Showing papers in "Indian journal of science and technology in 2014"
TL;DR: The results of principal component analysis used in the study have revealed the high level of genetic variation and the traits contributing for the variation was identified and this population panel can be utilized for trait improvement in breeding programs for the trait contributing for major variation.
Abstract: A population panel of 192 rice genotypes comprising traditional landraces and exotic genotypes from 12 countries was evaluated for 12 agro - morphological traits by principal component analysis for determining the pattern of genetic diversity and relationship among individuals. Twelve quantitative characters i.e. plant height, leaf length, number of productive tillers, panicle length, number of filled grains, spikelet fertility, days to 50% flowering; days to harvest maturity, grain length, grain width, grain length width ratio, and single plant yield were measured. The largest variation was observed for number of productive tillers with Coefficient of Variation (CV) of 28.03% followed by number of filled grains per panicle, single plant yield, leaf length , grain length width ratio. Days to maturity has shown the least variation with the CV of 9.74%. Principal component analysis was utilized to examine the variation and to estimate the relative contribution of various traits for total variability. In the current study, Component 1 had the contribution from the traits such as days to 50% flowering, leaf length, plant height, panicle length, days to maturity and number of filled grains which accounted 28.46% of the total variability. Grain width and grain length width ratio has contributed 16.8% of total variability in component 2. The remaining variability of 14.4%, 11.7% and 9.3% was consolidated in component 3, component 4 and component 5 by various traits such as spikelet fertility, single plant yield, grain length and number of productive tillers. The cumulative variance of 80.56% of total variation among 12 characters was explained by the first five axes. Thus the results of principal component analysis used in the study have revealed the high level of genetic variation and the traits contributing for the variation was identified. Hence this population panel can be utilized for trait improvement in breeding programs for the traits contributing for major variation.
67 citations
TL;DR: A novel steganographic technique based on nine-pixel differencing with modified Least Significant Bit (LSB) substitution with results reveal that the stego-images are imperceptible and hiding capacity is higher.
Abstract: To provide higher embedding capacity without sacrificing the imperceptibility, a novel steganographic technique based on nine-pixel differencing with modified Least Significant Bit (LSB) substitution is proposed. The image is divided into 3×3 non-overlapping blocks. In each block the average difference value is calculated. Based on this value the block is classified to fall into one of the four levels such as, lower, lower-middle, higher-middle, and higher. If a block belongs to lower level then 2-bit LSB substitution is used in it. Similarly, for lower-middle, higher-middle, and higher level blocks 3, 4, and 5 bit LSB substitution is used. After LSB substitution the pixel values are readjusted to minimize distortion such that these modified values do not disturb the embedded bits. The experimental results reveal that the stego-images are imperceptible and hiding capacity is higher.
46 citations
TL;DR: This paper presents the effective cost model for data storage with horizontal layout within the cloud, which converts the given aggregated data into horizontal layout form, which will reduce the size of the data to store in the cloud.
Abstract: Data storage space is virtually infinite in cloud computing. To store data in the cloud requires more cost because it is a 'pay and use model' and also the resources are based on budget constraints. Normally, question performance is a very important concept in database management system. To improve that introduces novel approach which will reduce the cost of data storage within the cloud. This novel approach converts the given aggregated data into horizontal layout form, which will reduce the size of the data to store in the cloud. This paper presents the effective cost model for data storage with horizontal layout within the cloud.
42 citations
TL;DR: In this article, the authors extracted morphological features of Bhilanganga drainage basin using satellite imagery and analyzed for assessing the drainage pattern and identifying priority sub-basins for conservation measures.
Abstract: Drainage pattern study utilizing Remote Sensing (RS) and Geographical Information System (GIS) has proved to be an efficient and quick tool, nowadays, for water resources planning, conservation and management. In the present study morphological features of 'Bhilanganga' drainage basin are being extracted utilizing satellite imagery and analyzed for assessing the drainage pattern and identifying priority sub-basins for conservation measures as well. The basin morphometric parameters such as linear and aerial aspects were determined and computed using ArcInfo software. The region is a part of Uttarakhand state of India, a hilly catchment in the lower Himalayan range covering an area of 1465.38 km2. The area extends from 30o19'41"N to 30o52'42"N latitude and from 78o29'13"E to 79o2'9"E longitude. The entire area is sub-divided into eight sub-basins ranging in area from 91.91 km2 to 465.29 km2. The pattern of drainage in the area is dendritic to sub-dendritic and the stream ordering ranges from order I to VII. The drainage density indicates a coarser drainage ranging from 1.68 to 2.34 km/km2. The entire area is the normal basin category as observed from the bifurcation ratio. The RS and GIS techniques have proven to be very useful in this case of morphometric analysis, as the study area is a hilly catchment located in a difficult terrain.
34 citations
TL;DR: In this paper, a Disperse red 60 and Disperse blue 56 were converted to the nano scale using ultrasonic homogenizer and characterized by transmission electron microscopy and compared with the polyester fabrics dyed with the same dyes without sonication.
Abstract: In this work a Disperse red 60 and Disperse blue 56 were converted to the nano scale using ultrasonic homogenizer and characterized by transmission electron microscopy. Dyeing of polyester fabrics was carried out in the temperature range of 70-100oC and compared with the polyester fabrics dyed with the same dyes without sonication. Dyeing was carried out using two different carriers: salicylic acid and HC carrier. ZnO nano powder was used to improve the light fastness for the dyed polyester fabrics.
32 citations
TL;DR: In this article, Zinc oxide (ZnO), Silver (Ag) and Titanium dioxide (TiO2) nanoparticles were synthesized using template-free aqueous solution based on simple chemical route which were characterised through SEM, TEM and XRD.
Abstract: Zinc oxide (ZnO), Silver (Ag) and Titanium dioxide (TiO2) nanoparticles were synthesised using template-free aqueous solution based on simple chemical route which were characterised through SEM, TEM and XRD. Size of Zinc oxide (ZnO), Silver (Ag) and Titanium dioxide (TiO2) nanoparticles measured 35-45nm, 20-80 nm and 85-100 nm, respectively to conform the nano-size. Groundnut seeds when dry dressed with the synthesised nanoparticles each at 500, 750, 1000 and 1250 mg kg -1, the dose of 1000 mg kg-1 outperformed in enhancing the germination (75%), shoot length (20.97 cm) root length (17.98) and thereby the vigour index (2949) compared to control (55%, 16.92, 15.21 and 1759) respectively.
31 citations
TL;DR: The combined method of feature extraction (Spatial and Frequency) shows superior performance than individual feature extraction schemes and gives good recognition results even without pre-processing of the image.
Abstract: Quality of image plays a vital role in increasing face recognition rate. A good quality image gives better recognition rate than noisy images. It is more difficult to extract features from such noisy images which in-turn reduces face recognition rate. To overcome problems occurred due to low quality image, pre-processing is done before extracting features from the image. In this paper we will analyze the effect of pre-processing prior to feature extraction process with respect to the face recognition rate. This also gives a qualitative description of various pre-processing techniques and feature extraction schemes that were used for our analysis. The results were analyzed with the help of bar graphs. The combined method of feature extraction (Spatial and Frequency) shows superior performance than individual feature extraction schemes. Also, this combined method gives good recognition results even without pre-processing of the image.
31 citations
TL;DR: In this article, the authors analyzed the long-term trends of monthly, seasonal and annual rainfall of Haridwar, Dehradun,Udham Singh Nagar, Almora and Nainital using Mann-Kendall and linear regression tests and change point was detected using cumulative deviation and Worsley likelihood statistic.
Abstract: Precipitation is the one of the prime indicators of climate change and its aberration causes many extreme events such as floods and droughts. Long-term trends were analyzed as monthly, seasonal and annual rainfall of Haridwar, Dehradun,Udham Singh Nagar, Almora and Nainital using Mann-Kendall and linear regression tests and change point was detected using cumulative deviation and Worsley likelihood statistic. Mann Kendall test revealed that there is significant increase in rainfall only for Haridwar district which has more urbanizing area compared to other districts. Haridwar is the holy place attracting significant floating population from all over the world, especially during festivals and fairs. Anthropogenic activity and industrialization is also the major cause of rainfall trend fluctuation in the Haridwar city. The monthly trend tests show that July rainfall is increasing whereas the December rainfall is decreasing which could be due to the seasonal shift. The start of change in the rainfall trend for the above mentioned districts is observed with distinct difference from 2009 onwards. From this it can be concluded that the stations to the west show significant trends compared to station which is towards east. Monsoon especially in July month a trend of increasing rainfall is observed in the studied Indian cities. The spatial and temporal trends of precipitation are pertinent for the future development and sustainable management of water resources of a given region.
31 citations
TL;DR: The development of an intuitionistic fuzzy logic controller for washing machine on the basis of intuitionism fuzzy systems and defuzzification techniques is described.
Abstract: In this paper, we describe the development of an intuitionistic fuzzy logic controller for washing machine on the basis of intuitionistic fuzzy systems. Intuitionistic fuzzy inference systems and defuzzification techniques are used to obtain crisp output (i.e., wash time of the washing machine) from an intuitionistic fuzzy input (i.e., type of dirt and degree of dirt). The wash time is calculated using intuitionistic fuzzy rules applied to an inference engine using defuzzification methods.
30 citations
TL;DR: Micronutrient-rich genotypes identified in this study opens up the possibilities for the identification of genomic regions or QTLs responsible for mineral uptake and translocation that can be used as donor for developing nutrient enriched varieties.
Abstract: Biofortification is an emerging cost-effective strategy to address global malnutrition especially in developing countries. This strategy involves supplying of micronutrients such as iron and zinc in the staple foods by using conventional plant breeding and biotechnology methods. Initial step in conventional plant breeding is to screen the natural gene reservoir for existing variation. The objective of this study is to estimate iron and zinc in the brown rice of 192 germplasm lines and to define its role in biofortification programme. Substantial variations among 192 lines existed for both iron and zinc content. Iron concentration ranged from 6.6 ig/g to 16.7 ig/g and zinc concentration from 7.1 ig/g to 32.4 ig/g in brown rice. Iron and zinc concentration were positively correlated implying the chance for concurrent selection for both the micronutrients. Micronutrient-rich genotypes identified in this study opens up the possibilities for the identification of genomic regions or QTLs responsible for mineral uptake and translocation that can be used as donor for developing nutrient enriched varieties.
27 citations
TL;DR: Field investigation was carried out to study the effect of different nitrogen levels on growth and yield parameters in potato var.
Abstract: Field investigation was carried out to study the effect of different nitrogen levels on growth and yield parameters in potato var. Kufri Surya. The experiment was laid out in a randomized block design with treatments consisting of six nitrogen levels replicated four times. Growth parameters like plant height, number of leaves per plant, number of shoot per plant, fresh and dry weight of shoot per plant and yield attributing parameters like number of stolon, fresh and dry weight of tuber per plant increased with an increase in nitrogen levels with maximum values being obtained on application of highest nitrogen level (375 kg N/ha). However, highest values for number of tuber per plant and per plot as well as tuber yield per plot and per hectare was recorded on application of 225 kg N/ha. The highest net returns (Rs. 117323) and maximum B: C ratio (1.42) was recorded on application of 225 kg N/ha.
TL;DR: A novel and a simple authentication model using one time pad algorithm that removes the communication of passwords between the servers is proposed to enhance the security in Hadoop environment.
Abstract: “Big Data” - voluminous and variety of data from different sources, which demands innovative processing and analysis for decision - making analysis. The data can be either in form of structured or unstructured data. Processing big data with the traditional processing tools and the present relational database management systems tends to be a difficult task. Parallel execution environment, like Hadoop is needed for processing voluminous data. For processing the data in a open framework like Hadoop we need a highly secure authentication system for restricting the access to the confidential business data that are processed. In this paper, a novel and a simple authentication model using one time pad algorithm that removes the communication of passwords between the servers is proposed. This model tends to enhance the security in Hadoop environment.
TL;DR: In this paper, a multi-item inventory model is presented to optimize the unit time profit of inventory management for the products having an expiration date after which the product can not be sold.
Abstract: Inventory decisions in supply chain are crucial for its success. These decisions become more important for the products with expiration date. Making these decisions in inventory systems with multiple products is a challenging task for managers. Most approaches in the literature for optimizing decisions in such an environment consider only a single item inventory. This paper presents a multi item inventory model to optimize the unit time profit of inventory management for the products having an expiration date after which the product can not be sold. As on one side the shortage costs are significant, on the other side, to maintain appropriate inventory levels for such type of products and avoid shortages is a very problematic job. For validation, the model is simulated and the results are compared. This article offers an approach for optimization and thus has business significance.
TL;DR: New Meta heuristic optimization algorithm called firefly algorithm (FA) used to solve the multi objective optimal power flow to identify the optimal setting of Static VAR Compensator (SVC) and optimal location is identified by using sensitivity analysis when the system is operating under normal and overloaded conditions.
Abstract: This paper presents a new Meta heuristic optimization algorithm called firefly algorithm (FA) used to solve the multi objective optimal power flow to identify the optimal setting of Static VAR Compensator (SVC) and optimal location is identified by using sensitivity analysis when the system is operating under normal and overloaded conditions. Sensitivity analysis based Voltage collapse proximity Index is proposed for placing the SVC at appropriate location under normal and over loaded conditions. Once the location to install SVC is identified, the optimal allocation of SVC is determined through firefly algorithm based A multi-criterion objective function comprising of four objectives minimize total power loss, minimize total voltage magnitude deviations, minimize the fuel cost of total generation and minimize the branch loading to obtain the optimal power flow. Simulations have been implemented in MATLAB and the IEEE 14-bus, IEEE 30-bus and IEEE 57-bus systems have been used as a case study. The results we have obtained indicate that installing SVC can significantly enhance the voltage stability of power system. Also for the purpose of comparison the proposed technique was compared with another optimization technique namely Genetic Algorithm (GA). The results we have obtained indicate that FA is an easy to use, robust, and powerful optimization technique compared with GA.
TL;DR: The obtained results showed that in the hybrid models the values ofMagnitude of Relative Error (MRE) and Mean Magnitude of relative Error (MMRE) were reduced compared with COCOMO model and also the accuracy of Percentage of Relative error Deviation (PRED) was higher in the Hybrid models.
Abstract: We used Particle Swarm Optimization (PSO) algorithm hybrid with Fuzzy C-Means (FCM) and Learning Automata (LA) algorithms for Software Cost Estimation (SCE) In this paper we test and evaluate PSO-FCM and PSO-LA hybrid models on NASA dataset software projects The obtained results showed that in the hybrid models the values of Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE) were reduced compared with COCOMO model and also the accuracy of Percentage of Relative Error Deviation (PRED) was higher in the hybrid models
TL;DR: In this research two most frequently used algorithms in clustering namely k means and fuzzy c means are used and the fuzzyc means algorithm was found to be more suitable for clustering of library requirements.
Abstract: The Requirement Engineering is the most important phase of the software development life cycle which is used to translate the imprecise, incomplete needs and wishes of the potential users of software into complete, precise and formal specifications. These specifications can be decomposed on application of a data mining techniques, clustering. The process of clustering the requirements allows reducing the cost of software development and maintenance. In this research two most frequently used algorithms in clustering namely k means and fuzzy c means are used. The output generated is then analyzed for evaluating the performance of the two clustering algorithms. The requirements specified by the different stakeholders of the library are used as the input. The data mining tool WEKA was used for clustering. The clustering algorithms were then analyzed for accuracy and performance. On analysis the fuzzy c means algorithm was found to be more suitable for clustering of library requirements. The results proved to be satisfactory.
TL;DR: In this article, the authors present the horizontal representation of data used for dataset preparation in data mining analysis and reduce memory space when evaluated with the cancer dataset, which reduces the complexity of data analysis.
Abstract: To prepare the data set from relational database management system for data mining is very difficult and time consuming task. These prepared data can be used as input in data mining analysis. But traditional structured query language aggregate function returns the records in one column per aggregated group. This paper presents the horizontal representation of data used for dataset preparation in data mining analysis and reduce memory space when evaluated with the cancer dataset.
TL;DR: In this article, the effect of environmental parameters on Global System for Mobile Communication (GSM) and Global Positioning System (GPS) signal strength with respect to weather parameters is analyzed.
Abstract: This work proposes analysis effect of environmental parameters on Global System for Mobile Communication (GSM) and Global Positioning System (GPS). This paper presents variation in GSM signal strength with respect to weather parameters. There are many sources of deviation for both issues, but into this research our main focus on Tropospheric delays. The results show humidity, pressure, temperature and air condition effect signal strength values of GSM and accuracy of GPS. The minimum and maximum measurements were recorded for GSM in the range - 89 and - 41 dBm where -89 is low signal strength and -41 is high signal strength. The accuracy of GPS were calculated and compared at different points. Result of this research showed that the tropospheric delay produce 6 to 14 meters deviation on same landmark at different weather parameters value.
TL;DR: This paper provides an advanced survey over attacks and common threats and the possibility of securing the available spectrum from the attackers.
Abstract: As the wireless communication greatly depends on spectrum utilization, the increase in demand for new wireless services and their application leads to the spectrum scarcity. In order to utilize the available spectrum efficiently, "cognitive radio"- The demanding technology is introduced. It is a dynamic technology that can sense the medium, utilizes the available white spaces, for transmission by detecting its neighboring devices. The cognitive radio targets to increase the efficiency of the spectrum changes without causing any intervention to the licensed users. Since cognitive radio works in the open network space, it increases the chance of the attacker to show intervene on the spectral medium. So, the security becomes the key factor. This leads to the realization of various security threats in the cognitive radio. There are various papers covering the security issues over the threats in cognitive radio, but this paper provides an advanced survey over attacks and common threats and the possibility of securing the available spectrum from the attackers. In addition to that future scope and challenges are also addressed. This survey will help the researchers to identify the space left out and the problems to be attached related to security issues on cognitive radio.
TL;DR: In spite of the variable response to MYMV, the genotypes EC 398897, TM-11-07, TM -11-34, PDM-139, IPM -02-03, IPM-02-14 and MH-521 exhibited resistance in both the locations and these genotypes would be utilized as donors to develop MyMV resistant lines.
Abstract: Mungbean Yellow Mosaic Virus (MYMV) is one of the most important diseases of Mungbean. It is transmitted through whitefly (Bemisia tabaci). The present investigation aimed to identify stable MYMV resistant lines through screening under natural condition. The experimental material consisted of 120 germplasm lines screened under field condition at two locations during kharif, 2013. Screening for MYMV resistance was done by planting infector rows along with the test entries. Results revealed that most of the genotypes studied were categorized as moderately susceptible to highly susceptible in both the locations. None of the test entries appeared to be immune. It was observed that the genotype shows differential response against MYMV at these locations. In spite of the variable response to MYMV, the genotypes EC 398897, TM-11-07, TM-11-34, PDM-139, IPM-02-03, IPM-02-14, Pusa-0672, Pusa-0871, CO-7 and MH-521 exhibited resistance in both the locations and these genotypes would be utilized as donors to develop MYMV resistant lines.
TL;DR: A video steganography algorithm based on Haar Integer Wavelet Transforms and Least Significant Bits (LSB) substitution for data hiding and extraction in Red Green Blue (RGB) components of the video files is proposed.
Abstract: This paper proposes a video steganography algorithm based on Haar Integer Wavelet Transforms (IWT) and Least Significant Bits (LSB) substitution for data hiding and extraction in Red Green Blue (RGB) components of the video files. In this approach, the cover-video is divided into RGB frames and the text in binary form is embedded into the LSBs of IWT coefficients. The embedded text is extracted from stego-video using the reverse process of data hiding. The proposed system was implemented using Audio Video Interleave (AVI) files. The experimental results prove that the proposed system has shown imperceptible modifications in AVI videos that lead to high security and an eavesdropper's inability to detect hidden data. The proposed system is simple and therefore can be used to transfer highly confidential data like military secrets, hospital reports and other data.
TL;DR: A novel scheme based on Wireless Sensor Networks for Ocean Status Notification System (WOSNS) so that the environmental conditions of the oceans can be monitored and is better than other protocols in terms of average delivery ratio, network lifetime and network traffic.
Abstract: Reliable and energy efficient routing protocols are considered as critical issues of discussion in Wireless Sensor Networks (WSN). In this paper, we proposed a novel scheme based on Wireless Sensor Networks for Ocean Status Notification System (WOSNS) so that the environmental conditions of the oceans can be monitored. According to the proposed approach, all the sensed data in each area will be transmitted to the related cluster head; then, they will be forwarded to the nearest sink. We used two sinks in appropriate positions. We used the proposed Smart Inner Routing Algorithm (SIRA) for routing data from the cluster heads to the related sink. Furthermore, we proposed a Binary Recursive Convergent (BRC) algorithm for aggregating data in each area. Multi-hop delivery was used to conduct the routing operations. We also introduced a Bidirectional Duplicate Elimination Technique (BDET to eliminate the duplicate data of the sinks. Simulation results indicated that the proposed method is better than the other protocols in terms of average delivery ratio, network lifetime and network traffic.
TL;DR: An optimization technique called Bacterial Foraging has been used in order to continuously optimize the allocation of resources thereby improving the energy efficiency of the data centre and making it clearly evident that cloud computing has great potential and offers significant performance gains as well as cost savings even under dynamic workload conditions.
Abstract: Cloud Computing is a relatively new technology and aims to offer “utility based IT services”. Cloud Computing is now becoming increasingly popular because of the potential number of advantages that it aims to offer. However, with the growing popularity comes the increasing power consumption. Therefore, there is an utmost need to develop solutions that aim to save energy consumption without compromising much on the performance. Such solutions would also help reducing the costs thereby benefitting the cloud service providers. In this paper, an optimization technique called Bacterial Foraging has been used in order to continuously optimize the allocation of resources thereby improving the energy efficiency of the data centre. The results obtained after simulating a cloud computing environment and implementing the proposed algorithm make it clearly evident that cloud computing has great potential and offers significant performance gains as well as cost savings even under dynamic workload conditions.
TL;DR: The proposed digital signature algorithm gives a new technology for producing effective output of digital signature as a result the signing and verifying of signatures are very fast compared to earlier ones.
Abstract: This paper analyzes the computer security of systems and importance of the digital signature and hashing message algorithm. The proposed digital signature algorithm gives a new technology for producing effective output of digital signature as a result the signing 1 and verifying of signatures are very fast compared to earlier ones. To improve the security and authentication of sending data, this method uses "Message Digest", "IDEA" and "GOST" 2 algorithms. The new message digest algorithm is to provide high security, to transfer data by combination of digital signature algorithm and symmetric key cryptography algorithm. The new hashing algorithm proposed creates a unique digital fingerprint along with symmetric key encryption generated IDEA and GOST algorithms 3,4 . The receiver used the symmetric key and hashing algorithm to form a signature. If this message digest match with the sender digests the message the content will be decrypted and read by sender.
TL;DR: In this paper, the authors investigated the use of waste bricks as waste material for concrete preparation and found that using waste bricks in concrete can improve the strength and durability of concrete especially in areas close to brick furnaces.
Abstract: The present study aims to investigate the use of clay bricks in concrete preparation. In the first phase of the study, the clay bricks as waste materials from building remains were collected and ground by jaw mills and finally graded in the range of standard sand. The first experiments like XRF, water absorption, and unit weight were then carried out on the materials. After that, some samples with substitution percents of zero to one hundred from waste bricks as sand were made and the new concrete parameters such as compressive strength, water absorption and unit Weight were examined. In the second phase, nano SiO 2 in all mixes from the brick waste materials were replaced for the cement and then the experiments of compressive strength and water absorption were done on the samples that contained nano SiO 2 and waste clay bricks. The results clearly revealed that, in light of some positive effect such as a reduction in the concrete unit weight and recycling the waste materials and also the minimum reduction of compressive strength, using brick waste materials may be considered a suitable choice in concrete especially in areas close to brick furnaces. Furthermore, nano SiO 2 can improve the strength and durability of concrete. Conclusively, using waste bricks can be an effective measure in sustainable development.
TL;DR: This work proposes a bit plane slicing of digital image to provide the more security and involves rotation of bit planes to make highly secure image encryption.
Abstract: Image encryption plays a major role in information security. It is mainly used to convert the original image into another form. In this work, we propose a bit plane slicing of digital image to provide the more security. The main aim of BPS is used to divide the digital image into 8 bit planes. The bit plane is further rotated in order to provide better encrypted image and to make hacking more difficult. It focuses on two techniques such as bit plane slicing and image rotation for efficient image encryption. The classification of bit plane is used for analyzing the importance played by each bit of an image. It is used to estimate the each pixel of an image. The proposed technique involves rotation of bit planes is employed to make highly secure image encryption. By this method scrambling of an image is based on efficient technique even it is intercepted, the information cannot be understood. It is mainly useful for image compression because it exhibits high coding efficiency. This method which makes the decryption of an image more difficult compared to other techniques.
TL;DR: A simple Anonymization technique using subclustering is specified which achieves maximum privacy and also utility with minimum execution time.
Abstract: As there are new techniques growing to reveal the hidden information on data, the threat towards those data also increases. Therefore, privacy preservation in data mining is an emerging research area which develops various algorithms to anonymize the data provided for data mining. The existing methodology handles the tradeoff between utility and privacy of data in a more expensive way in terms of execution time. In this paper, a simple Anonymization technique using subclustering is specified which achieves maximum privacy and also utility with minimum execution time. The methodology is explained with algorithm and the results are compared with the baseline method.
TL;DR: In this paper, the authors proposed an extension of multiplicative data envelopment analysis (MDEA) model under variable return to scale (VRS) technology in the presence of stochastic data.
Abstract: One class of models introduced in data envelopment analysis is called multiplicative model. In this paper, the extension of multiplicative data envelopment analysis(MDEA) model under variable return to scale(VRS) technology in the presence of stochastic data was focused on. The log-normal distribution is a family of probability density functions that is frequently used in practical situations. Therefore, in the present study, a stochastic MDEA model under VRS technology was proposed for measuring the stochastic α- efficiency of decision making units (DMUs) with inputs and outputs having log-normal distributions. Moreover, stochastic super-efficiency model was proposed for ranking stochastic α- efficient DMUs in stochastic MDEA model. Finally, an example of the system reliability was presented for 12 different brands of computers to demonstrate our proposed modeling idea and its efficiency.
TL;DR: An intrusion detection system is proposed using Decision Table/Naive Bayes (DTNB) that is able to detect intrusion with a superior detection rate.
Abstract: An intrusion detection system is proposed using Decision Table/Naive Bayes (DTNB). The Proposed system uses a hybrid classifier DTNB that is used to identify possible intrusions. The system is trained using a subset of the NSL KDD Cup dataset. The trained model is then tested using a subset of NSL KDD Cup dataset. The DTNB hybrid classifier is able to detect intrusion with a superior detection rate.
TL;DR: In this paper, the authors discuss various innovations and technological breakthroughs that took place in Indian agriculture during the British period and afterwards and the possible solutions for overcoming this slow down have been discussed.
Abstract: There are myriad innovations that have been part of agricultural transformation in India. This paper discusses various innovations and technological breakthroughs that took place in Indian agriculture during the British period and afterwards. Some of the innovations occurred inadvertently that are believed to have had higher impact on food production and livelihood security. Food security being India's major concern under changing climatic scenario, the reasons for slow down in food grain production in recent past have been looked into with a major emphasis on rice and wheat crops and the possible solutions for overcoming this slow down have been discussed.