Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Approach to Overcome Overlapping of Clusters by Fuzzy k-Means

: Of all the clustering algorithms, the frequently employed methods of partitioning algorithms include k-means, medoids and certain modifications. For K-means, a centroid represents the mean or median point of a group and for K-medoids, wherein a medoid represents the most central point of a data group. We present a hybrid method with both algorithms; k-medoids and k-means to cluster a dataset of thyroid disease drugs and the program is run to generate clusters centred on k-means and k-medoids, followed by enhancing the outcome by implementingfuzzy k-means. Clusterability was carried out by Hopkins statistic and cluster validity by Nbclust resulted in k=3. Both the methods resulted in clusters with negative silhouettes, however, hybrid clustering algorithm resulted in partial overlapping of data points, hence fuzzy k-means algorithm was applied on sub-set of dataset. Finally, of all the six fuzzy algorithms studied, fkm algorithm displayed superior separation of clusters with well-defined data points.
SENTENCE ORDERING IN MULTI DOCUMENT SUMMARY USING LOCALISED CONTEXTUAL INFORMATION

: Relevance of automatic multi document summarization system increases day by day due to the availability of huge amount of textual data in the Internet. Multi document summarization system generate generic summary by extracting most relevant sentences from the input documents. Sentences are ranked based on statistical and /or linguistic information and sentences with high ranks are extracted to generate the summary. Generic summary generated automatically by extraction method may not guarantee cohesion, since summary holds sentences from multiple documents in a random manner. In this paper, we propose a sentence ordering method, which organizes the sentences in the generated summary to improve cohesion. The way the first sentence opens up the topic determines the overall readability of the summary. The most important step in our work is to identify the most appropriate sentence that is to be placed as the first sentence. Overall cohesion of summary is improved, if sentences are related to each other. Positions of remaining sentences are identified by maximizing the similarity between the consecutive sentences through the construction of maximum cost spanning tree using localized contextual information. Our system increases understandability and readability of the summary.
Efficient Subspace Analysis for Anomaly Detection

 Abstract — In today’s era detection of security threats that are commonly referred to as intrusion, has become a very important and critical issue in network, data and information security. In recent times data mining and machine learning have been researched extensively for intrusion detection with the aim of improving the accuracy of detection classifier. KDD CUP’ 99 Data set is the most widely used dataset in research domain. Selecting important feature on the basis of feature selection approach have lead to a simplification of the problem, faster and more accurate detection rates. In this paper, we presented an efficient approach for detecting relevant features from the KDD CUP’99 Data set using subspace method.
Arabic Sentiment Analysis Using Deep Learning: A Review

Summary Social media provides a significant source of public opinions and trends. Recently, the interest in analyzing this publicly available data through sentiment analysis has increased noticeably. The use of deep-learning for sentiment analysis is lately under focus, as it provides a scalable and direct way to analyze text without the need to manually feature-engineer the data. As the work on Arabic sentiment analysis using deep learning is scarce and scattered, this paper presents a systematic review of those studies covering the whole literature, analyzing 19 papers. The review proves a general trend of Arabic sentiment analysis performance improvement with deep learning as opposed to sentiment analysis using machine learning.
An Efficient Mining of Frequent Itemset Purchase on Retail Outlet using Frequent Itemset Ultrametric Tree on Hadoop

- Mining frequent itemset purchase in a retail outlet is a very strenuous job. As extracting the frequently occurring itemsets over a large heterogeneous database is a core problem. Existing parallel mining algorithm for frequent itemsets does not support automatic parallelization, load balancing, synchronization and fault tolerance over a large cluster. Hence as a solution to these problem, an improvised algorithm called frequent itemset ultrametric tree algorithm using MapReduce programming model on Hadoop is used. Here in this technique, we implement three MapReduce jobs to perform the mining task.
A Study on Clustering Based Methods

-- Data mining is a process of mining information from huge data sets and making it into a logical form for supplementary purpose. Clustering is an important step in data mining applications and data analysis. Clustering is a method of arranging objects with similar properties into a single group. Data mining is done by passing through various phases. The process of mining can be done by using two learning sets, supervised and unsupervised learning. The clustering is an unsupervised learning. It has following categorized partition-based method, density-based method and grid-based method, hierarchical-based method. A good clustering method will produce high superiority clusters with high intra-class similarity and vice-versa.
Physical Exercise and Psychological Well-Being: A Prognosis for Cost-effectiveness of Corporate Health Care

The purpose of this paper is to predict the cost-effectiveness of a preventive health care project based on physical exercise that will take place at Medicon Village, Lund, in the fall of 2016. Data from the Health Survey for England is used to develop an empirical model with individual fixed effects that estimates the relationship between physical exercise and psychological well-being. The frequency of different kinds of physical exercise is used to explain several indicators of psychological well-being. The empirical model is then matched with survey responses collected from Medicon Village employees in order to realistically predict the impact of the project. The results show that the empirical model fits the collected survey data well. Prediction intervals are calculated by inserting survey respondents’ activity levels into the empirical model. This results in estimated levels of psychological well-being. 97.9% of these prediction intervals accurately cover the respondents’ real reported value of given indicators of psychological well-being. The cost-effectiveness of the preventive health care project will differ for every participating individual, due to different base line health statuses and sporting backgrounds, but also for every measure of psychological well-being. Physical exercise also does not impact all the indicators of psychological well-being equally. The model developed in this paper has the ability to take this into account and can predict the cost-effectiveness of the project for any given individual. Three examples of cost-effectiveness estimates based on our survey responses are presented in the results section. (Less)
Oral Cancer Biomarkers-as Powerful Diagnostic and Prognostic Tools

Oral carcinogenesis is considered to be a highly complex, molecular and histologically multistage process, which is often localized in the oral cavity, may metastasize and spread out resulting in the onset of Squamous Cell Carcinoma of Head and Neck (SCCHN). Among all the oral cancers, the frequency with which OSCC (Oral Squamous Cell Carcinoma) (arising from the lining mucosa) occurs is the highest [1-3], making OSCC the sixth most widespread malignancy [4]. In spite of this, incidence of Oral Cancer is more predominant in the Southeast Asian countries [5] owing to excessive smokeless tobacco products consumption [6] as a consequence of nitrosamines mediated DNA adduct formation followed by uncontrolled proliferation [7]. One of the most important risk factor for the oral cancer to develop in western countries is the consumption of tobacco and alcohol independently or together [8, 9] (synergistic effect) or infection with human papilloma virus, ISSN: 2319-7706 Volume 5 Number 1(2016) pp. 209-220 Journal homepage: http://www.ijcmas. com
The Effectiveness of the Accounting Information System Under the Enterprise Resources Planning (ERP) A Study on Al Hassan Qualified Industrial Zone’s (QIZ) Companies

This study aimed to identify the effectiveness of the accounting information system for companies that adopting "Enterprise Resource Planning (ERP)" systems, and its relationship with the quality of accounting outputs (information) and the internal control. To achieve the goal of this study, the researcher chooses companies that located in Al Hassan Industrial Zone, particularly companies that uses ERP systems. A questionnaire designed and distributed to a sample of accountants and financial managers who works at such companies. The researcher used means and frequencies to describe the sample of the study and the questionnaire responses besides t test to test the hypotheses of this study. The results showed that the integration of accounting information system within the ERP system improving the quality of accounting outputs and the internal control in companies. More studies are required on this field to support the result of current study and to expand the accounting literature on this issue. Companies also recommended to adopt ERP systems because it will improve their performance
Collagen: New Dimension in Cosmetic and Healthcare

Collagen is one of the natural biomaterials used in cosmetic preparation. It is the most abundant protein in mammals which is obtained from many sources such as bovine, porcine and human. Collagen based cosmetics are in demand now a days though safety issues related with allergies are still main concern of consumers. The collagen is used for different purposes in cosmetic and medical field such as dermal filler, skin substitute and facial products. Use of collagen in medical field is useful depending upon the patient’s requirement. It is useful in pathological conditions like in severely burn patients, patients with chronic wounds such as foot ulcers due to diabetes and venous leg ulcers etc however, use of collagen injection as anti-aging/anti-wrinkle biomaterial need to be further investigated in large population study to check the side effects in long term. Review Article Samad and Sikarwar; IJBCRR, 14(3): 1-8, 2016; Article no.IJBCRR. 27271 2
Providing Address Anonymity in Multicast Multi-hop Wireless Sensor Networks

- Due to the open nature of a Wireless sensor network(WSN),it is relatively easy for an adversary to eavesdrop and trace packet movement in the network, in order to capture the nodes physically. The nodes in WSN can sense, collect and disseminate information for many different types of applications . One of these applications is subject tracking and monitoring, in which monitored objects often need protection, from different adversaries. An adversary might trace the messages in the WSN to find the source node that sent the message. The adversary might try to disrupt the source and the destination node and hence the entire network to fulfill his agenda. Hence the question is :how do we hide the locations of the communicating nodes, from the adversary? This question is relevant in many applications like battlefield surveillance, patient monitoring, etc. In this paper, we discuss the core techniques used to provide location privacy within WSN, in relations to the assumptions about the adversary’s capabilities. Further, in this paper we propose a novel anonymity scheme to hide the identities of the nodes that participate in the message transmission.
DESIGN AND DEVELOPMENT OF SMALL PUNCH TESTING FIXTURE TO PREDICT THE MECHANICAL PROPERTIES OF CORTICAL BONE

A simple, versatile test rig for testing small bone samples was built up. This elaborates new features, in comparison to the previous one using big samples, as an alternative approach to predict the properties by using wide range of samples with varying thickness, shape and geometry. Testing fixtures are design and developed as per the shape of miniature samples. The displacement is measured with extensometer of precise range. The test rig is used on table top universal testing machine Tinius Olsen H50 KS. This technique gives a method of acquiring up-to-date mechanical properties of components expending a little measure of material in contrast with prerequisite for standard conventional methods. In most cases, the full-size specimen is generally obtained by decimating the parts. In these cases, small specimen testing innovation has advanced out of need to create material of parts used in nuclear power generation system, petroleum industry, chemical plants, thermal power station etc.
Screening for Physical, Phytochemical and Antimicrobial Activities of Leaf Extracts of Sapindus

The crude extracts from leaf of Sapindus emarginatus Vahl. in different solvent, were subjected to pharmacognostic and fluorescence analysis, phytochemical and antimicrobial screening against selected gram positive, gram negative bacteria and fungus. Methanol and aqueous extracts of leaf were used for phytochemical screening and antimicrobial activity. Phytochemical studies indicated that the leaf contain a broad spectrum of secondary metabolites. Carbohydrates, alkaloids, phenol, tannins, fixed oils & fats, gums & mucilage and flavonoids were predominantly found in both the solvent extracts of leaf followed by steroids, saponins and proteins. Both the extracts showed varying degree of inhibitory potential against all the tested bacteria. The aqueous extract showed the highest activity against Escherichia coli (36mm) and Pseudomonas aeruginosa (36mm) but methanol extract of leaf had maximum against Pseudomonas aeruginosa (29mm). In the case of antifungal activity methanol extract of leaf had higher inhibitory action against Aspergillus niger. Aqueous extract of leaf had no inhibitory action against the test fungus.
feature-An Effective Classification and Novel Class Detection of Data Streams

— Data stream classification suffered from the problem of infinite length, concept drift, concept-evolution and feature-evolution in data mining community. Usually data streams are infinite in length and it makes difficult to store and use all the historical data for training. Several research is eliminating the concept-evolution and feature-evolution concepts. Recently, many researchers have been focused on data streams as an important approach against huge database mining instead of mine the entire database. In this paper, an efficient approach is proposed for classification and novel class detection of data streams. The proposed method uses the outlier detection method to remove the unwanted data present on the data streams. Also, this approach uses the Nearest Neighbor algorithm and the Naive Bayes classifier concepts for novel class detection. The performance is evaluated with respect to error rates, final word count, speed and time. The result shows that the proposed method for classification and novel class detection provides better results than the existing techniques.
Attitudes and Behavior Towards Sunlight Exposure and Knowledge About Vitamin D Among Omani Female University Students

The present study was carried out to assess the knowledge, awareness, and basic concepts about vitamin D along with attitudes and behavior practice towards sunlight exposure among Omani female students. A cross sectional study with 309 respondents was conducted among female students studying in A’Sharqiyah University, Ibra, Sultanate of Oman. A pre-designed and self-administered questionnaire was distributed to all students in order to collect the information regarding their knowledge, behavior and attitude about vitamin D and sun exposure. The present study observed that 90.5% students were aware of Vitamin D and majority of them (90.6%) indicated sunlight as the most important source of vitamin D. Among all the participants, 73.5% and 69.9% have also chosen incorrect responses for fruits and vegetables, respectively, as important sources of vitamin D. Despite having more knowledge about vitamin D, awareness and basic concepts in terms of current recommended daily dose was very low (6.8%) and most of the students were not aware of the quantity of their vitamin D supplement intake (61.5%). Only 25.2 % reported valid response regarding the exposure to sunlight time needed to get enough vitamin D. Female students showed negative behavior and attitude in terms of low frequency of sunlight exposure (> 3 times/week, 23.0%) and use of sunscreen products and ointments (53.7%). Educational institutions were among one of the important sources of information about vitamin D (73.8%). The major findings of this study demonstrated the ignorance, lack of consistency and confusion between knowledge, awareness and attitude among female students. Moreover, a negative approach toward exposure to sunlight may prevent the students from obtaining beneficial effects from sunlight and could predispose them towards vitamin D deficiency or insufficiency status. Media and primary health care centers should play a vital role in creating more awareness and knowledge about the Vitamin D in female population.
Image Processing for Hazy Weather Conditions

: Accidents due to the hazy vision in adverse atmospheric conditions is not an issue limited to a region. It is observed worldwide that even after developing the road safety knowledge the accidents in hazy atmosphere are not reduced. These are due to some constraints like blurred vision in hazy conditions in which human eyes cannot detect vehicles or other objects coming in front of vehicle. To overcome this issue there should be some interface between the driver and the objects coming in front of vehicle. The issue occurs while driving in hazy environment and can be avoided by providing an interface which will store the video in form of frames at a speed specified by the camera module used on the front panel of the vehicle. The video stored in format of frames will be processed through the Raspberry Pi which is a series of small single board computer. There will be a provision for the driver to turn on the system whenever it is necessary by pressing a button and then there will be a TFT display provided inside the vehicle to visualize the objects coming in front of the vehicle in advance to the driver.
Source Code Summate using Semantics and Query

In the software evolution process a developer must analyze the source code in order to understand the entities in it. In general this analysis is done manually which takes lots of time and is a tedious task. The other option is to use automated source code summarization techniques. In most of the cases the developer will not analyse the total code he needs to analyse only one entity like packages or classes or methods or other entities in the source code. But all the Existing techniques provide the summary of the total code. Large software applications contain huge number of packages, classes, methods and other program entities so summarizing the total code is time consuming and tedious process. In this paper we propose a novel source code summarization technique which is based on the developers query and semantic content of the source code. Based on the query the summary is generated for the entities which the developer is interested.
Harmonic Estimation- An Essential Feature of Smart Grid

-This paper presents an adaptive filter for fast estimation of harmonic and frequency components of a power system voltage or current signal corrupted by noise with low signal to noise ratio (SNR). This new algorithm is based on an objective function often used in independent component analysis for robust tracking under impulse noise conditions. Instead of choosing the step size η and the parameter β of the cost function by trial and error, an adaptive particle swarm optimization technique is used alternatively to obtain both η and β to reduce the error between the observed voltage or current samples and the estimated ones. Using the optimized values, the amplitude and phase of the fundamental and harmonic components are estimated. A smart grid is a system which includes a variety of operational and energy measures including smart meters, smart appliances, renewable energy resources, and energy efficiency resources. Electronic power conditioning and control of the production and distribution of electricity are important aspects of the smart grid . To test the effectiveness of the algorithm, for use in smart grid applications , several time-varying power system signals are simulated with harmonics, inter-harmonics and decaying dc components buried in noise with low SNR and are used to estimate the frequency and harmonic components. The results so obtained is found satisfactory and given to prove the validity of the proposed algorithm.
GCC over Heterogeneous Wireless Ad hoc Networks

Congestion control in wireless networks has been extensively investigated over the years and several schemes and techniques have been developed, all with the aim of improving performance in wireless network. With the rapid expansion and implementation of wireless technology it is essential that the congestion control problem be solved. This paper we propose to control the congestion and error in network using Forward Error Correction (FEC) technique, which will avoid the error. Hybrid Resource based Congestion Control (HRCC) which will reduce congestion in transmission channels and show that a combination of queue-length-based scheduling at the base station and congestion control implemented either at the base station or at the end users can lead to fair resource allocation, queue-length stability and reduce congestion in transmission channels.
Abandoned Object Detection with Security Alert Using Smart Phone

— Abandoned object detection is a technology that deals with detecting unattended, unknown objects of a certain class for a period of time. Detecting abandoned object is a very important task in places where there is high security threat e.g. terrorist attacks. In earlier methodologies there were certain drawbacks such as only security alarms used to be raised, accuracy rate of detection was low in case of static environment, and unwanted objects were misunderstood as abandoned. The proposed system consists of dynamic or real time environment and capturing of live streaming videos. In the proposed System, a new concept which is being introduced is the human detection using the RGB to HSV conversion algorithm. The major concern while detecting an abandoned object is when a human is misunderstood as abandoned object and false alarm is raised. To avoid such false alarms the proposed system uses skin colour thresholding on the focused blob and analyse if human or not. If the system displays human features then the detected object will be ignored and no alarm will be raised. Otherwise, the detected abandoned object is captured and an alert is sent to the security in-charge through SMS and Electronic Mail using wifi facility. For better security purpose the live video feed is provided on an Android Application.