, voltage and pulse-on-time on the Al-SiC (reinforced with 10% wt. of SiC). The output parameters for the process are MRR, TWR and surface roughness. It is found that the selection of input parameters plays an important role in the performance of the EDM.

Electronic voting machine based on Blockchain technology and Aadhar verification

Abstract: Increasingly digital technology in the present helped many people lives. This paper describes an electoral system for Indian election on blockchain technology and Aadhar verification. The aspect of security and transparency is a threat from still widespread election with the current system. Some of the problems that can occur in the current system are with an organization that has full control over the database and system, it is possible to tamper with the database of considerable opportunities. The proposed system is mainly designed for our country based on Aadhar verification where the details of the persons who are above 18 years are extracted from Aadhar card database since it had become mandatory in the present scenario. To ensure more security, the fingerprint of a voter is used as the main authentication resource. The system will allow the voter to vote through his fingerprint. As soon as they cast their vote, blockchain technology comes into existence which is integrated inside EVM. By adopting Blockchain in the distribution of databases can reduce one of the cheating sources of database manipulation. This research discusses the recording of the voting result in blockchain algorithm from every place of election.

Heart Disease Prediction System using Hybrid Technique of Data Mining Algorithms

Abstract: The primary goal of this research paper is to devise out a model that gives a highly accurate prediction of Heart Disease. As we have done a combination of Genetic and Naive Bayes Technique, the Investigation developed a Hybrid model of both these techniques and called it Hybrid Genetic Naive Bayes Model for predicting high accuracy in results.

Iris recognition based on human interpretable features

Abstract: The human iris is used for human recognition in various applications. However, deployment of iris recognition in forensic applications has not been reported. A primary reason is the lack of human-friendly techniques for iris comparison. The usage of iris recognition can be increased by visualizing the similarity between irises. Scientist Shen proposed the human-in-the-loop method for detecting and matching iris crypts. Thus with the help of this, we proposed a new approach for automatic detection and matching of crypts. This detection method is able to capture iris crypts of various sizes. This matching scheme is designed to handle potential topological changes in the detection of the same crypt in different images. In particular, this approach achieves over 22% higher rank one hit rate in the identification, and over 51% lower equal error rate in verification. In addition, the benefit of this approach on Multi-enrollment is experimentally demonstrated.

Job satisfaction of secondary school teachers

Abstract: Teachers always play a vital role in the development of the society and the nation at large. They are accorded recognition due to their manipulative skills in igniting the inherent talents of the children. The successful running of any educational system depends mainly upon the teacher, the pupil, the curriculum, and the available facilities. Out of these, the teacher is the most important one and is the pivot on whom the entire educational structure rests. Teachers, who are happy with their job, find satisfaction in their lives and hence play a vital role in the process of strengthening the society they belong (Lavingia, 1974). Hence, job satisfaction of teachers is not only important for themselves, but also for the students and as well as the institution and the society they belong. Based on this, a study is conducted by taking a sample of 100 teachers working in different secondary schools of English medium and Telugu medium belonging to Anantapur district of Andhra Pradesh were taken to investigate the problem. Job Descriptive Index developed by Hulin, Kendall, and Smith (1969) was used to measure Job Satisfaction. Data were analyzed using mean, S.D, t-test and F-ratio. The results revealed that: 1. There is no significant difference in the job satisfaction of secondary school teachers belonging to various monthly income groups and 2.There is no significant difference in the job satisfaction of secondary school teachers belonging to a different medium of instructions.

Heart disease prediction using classification and feature selection techniques

Abstract: The value of measurement age, blood pressure, weight, smoking habits, exercise, and blood serum cholesterol in predicting death and coronary cardiopathy was studied over an amount of ten years. Sixteen teams comprising 12 763 men aged 40-59 years (at the outset) from 7 countries (Yugoslavia, Finland, Italy, Kingdom of The Netherlands, Greece, USA, and Japan) were studied. the very best risk factors were found to be age, pulse blood pressure, and blood serum cholesterol concentration (related to saturated fatty acids within the diet). Variations in incidence rates couldn't be shown to be associated with characteristics of the cohorts in relative weight, smoking habits or physical activity. To design a perceptive model for heart illnesses acknowledgment using data mining strategies that are fit for enhancing the constancy of heart infections conclusion. Thereafter, we divide this data into Training and Testing Data Sets and employ Naive Bayes technique to obtain relatively higher prediction accuracy. The primary goal of this research would be given a highly accurate prediction of Heart Disease. As we have done a combination of Genetic and Naive Bayes Technique, the Investigation would be developed a Hybrid model of both these techniques and called it Hybrid Genetic Naive Bayes Model for predicting high accuracy in results.

Twitter Sentiment Analysis using Vader

Abstract: Twitter is a micro-blogging site used by people to express their opinions on various topics Sentiment Analysis is the process of extracting meaningful customer insight from a text in terms of sentiment score Twitter Sentiment analysis is an application of sentiment analysis, on the twitter data (tweets)But today it has become difficult to analyze tweets because of the changed and challenging formats of the tweets The increase in the use of various slangs, emoticons, abbreviations, and puns in tweets, has made it difficult to analyze tweets in the same ways as before In this paper, we aim to review some papers regarding research in sentiment analysis on Twitter, describing the methodologies adopted and models applied; along with describing Vader Sentiment Analysis which is a Python-based approach

Automated street lighting system using IoT

Abstract: In this modern era where energy is a major concern worldwide, it is our prior responsibility & liability to save energy effectively. With the development of technology, where automation system plays a vital role in daily life experience and it is being preferred over the traditional manual system today. Here we propose an IOT based street light monitoring and controlling system to ensure, low power consumption, instant faulty light detection and light dimming as per external lighting conditions. Our proposed system consists of smart street lights that have external light sensing that automatically turns on at the desired intensity based on an amount of lighting needed.

The physics of Magnetic Resonance Imaging

Abstract: MRI is an acronym for Magnetic Resonance Imaging. MRI is used in radiology and it is one of the scanning technologies where magnetism, radio waves, and a computer are used to take the total image of the body structures. The chief advantage of the MRI is to give clear images of the soft-tissue structure where other imaging techniques fail to give without any effect to the patient.MRI is based on the interaction of magnetic properties of hydrogen with both a large external magnetic field and radio waves, which send signals to the body and then receive signals back. These returning signals are converted into images by a computer attached to the scanner. Imaging of any part of the body can be obtained in any plane. This Article gives a brief idea about the history, construction, working principle of MRI which includes Nuclear spin, Larmour,s frequency, T1 and T2 relaxation and T1 and T2 weighted images.

IoT based smart energy meter monitoring and controlling system

Abstract: In recent scenario, energy saving holds prime significance because of inequality between demand and power generation. Using Wi-Fi module entire system will be controlled. Internet of Thing (IoT) is internally related to computing tricks transferring the data under the network with no any help of a human to human or human to computer interrelation. The load to the consumer is to consume regularly with regular monthly payment of the bill. When the electricity bill is paid then the supply will continuously flow or provides.

Ion Exchange Resins- An approach for the Development of Advanced Materials with Industrial, Pharmaceutical and Clinical Applications

Abstract: Ion exchange resins (IER) are cross-linked water insoluble polymers that contain ionizable acidic or basic functional groups and have the ability to exchange counter-ions from surrounding within aqueous solutions. On the basis of nature of the exchangeable ion of the resin as a cation or anion, classified into two main classes, cationic exchange resinand anionic exchange resins, respectively. Due to versatile properties of IER, it has received considerable attention from worldwide pharmaceutical scientists. Research has shown that for the past few years, IER is equally suitable for drug delivery techniques, including controlled release, topical, transdermal, nasal and taste masking. The efficacy IER mainly depends upon their physical properties such as porosity, acid-base strength, degree of cross linking, stability, purity and particle size. Ion-exchange resinates (Drug-Resin complex) of drugs can help in reducing the dose, fluctuations in blood and tissue concentrations, avoiding dose dumping, and maintenance of drug concentration below toxic level can be achieved. The major drawback of sustained release or extended release is dose dumping, resulting in increased risk of high dose toxicity. The utilization of IER has occupied an important place in the development of controlled or sustained release systems because of their better drug-retaining properties and prevention of dose dumping. Resins are polymers that contain appropriately substituted acidic groups, such as carboxylic and sulfonic for cation exchangers; or basic groups, such as quaternary ammonium group for anion exchangers. Drug resin complexation converts drug to amorphous form leading to improved drug dissolution. Many studies have reported the use of IER for drug delivery on the desired site of action. Sulfonated and carboxylic resins with a polystyrene backbone are mostly used in clinical medicine. This review will cover various types of ion exchange resin, their property, chemistry; The role of IER in controlled drug delivery systems, its Industrial, Pharmaceutical and clinical applications, methods of preparation of IER along with their resonates.

A smart farming system using Arduino based technology

Abstract: Internet of Things (IoT) is a technology that permits things to communicate and connect with each other. This is helpful in changing the patterns and processes in both industry and agriculture towards higher efficiency. A system is proposed which describes the smart farming in order to improve the production process in planting. Smart farming consists of two main parts which are a sensor system and a control system. Sensor system consists of a set of tools to obtain the sensed values. Control system involves a blower, watering and roofing system operated on a human interface. Two Arduino boards are programmed for sensing and the controlling system. Programming for controlling the system is done in python. The sensed values from a different sensor are viewed on an LCD display as well as a serial monitor. Results are maintained as a database in excel sheet and the graphical representation of the same is obtained. Looking on to results obtained from the sensor system, a control system is activated using the python controlling console. An increase in product quality and quantity is achieved by following the proper decision-making process.

Smart Assistance for Blind People using Raspberry Pi

Abstract: This paper addresses the integration of a complete Text Read-out system designed for the visually challenged. The system consists of a webcam interfaced with raspberry pi which accepts a page of printed text. The OCR (Optical Character Recognition) package installed in raspberry pi scans it into a digital document which is then subjected to skew correction, segmentation, before feature extraction to perform classification. Once classified, the text is readout by a text to speech conversion unit (TTS engine) installed in raspberry pi. The output is fed to an audio amplifier before it is read out. The simulation is just an initiation of image processing i.e. the image to text conversion and text to speech conversion done by the OCR software installed in raspberry pi. The system finds interesting applications in libraries, auditoriums, offices where instructions and notices are to be read and also in assisted filling of application forms.By using ultrasonic sensor we will measure the distance between the blind people and obstacle then the distance will be played through ear phones.

A search for the source of high content of sodium chloride (NaCl) at Crater Lake Lonar, Maharashtra, India

Abstract: Highly saline and highly alkaline nature of lake water is observed at Lonar Crater from ancient time till today. The formation of this lake is related to the formation of the crater by the impact of a meteorite forming Soda Lake. The existence of NaCl (Sea salt/common salt) in such a large quantity at Lonar, where the source is unknown because the formation of NaCl salt is a natural process and it may have started before the sea came into existence after the formation of the earth. The surrounding basaltic rocks has no NaCl salt or Chlorides content. A search was conducted to find the source of NaCl, which constantly maintained high salinity and at the same time high alkalinity from ancient time. Three edible salts i.e., Halite rock salt (mineral form of NaCl), Kala namak (Black salt) and Sea salt (common salt) having similar physical properties as representative samples were taken for comparison with respect to Lonar salt. After analysis of the three salts namely Halite (rock salt), Kala Namak and Sea Salt, the major component found was NaCl in various amounts. It was found that the major component NaCl was also present in Lonar Salt which suggested that the source of high salinity may be from the remains of an ancient dried up sea which existed before volcanic eruption of 65ma, or there may be store house of NaCl salts beneath the basaltic rocks which reflects the primitive ecosystem lying under primitive basaltic rock, totally unknown and have not been excavated. This paper reports the findings and the work carried out to search for the source of high content of NaCl (sea salt also known as common salt) existing at the Crater Lake, Lonar on preliminary basis.

Air pollution modelling

Abstract: Industrial chimney releases pollutant to the environment which causes air pollution. As an air pollutant is transported from a source to a potential receptor the pollutant disperses into the surrounding air so that it arrives at a much lower concentration than it was on leaving the source. Air pollution modeling helps to determine the mathematical relationship between the effects of source emission of pollutant on ground level concentration. Many dispersion models have been developed and used to estimate the downwind ambient concentration of air pollutants from sources such as industrial plants, vehicular traffic or accidental chemical release. Air Pollution emission plume i.e., the flow of pollutant in the form of smoke released into the air. Throughout many dispersion models, Gaussian Dispersion Models perhaps the oldest (circa 1936) and perhaps the most commonly used model type. The primary algorithm used in Gaussian modeling is the Generalized Dispersion Equation for a continuous point source plume. This paper reviews the air pollution modeling which relates the effects of source emission on ground level concentration by mathematical equations and terminology.

Segmentation of cartilage from knee MRI images using the watershed algorithm

Abstract: We present here watershed segmentation method for the segmentation of knee cartilage. Watershed segmentation is a state of the art method and involves great simplicity of application. MRI images of the knee cartilages are used for segmenting and early detection of the osteoarthritis. MRI images offer better visualization of the soft tissues like cartilage still visualization of the tissues prone to damage is needed to be detected earlier. However, the method incorporates noise while segmentation stills its great simplicity attracts researchers for its use.

Smart cane for visually impaired people

Abstract: Visually impaired people find difficulties detecting obstacles in front of them, during walking in the street, which makes it dangerous. Smart cane for visually impaired comes as a proposed solution to enable them to identify the world around. It is used for the smart navigation for visually impaired people in indoor and outdoor environment respectively. In this, we propose a solution, represented in a smart cane with the ultrasonic sensor to detect any other obstacles in front of the user, which is close enough. Moreover, another sensor i.e. water sensor is placed at the bottom of the stick for the sake of avoiding puddles. This proposed system uses the ATMEGA16 328 micro-controller embedded system and buzzer.

Simulation study of brent kung adder using cadence tool

Abstract: Adders are the most fundamental piece of any computerized framework. In order to perform the addition of two numbers, adders are used. They also form the requisite part of Arithmetic and Logic Unit. Besides this application, they are also used in computers to calculate address, indices and operation codes. Adders are also used to employ different algorithms in Digital Signal Processing. There is a prerequisite to provide an efficient adder design which fulfills the trade-off amongst speed and space consideration to increase the performance of the system. In the modern age, in addition to the trade-off between speed and space, power consumption assumes an imperative. Gadgets with low power utilization and good performance are favored in real-time applications. Parallel Prefix adders are the ones generally utilized as a part of Digital Designs due to the adaptability associated with outlining these Adders. Brent Kung Adder (BKA) is a low power parallel prefix adder, as it uses minimum circuitry to obtain the result. A simulation study of this adder is carried out using cadence tool. The 4-bit, 8-bit, 16-bit and 32-bit BKAs were designed and simulated using CMOS logic- 45nm Technology. A comparative study was made by comparing the obtained results with Ripple Carry adder and Carry Look-ahead adders. Obtained results show that the power consumption and propagation delay for the BKA implementation are reduced compared to RCA and CLA.

Growth and Instability in Area, Production and Productivity of Cassava (Manihot Esculenta) in Kerala

Abstract: Cassava is a major tuber crop cultivated in Kerala, as a sole crop or as a mixed crop, mainly cultivating in homesteads and primarily used for household consumption The share of cassava area in Kerala to all India area declined from 8557 to 455 percent in 2001-02 With the introduction of short duration varieties, there was an increase in productivity Trend and Instability analysis in the area, production and productivity of cassava for a period of 25 years were carried out The estimated trends in the area, production, and productivity of cassava, using semi-log function revealed that there was a significant decline in an area with a compound annual growth rate of 137 %, the non-significant decline in production by -002 % and a significant increase in productivity by 13 % Cuddy-Della Valle index provides the best estimates and instability was found to be more in productivity (404 %)

Big Data Classification of Users Navigation and Behavior Using Web Server Logs

Abstract: Users for online shopping are increasing day by day because of easy to get and time-saving property of online shopping. Having a proper understanding of users interest for certain type of product or different products for online shopping becomes important to create personalized service for a target market. An important property of successful e-commerce website is the ability to provide useful content at the right time to users. And because of all this, personalization techniques are introduced to create adaptive shopping application in which user interfaces change according to users interest. User’s behavior information is stored in web log files, and to get the information data mining techniques are used in which they use statistical characters to model users behavior and not considering the sequence of action performed by uses. It becomes helpful if we follow user’s session to understand complex user behavior. Therefore to eliminates all these issues this paper proposes a linear-temporal logic model checking approach for the analysis of structured e-commerce weblogs. If we consider a common way of mapping log records according to e-commerce structure, weblogs can be easily converted into event logs by which behavior of the user is captured. After getting users behavior by performing different predefine queries to identify different behavioral patterns that consider the different actions performed by a user during a session.