Miracle-dz/UniFAR-FTUs huggingface dataset:
CLUSTERING OF MEDICAL DOCUMENTS USING SYMPTOM/MEDICATION NAMES

Clinical documents contain huge amount of medical data. This data can be used for medical treatment of various diseases and their symptoms along with their recommended medications. Data mining techniques are applied on this clinical data, which is an important source to improve the current healthcare system by making it more proficient. In this paper, we have developed a method for clustering of the clinical documents. The clinical documents are obtained from different hospitals and websites. Pre-processing of textual data is done to amplify the performance of Clustering. We have used different tools like MedEx and MetaMap to fetch essential data from clinical narratives. MedEx is used to fetch medication data and MetaMap is used to get symptom names which are related to patient. The multi-view Non-negative matrix factorization (NMF) is used to cluster clinical documents. Our experimental result shows that, as the number of clinical documents increases processing speed decreases to get the result.
The study of the protective effect of vitamin E against cypermethrin toxicity on testicular histology in mice

Cypermethrin is pyrethroid insecticide that is used worldwide for pest control in agriculture and household use. Vitamin E is a potential antioxidant protecting cells from oxidative stress. The aim of the present study was to investigate the protective effect of vitamin E on cypermethrin-induced changes in mice testis. Forty adult male albino mice,were divided into four groups: group I: served as control given corn oil; group II: received cypermethrin (2.8 mg/kg b.wt.) in corn oil; group III:received vitamin E (100 mg/kg b.wt.); group IV:received both cypermethrin and vitamin E. All treatments were given for 14 days.Light and electron microscopic demonstrated that cypermethrin induced atrophic changes in Leydig cells, thickening of seminferous tubule basement membrane with increased electron density of spermatogonia nuclei and cytoplasm. Sertoli cells vacuolation and appearance of abnormal spermatids were demonstrated. In vitamin E treated group normal testicular parenchyma was observed. In contrast, vitamin E given with cypermethrin result in significant improvement in tubules and Leydig cells and amolerated cypermethrin toxicity. Conclusion: showed that administration of vit E can protect against.The results cypermethrin induced oxidative damage in mice testicular tissue. [Turki M. Al-Shaikh. The study of the protective effect of vitamin E against cypermethrin toxicity on testicular histology in mice. J Am Sci 2013;9(4):615-621]. (ISSN: 1545-1003). http://www.jofamericanscience. org. 68
An Adaptive Selection of Gradient Magnitude Threshold in Anisotropic Diffusion of MRI

Anisotropic diffusion filter, being an edge preserving non-linear image restoration method, has been of wide acceptance and of intrinsic interest among the researchers in image processing domain. But judicious choice of its operational parameters is mandatory to ensure the optimum performance. Its operational parameters include number of iterations, threshold of gradient modulus etc. These operational parameters are usually selected through trial and error, through qualitative inspection of restored image. The noise retains even after the restoration and the image is likely to get blurred if the number of iterations is not wisely chosen. The selection of threshold of gradient modulus is not image driven and usually blindly chosen. Moreover, in anisotropic diffusion the diffusion coefficient is computed from the local gradient. Even the noise pixels may exhibit high local gradients in heavily corrupted images. The fine details in the image may be lost during the iterative smoothing unless the operational parameters are carefully selected. The main objective is to propose an adaptive image driven estimation of threshold of gradient magnitude, rather than setting it manually. The performance of the modified anisotropic diffusion will be compared with conventional P-M model in terms of the ability to preserve edges during restoration.
Automatic Skew Detection and Localisation of Vehicle License Plate Using Hough Transform

— Automatic Skew Detection and Localization of Vehicle License Plate Using Hough Transform are used to identify a vehicle by its number plate. The proposed algorithm consists of three major parts: Extraction of plate region, segmentation of characters and recognition of plate characters. The proposed license plate localization algorithm is based on a combination of several algorithms that include Thresholding, Edge Detection and Hough rectangular transforms. The process flow is, initially the Thresholds are performed on a plain image. Then edge detection is applied to the obtained image and then location is found using top hat transform and then the skew is detected by using the Hough Rectangular Transform and correct it and finally get the localized number plate from the digital image as a deskewd image. After that Connected component analysis is used to segment the characters individually and finally statistical based template matching is used for recognition of plate characters.
A Novel Compact Size Dual Notched Bands UWB Elliptical Monopole Antenna

176 Abstract— In this paper, a new compact ultra-wideband printed elliptical monopole antenna is presented. The proposed antenna operates over a wideband from 2.85 to 15.4 GHz for voltage standing wave ratio (VSWR) less than two. Two modifications are introduced to enhance the frequency-impedance characteristic of the presented elliptical monopole antenna. The first one is to chamfer the edges of the ground plane with 45°angle. The second modification is to use asymmetrical in length finite ground planes. By utilizing a symmetrical L-shaped slot and an inverted U-shaped slot embedded in the radiating patch and feed line respectively, a dual band notched characteristic were achieved. These bands are 3-4 GHz and 5-6 GHz used for WiMAX and WLAN operations. The center frequency and the width of the notch bands are adjusted by varying the length and the width of the slots. The antenna shows omnidirectional radiation pattern characteristics with acceptable gain. Compared with other recently proposed dual band notch antennas, the proposed antenna exhibits advantages of a compact size, simple structure, wide bandwidth and good band-notch characteristic. The simulation results are obtained and optimized using a commercial electromagnetic simulator CST Microwave Studio.
Wheat Yield Prediction Using Artificial Neural Network and Crop Prediction Techniques (A Survey)

This survey paper represents the forecasting techniques in the field of Agricultural (Wheat crop). Paper shows all the past research development of forecasting in all areas. The major forecasting models are Statistical, Metrological, Simulation, Agronomic, Remote Satellite Sensed, Synthetic and Mathematical in the field of Agricultural Yield. This paper shows compact combination of all these models and shows why Neural Network Model is important from other models for nonlinear data behavior system like wheat crop yield prediction.
An Effective Approach for Automatic Bug Triage Techniques

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The process of fixing a bug is called bug triage that goal is assigned to a developer for new coming bug. In a software firm, they spend their time and price to manage the bugs. So to reduce time and price of manual work in software firm they use automatic bug triage. By automatic bug triage, find predicted developer to resolve the bugs. In proposed approach, we used data reduction techniques and machine learning algorithm. To enhance standard of data, we used data reduction techniques, for that feature selection and instance selection techniques are used. We used feature selection and instance selection techniques at the same time to improve the accuracy of automatic bug triage. Also, we used machine learning technique for bug triaging system. We have added a new module here which will describe the status of the bug like whether it assigned to any developer or not and it is rectified or not. In addition, the load between developers based on their experience is re-balanced. The experimental result shows high prediction accuracy by using data reduction techniques and machine learning algorithm.
Optimised Link State Routing Protocol Testbed and Performance Evaluation

Summary This paper discusses the implementation of OLSR routing protocol on TL-MR3040 routers for MANET experiment. To date, many devices are equipped with wireless module; however most system is set to be in the form of structured communication. Indeed the current wireless devices such as WiFi router and access point has the ability to communicate in ad hoc fashion. However, a compatible protocol is required to enable such devices to operate effectively. Nevertheless, the heterogeneity of the wireless communication frequently poses a challenge for the device to route packet in the network. The OLSR is a proactive MANET routing protocol which may create mesh topology and operate effectively to assist wireless devices to self-configure routing path when topology changes. To see the feasibility of OLSR routing protocol on real-world environment, the paper presents the implementation and experiment conducted on TL-MR3040 routers equipped with the OLSR routing protocol. Results from experiment show that the OLSR communication between the routers is viable. In addition, the performances of the routers are evaluated in terms of bandwidth, ETX, and the self-healing mechanism ability.
Influence Of Corporate Image On Brand Personality: A Customers’ Perspective

Brand personality has a great influence on brand positioning, buying decision and loyalty of the consumers. A favorable, strong and unique perception of the brand in the mind of customers distinguishes it from those of competitors. Certain brands enjoy high market share and price as they have better perceived quality, greater awareness, strong brand association and higher customer loyalty. Hence understanding and meticulously creating the personality of the brands plays a vital role in its success and failure. The present study assesses the influence of corporate image on its brand personality.
A New Method for Instantaneous F 0 Speech Extraction Based on Modified Teager Energy Algorithm

 Abstract — A new method for instantaneous F 0 extraction from the speech signal based on Modified Teager energy algorithm is presented. Applications to Thai tone classification are considered. The need for a fast and reliable method for pitch detection, estimation and tracking is crucial for an investigation on the problem of tone classification in a Thai speech recognition system. The advantages of the proposed method include reduced computational complexities and improved resolution due to the availability of pitch estimates at every sample location. Preliminary results on F 0 extraction of the five Thai tones spoken in isolation suggest comparable or better performance than the typical frame-based autocorrelation method.
Opportunistic Data Forwarding In MANETS through Proactive Source Routing

: In multi hop wireless networking, Opportunistic data forwarding has drawn much attention, with most research conducted for stationary wireless networks. Opportunistic data forwarding has not been widely utilized in mobile ad hoc networks (MANETs),the reason behind this is the lack of an efficient lightweight proactive routing scheme with strong source routing capability. In this paper, proposed a lightweight proactive source routing (PSR) protocol. PSR can maintain more network topology information than other protocols like distance vector (DV) routing to facilitate source routing, although it has much smaller overhead than traditional DV-based protocols [e.g., destination-sequenced DV (DSDV)], link state (LS)-based routing [e.g., optimized link state routing (OLSR)], and reactive source routing [e.g., dynamic source routing (DSR)]. This paper concentrates on reducing the overhead at the base line protocols, then testing to the better data transportation. Network Simulator (NS-2) help in testing and implementing to this paper for effectively reduced to the overhead in the data transportation.
Recognition of Devanagari Handwritten Numerals using Two Different Approaches

— This paper proposes two methods for automatic recognition of Handwritten Devanagari Numerals. In first method, Grid features i.e. structural features are extracted and minimum distance is calculated using these features for classification. In second method, ICZ (Image Centroid Zone) & ZCZ (Zone Centroid Zone) features based on distance information are extracted and given to an already trained Neural Network for classification. The accuracies obtained using two approaches are evaluated.
Collaborative Filtering

Social voting is a promising new feature in online social networks. It has distinctive challenges and opportunities for suggestion. In this paper, we increase a set of matrix factorization (MF) a nearest-neighbor (NN)-based recommended systems (RSs) that explore user social network and group association information for social voting recommendation. During experiments with actual social voting traces, we express that social network and group association information can drastically progress the popularity-based voting advice, and social network in order dominates group association sequence in NN-based approaches. We as well observe that social and group information is much more precious to cold users than to heavy users. In our experiments, simple meta path based nearest neighbor models outperform computation concentrated on matrix factorization models in hot voting recommendation, while user's preferences non-hot votings can be better mined b factorization models. We further put forward a hybrid RS, bagging distinct single approaches to get the best top-k hit rate.
Performance Enhancement of RSA Cryptography Algorithm by Membrane Computing

— The problem of using RSA algorithm in cryptography is the long time it takes for the encryption process. To overcome the problem, RSA algorithm uses short messages. In this paper we make analysis for the RSA public key protocol in the framework of membrane computing to develop a membrane model of RSA algorithm with performance improvement. The approach has been validated by developing a simulation program in C++ of RSA algorithm using the property of parallel computing of membrane environment to enhance encryption/ decryption time of the RSA algorithm. Comparing the encryption time results using normal RSA algorithm and the developed model, it was proved that the developed algorithm is faster than the normal one by 30% approximately.
Interpretive Structural Modelling (ISM) approach: An Overview

Interpretive structural modelling (ISM) is a well-established methodology for identifying relationships among specific items, which define a problem or an issue. This approach has been increasingly used by various researchers to represent the interrelationships among various elements related to the issue. ISM approach starts with an identification of variables, which are relevant to the problem or issue. Then a contextually relevant subordinate relation is chosen. Having decided the contextual relation, a structural self-interaction matrix (SSIM) is developed based on pairwise comparison of variables. After this, SSIM is converted into a reachability matrix (RM) and its transitivity is checked. Once transitivity embedding is complete, a matrix model is obtained. Then, the partitioning of the elements and an extraction of the structural model called ISM is derived. In this paper, key concept of ISM approach is discussed in detail
An Efficient Algorithm for Mining Frequent Sequential Patterns and Emerging Patterns with Various Constraints

 Abstract — In many cases, sequential pattern mining still faces tough challenges in both effectiveness and efficiency. On the one hand, there could be a large number of sequential patterns in a large database. A user is often interested in only a small subset of such patterns. Presenting the complete set of sequential patterns may make the mining result hard to understand and hard to use. On the other hand, although efficient algorithms have been proposed, mining a large amount of sequential patterns from large data sequence databases is very expensive task. If we can focus on only those sequential patterns interesting to users, we may be able to save a lot of computation cost by those uninteresting patterns. Many types of constraints can be pushed in sequential pattern mining like item constraint, aggregate constraint, length constraint, gap constraint, duration to enhance the performance.
Survey on Security Algorithum Using Skyschild Technique for Defence System on DDOS Attack

: Distributed Denial of Service (DDoS) attacks are a virulent, relatively new type of attack on the availability of Internet services and resources. DDoS attackers infiltrate large numbers of computers by exploiting software vulnerabilities, to set up DDoS attack networks.These unwitting computer are then invoked to wage a coordinated, large-scale attack against one or more victim systems. As specific counter measures are developed, attackers enhance existing DDoS attack tools, developing new and derivative DDoS techniques and attack tools. Rather than react to new attacks with specific countermeasures, it would be desirable to develop comprehensive DDoS solutions that defend against known and future DDoS attack variants. However, this requires a comprehensive understanding of the scope and techniques used in different DDoS attacks. This paper attempts a comprehensive scoping of the DDoS problem. We propose new taxonomies to categorize DDoS attack networks, to classify the different techniques used in a DDoS attack, and to describe the characteristics of the software tools used in setting up a DDoS attack network. These taxonomies help us to understand the similarities and differences in DDoS attacks and tools, and the scope of the DDoS problem. Given this new understanding, we propose classes of countermeasures that target the DDoS problem before, during and after an actual DDoS attack. In order to be an effective service, the DDOS attack must be detected and mitigated quickly before legitimate user access the attackers target. The group of systems that is used to perform the DDOS attack is known as the Botnets. These paper introduces the overview of the state of art in DDOS attacks detection stratergies
Energy-efficient sleeping technique in cellular network

Presently days the greater part of the people groups are utilized portable phones, therefore the number of base stations and base station utilization’s are additionally increased. The expanding interest of high limit in cell systems requires enormous vitality consumption. Thus, energy proficiency is turned out to be really objective in cell networks. In a phone network, the base stations are utilized more measure of energy. So, energy effectiveness component is connected to the base stations. In this case, we have used a mechanism to on/off base stations according to the users. If a base station does not contain any client then it goes into the sleeping mode, otherwise, it proceeds to its dynamic mode. In this case, a user-centric clustering mechanism is considered. In this technique another system is likewise used, this case the base stations check their closest neighbor base stations. Then tally the number of active base stations and sleeping base stations. If any client needs to interface another client with another base station and the majority of the base stations are sleeping. At, this case the resting base stations are naturally going into the wake-up state. And help to associate the clients.
Speckle Noise Removal Using Dual Tree Complex Wavelet Transform

Dual Tree Complex Wavelet Transform (DTCWT),is a form of discrete wavelet transform which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts.In this paper, the dual-tree complex wavelet transform (DTCWT) based despeckling algorithm is proposed for SAR images by considering the significant dependences of the wavelet coefficients across different scales. The DTCWT has the advantage of improved directional selectivity, approximate shift invariance, and perfect reconstruction over the discrete wavelet transform.The wavelet coefficients in eachsubband are modeled with a bivariate Cauchy probability density function (PDF) which takes into account the statistical dependence among the wavelet coefficients. The simulation results show that this method is faster and gives better performance when compared to the conventional discrete wavelet transform.
Accuracy Confined Access Control (Acac) For Privacy Preserving Data Streams

Privacy preserving data mining is a rising field of research which is concentrating on the two conflicting objectives (i) Utility and (ii) Privacy. In recent years many access control mechanisms and privacy protection mechanism have been proposed for the ceaseless data streams. Access control mechanisms for a data stream permits access to approve sliding window by just taking into account the consent utilized on each roles (role-based access control). Privacy protection mechanisms accomplishes privacy prerequisites by generalization of the stream data. Generalization produces imprecision results which can be reduced by delaying the publishing of stream data which in turn prompts to false-negatives. The challenge is to optimize the increase in imprecision due to the overlap of the rectangle bounds. To enforce accuracy confined access control for privacy preserving data stream an indexing mechanism of R*-tree is formulated that effectively reduces the imprecision and produces the optimized results.
A Survey on Contextual Operation using pair wise Ranking and COT for Recommender Systems

The interest for universal data preparing over the Web has required the improvement of setting - mindful recommender frameworks fit for managing the issues of data over-burden and data sifting. Contemporary recommender frameworks saddle setting - mindfulness with the personalization to offer the most exact proposals about various items, administrations, and assets. Nonetheless, such frameworks run over the issues, for example, scantily, cool begin, and versatility that prompt to uncertain suggestions. The cutting edge setting demonstrating techniques for the most part regard settings as specific measurements like those of clients and things, and catch importance's amongst settings and clients/things. In any case, such sort of significance has much trouble in clarification, e.g., it is not natural that a client is more important to weekday than end of the week. A few takes a shot at multi-area connection forecast can likewise be utilized for the setting mindful suggestion, yet they have constraints in creating proposals under a lot of relevant data. Persuaded by late works in characteristic dialect handling, we speak to every setting esteem with an idle vector, and model the relevant data as a semantic operation on the client and thing. Moreover, we utilize the relevant working tensor to catch the regular semantic impacts of settings. For the relevant data of every client thing communication, the logical operation can be demonstrated by duplicating the working tensor with idle vectors of settings. However a client thing collaboration results can be created under particular relevant data yet can't be yielded under other logical circumstances. So we propose a pairwise positioning imperative on the relevant data.