Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Sampling for Class Balancing with Machine Learning Technique for Intrusion Detection System

: Information security is becoming a more important issue in modern computer system. Intrusion Detection System (IDS) as the main security defensive technique that can effectively expand the scope of defense against network intrusion. Data Mining and Machine Learning techniques proved useful and attracted increasing attention in the network intrusion detection research area. Recently, many machine learning methods have also been applied by researchers, to obtain high detection rate. Unfortunately a potential drawback of all those methods is that how to classify attack or intrusion effectively. Looking at such inadequacies, the machine learning technique on balanced classes of data is applied for obtaining the high detection rate. Also, use of internet is increasing progressively, so that large amount of data and it security is also an issue. Sampling technique is one the solution for large datasets. This work proposes a sampling technique for obtaining the sampled data. Sampled dataset represent the whole dataset with proper class balancing. Imbalanced classes can be balanced by sampling techniques. The purpose of this paper is to propose attack classification framework based on a different model. This model also based on machine learning and sampling to improve the classification performance. The proposed work is tested on basis of Accuracy, Error rate, Detection rate and False Alarm rate. KDD CUP'99 dataset used for the approach proposed in this paper. This work suggests the framework for classification of abnormal and normal data and detect intrusions even in large datasets with short training and testing times.
Quality Control of Platelets Concentrates; an In Vitro Fate Prediction Model System of PCs Transfusion

Introduction: We previously described that metabolic resting preserves old and cold platelets (PLTs) concentrates (PCs). In Badlou et al. 2006 we have established that P-selectin involved as an intermediate in binding, and the combination of PS exposure with (-out) changes in GPIb in phagocytosis of PCs. Using a standard threshold over the interaction between donors PLTs and patient’s phagocytes might increase success of transfusion, and decrease side effects, pretransfusion. The aim of this study is to introduce a novel method, which could be used as an in-vitro prediction model system to envisage PCs fate, posttransfusion. Materials and Methods: Human PCs were stored for different periods to obtain a wide range of surface expressed P-selectin and-PS exposure. The quantitative change in GPIb was deduced from decreased binding of an anti GPIb- antibody measured by FACS flowcytometry. Correlations established in RT stored-PCs were compared with PCs stored at 0°C, and metabolic suppressed stored at 4°C (MSP4). Results: Qualitative and quantitative analysis revealed that ‘good PCs’ which had low P-selectin and PS exposure, and high GPIb expression were not removed by phagopcytes. Comparison studies between C22, C0 and MSP4 showed that at a given amount of PS exposure and GPIb expression, phagocytes immediately removed ‘bad PCs’. Threshold- dependent removal might be caused by ageing-dependent lesions. At high GPIb expression was phagocytosis almost 0%, when GPIb expression decreased below certain degree phagocytosis increased, remarkably. Discussions: Our results signify that these chosen three markers combination measurements are reliable markers for phagocytic (ir-) responsiveness. In the near future, when these thresholds established as standard thresholds then any (Para-)medic can predict on the basis of relatively simple analysis, whether delivered PCs from the blood banks are immunogenic or not. In conclusion, our introduced in-vitro model system could be used as the quality control of any randomly selected and prepared PCs, pretransfusion.
MAC 802.11 Protocol with Dynamic Bandwidth Allocation for Data Transmission in Network

: Medium access control protocols and its effect on capacity are important aspects in communication system design for any shared medium like wireless. In multi-hop ad hoc networks that use a distributed and contention based channel access mechanism such as those specified in the IEEE 802.11 standard, the capacity of individual links are not known. Existing methods in literature attempt to solve this using measurement based approaches. This thesis proposes graph theoretical and real-time approaches to estimate the capacities of individual links in a multi-hop ad hoc network and uses analytical modeling to derive node throughputs and successful transmission probabilities of individual nodes in multi-hop ad hoc networks.
Contamination of Heavy Metals, Source, Effects on Leaving Things and Different Remediation Techniques in Soil: A Review

Different researches showed that contamination of heavy metals in soil has become more and more serious, which affects Both soil fertility degradation and detrimental to human health through food chain causing adverse effects on human health. The concentration of metals beyond Maximum Permissible Level (MCL) leads to number of nervous, cardiovascular, renal, neurological impairment as well as bone diseases and several other health disorders and also computed the macronutrient in the human body. Due to these it needs more attention towards the contamination area using either prevention or minimizing methods of the source of contamination. Different researches mentioned different remediation techniques which involve phytoremediation, lime, phosphates, and different biochar materials. Remediation mechanisms basically consist of two fundamental principles. The first is to completely remove contaminations from polluted area and the second is to transform these pollutants to harmless forms. The application of Biochar in soil makes dual purpose which ameliorating soil fertility and remediated heavy metal due to the content of different physicochemical properties. So in this paper, including source of heavy metal, effect of heavy metal in human, plant growth and soil microorganism and remediation technique of contaminated soil, reaction of biochar in soil and application of biochar in soil quality were discussed. Therefore this is particular importance as it indicates the value of biochar as alternative remediation and amendments to ameliorate soil nutrient and acid soils for small-scale farmers who cannot afford to regularly purchase lime and mineral fertilizers as compared to phytoremediation techniques. But phytoremediation wide scope of area use of plants to partially or substantially remediate selected contaminants in contaminated soil, sludge, sediment, groundwater, surface water, and wastewater.
Brain Tumor Segmentation Based on GLCM Feature Extraction using Probabilistic Neural Network

: The paper presents the MRI brain diagnosis support system for structure segmentation and its analysis using K-means clustering technique integrated with Fuzzy C-means algorithm. The method is proposed to segment normal tissues such as White Matter, Gray Matter, Cerebrospinal Fluid and abnormal tissue like tumour part from MR images automatically. These MR brain images are often corrupted with Intensity In homogeneity artefacts cause unwanted intensity variation due to non-uniformity in RF coils and noise due to thermal vibrations of electrons and ions and movement of objects during acquisition which may affect the performance of image processing techniques used for brain image analysis. Due to this type of artefacts and noises, sometimes one type of normal tissue in MRI may be misclassified as other type of normal tissue and it leads to error during diagnosis. The proposed method consists of pre-processing using Gaussian filter to remove noise and K-means clustering technique integrated with Fuzzy C-means algorithm segments normal tissues by considering spatial information because neighbouring pixels are highly correlated and also construct initial membership matrix randomly. The results will be presented as segmented tissues and classification using neural network classifier.
Scale Invariant Feature Transform based Sign Language Recognition for Deaf People

ign language is one of the best methods used to communicate with deaf and dumb people and robots. The SIFT (Scale Invariant Feature transform) algorithm takes an image and transforms it into a collection of local feature vectors. SIFT method is used to extract all the features of certain types of signs, then formed theirs code book from all the features by using K means clustering and finally classified by using the multiclass support vector machine. This paper presentssystem of sign language recognition using bag-of-words and multiclass support vector machine (SVM) approach that uses Scale invariant feature of image.We are used American Sign Language (ASL) as an example of a gestural language(GL). The objective of the paper is to decode ASL Image into the appropriate alphabets.
Improved Evolutionary Optimization Approach For Solving The Multi-Objective Facility Location Problem

: This paper presents hybrid approach consists of three metaheuristic techniques which are Evolutionary Optimization with two efficient metaheuristic techniques for solving the multi-objective facility location problem. The target is to put a good network design of creating new IT centers as endpoints connected with the main datacenter in an educational organization minimizing the number of threats and risks through the network segments. Also minimizing the consumed runtime of travelled packets through this network and minimizing the total required distances to build this design. Furthermore it, a system was designed and developed to help in solving the complicated calculations of this problem. Finally, a comparison study is carried out to compare the hybrid approach techniques performance and results which support the expansion of the designed network.
Maximum Power Point Tracking Algorithms Applied to Wind-Solar Hybrid System

The production of electricity from renewable energy sources like solar, wind energy increases in recent years due to environmental problems and the shortage of traditional energy sources in the near future. This paper presents modeling, simulation, and performance study of Hybrid generation system with PI and MPPT controller. The Wind power generation system uses Wind Turbine(WT), a Permanent Magnet Synchronous Generator(PMSG), a three phase controlled rectifier bridge with PI controller, a dc bus with a capacitor and a current regulated PWM voltage source inverter. The PV cell model is developed including the effects of changing solar irradiation and temperature and Maximum power from PV cell is obtained by using MPPT controller. This paper reports the development of wind/photovoltaic power generation system and also describes the Wind-Solar Hybrid system for supplying electricity to the Load and describe various MPPT techniques namely Perturb and Observe(P&O), Incremental Conductance(INC) and Fuzzy Logic based MPPT controller and their performance. Simulation results of Hybrid system using various MPPT techniques are provided.
Gaussian Mixture Model Based Hierarchical Clustering in Prediction of Autism Spectrum Disorder

Autism is one of the most complex and divergent class disorders which accompany various lacking in symptoms needed for classification, societal interaction, abridged verbal communication, and monotonous behavior. Timely and proper diagnosis of Autism Spectrum Disorder can ensure the offering of medical treatment and guidance to get cure. In this paper, Gaussian Mixture Model based Hierarchical Clustering is proposed for efficiently predicting the Autism Spectrum Disorder. Also, Flexible splitting concept was proposed for hierarchical clustering in order to increase the quality of guessing and classification accuracy. The proposed algorithm is validated to check the performance against the existing method. The results shows that the proposed algorithm outperforms the existing algorithm in terms of classification accuracy.
Italian Industrial Districts: Theories, Profiles and Competitiveness

The paper is a contribution to the debate about the theoretical aspects, the structure, and the competitiveness of Italian industrial districts. The work first examines the theoretical strand on industrial districts ranging from Marshall to Becattini, and focusing on the contemporary distrettualism of Giacomo Becattini, where the district is essentially a socio-economic construct and an important localized productive system. Furthermore, the paper offers an updated picture of the Italian industrial districts as they are represented in the 2011 Census by the National Statistics Institute. Finally, this study underlines the resilient competitive capacity of this typical form of industrial organization. Then, through empirical literature, it analyzes the Italian district companies, and their performance and success in foreign markets, especially with regard to “Made in Italy” products.
Antioxidant and antimicrobial properties of Adhatoda

Copyright: © 2015 | Author(s), This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial No Derivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is noncommercial and no modifications or adaptations are made. Plant Adhatoda vasica L. Nees (Acanthaceae) commonly known as Malabar nut is an evergreen two – three m tall shrub, sometime used as hedge, branches opposite and stem yellowish. Leaves simple, 10-20 cm long and 3 to 7.5 cm or sometime much more broad, elliptical, ovate-lanceolate, and tapering towards apex. Inflorescence terminal or sub terminal spikes, flowers white bilabiate and fruits two-valve capsule, which dehisces when mature, or dry. The plant leaves, bark and root known for traditional medicinal use in Ayurveda. The plant parts generally bitter and useful in cough, bronchitis, asthma, skin disease, eczema and scabies. The leaves extensively employed in preparations indicated in respiratory ointments and particularly in cough syrups. An antioxidant is a molecule capable of slowing or preventing the oxidation of other molecules. Oxidation is a chemical reaction that transfer electrons from a substance to oxidizing agent oxidation reaction can produce free radicals, which start chain reaction that damage cells. Antioxidants terminate these chain reactions by removing free radical intermediates and other oxidation reaction by being oxidize themselves. In present investigation preliminary antioxidants evaluated from the experimental plant and antimicrobial sensitivity test carried out against some human pathogenic microbial strains to support out the potential compounds of pharmacognostic interest.
THRESHOLD CONGESTION DETECTION VICTIMIZATION PROTEA IN DDOS

This analysis paper implements congestion detection victimization protea against DDoS attack. In initial level to notice congestion causation attack. Therein massive attacks area unit detected early within the border router within the transit network before converge at server. At the second level to notice the well good wrongdoer to cut back the network performance to perform attack with adjustable entropy price that sort of secret attacks area unit stay unobserved within the transit domain. These attacks area unit detected within the border router within the stub domain close to the victim. Protea is employed to high filtering accuracy. Known the wrongdoer and deactivate the service for wrongdoer from server. It’ll facilitate to legitimate user to urge frequent service kind server. Thought of varied threshold and alter purpose detection on entropy to boost the detection rate. This system offers high answer to DDoS attack.
ANTIOXIDANT ACTIVITY OF CISSUS QUADRANGULARIS L. STEM IN-VITRO

The present study aimed to evaluate the in-vitro antioxidant activities of Cissus quadrangularis L. stem. The preliminary phytochemical assay using solvents of different polarity namely water, 50% hydroethanol, ethanol, acetone, chloroform and petroleum ether showed the presence of secondary metabolites like flavanoids, alkaloids, tannins, triterpenoids, carbohydrates, saponins, glycosides, ligins and inulins. Among all the extracts, hydroethanol extract showed the presence of more secondary metabolites. Hence it was utilized for antioxidant assays like superoxide radical scavenging activity, hydroxyl radical scavenging activity and metal chelating activity. These results revealed that the 50% hydroethanol extract of Cissus quadrangularis L. stem possessed potent antioxidant properties.
A Review for an Intrusion Detection System Combined with Neural Network

— Intrusion detection system has become a core component in computer network era. It is expanding day by day. That is why, there is a need for security from attackers, spammers and criminal enterprises as they are growing up with the expansion of Internet. An Intrusion Detection System is integrated with neural network using layered framework to build an effective computer network. This existing system is experimented with KDD 1999 dataset. It works for offline dataset. This system is compared with existing approaches of intrusion detection system which either uses neural network or layered framework and shows the higher accuracy. In this way, a new system can be proposed in which data can be used as Real Time data set. The system can be used to implement the Real Time Host based attacks. This system is useful in online environment. Also it provides high accuracy with less false alarm rates.
Short Communication Screening of some Bangladeshi medicinal plants for in vitro antibacterial activity

SUMMARY A total of 33 extracts representing 26 plant species belonging to 24 families were collected fromdifferent regions of Bangladesh, and screened for their in vitro antibacterial activity againstseveral pathogenic Gram-positive and Gram-negative bacterial strains using the conventionaldisc diffusion method. The most potent activity was exhibited by the extracts of Aegicerascorniculatum, Alocasia fornicata, Ceriops decandra, Cuscuta reflexa, Lasia spinosa, Lantana camara,Pandanus foetidus and Xylocarpus granatum. The extracts of Abtilon indicum, Derris trifoliata,Dendrophthoe falcat, Ruellia tuberosa and X. moluccensis did not show any antibacterial properties attest concentrations.Key words: Antibacterial activity; Medicinal plants; Disc diffusion method; Bangladesh INTRODUCTION Natural products have long been utilized as anindispensable source for the discovery anddevelopment of new drugs. One of the majorsources of these natural products is medicinalplants that have been used traditionally in manycountries to combat various diseases, includinginfections. The healthcare systems in manydeveloping countries like Bangladesh still relysignificantly on the uses of medicinal plants.Bangladesh is one of the South Asian countries thathave a rich and prestigious heritage of medicinalplants’ uses to treat various diseases. As aconsequence, medicinal plants have traditionallyoccupied an important status in the socio-cultural,spiritual and medicinal arena of rural and triballives on Bangladesh. A conservative estimate wouldinclude at least 500 species of medicinal plants thathave been used in Bangladeshi traditional medicines(Ghani, 1998). A survey conducted in 1990 indifferent villages in Bangladesh revealed that onaverage of 14% of people suffering from illnessesapproach qualified allopathic doctors, 29% contactunqualified village doctors, 10% contact mullahs,
Study on Co-Extracting Opinion Words and Opinion Reviews Based on the Word Alignment Model

Data mining is a procedure of searching or finding, collecting and analyzing a big group of data in the database and discovering the patterns or relationships between them. There are numerous challenges and conditions that have given arise in data mining and one amongst them is opinion mining. Sentimental analysis can also be referred to as Opinion mining which involves analyzing the emotions of individuals towards creating a system to classify and collect opinions or reviews about various products and services. To analyze this type of data, opinion mining techniques are used. Hence for fine grained output from opinion mining, word alignment model and patterns of sentences and phrases. Getting opinion words and opinion targets is the crucial and significant tasks. After detecting the opinion target and opinion word one important task is to get the relation between them. From the review it is evident that it is acquired using word alignment technique. Word alignment model is heavy task hence to balance the load and improvise the execution process partial supervised technique is employed and syntactic patterns are useful for it. In this paper have to examine the Co-extracting opinion words and opinion reviews techniques that will be on the basis of the alignment model.
Quo Vadis, Pulmonary Tuberculosis?

Tuberculosis (TB), is mainly caused by the ancient stealth pathogen, Mycobacterium tuberculosis, and remains among the top ten leading causes of death worldwide. Downward disease trajectories in the US and Europe, have been juxtaposed with high disease burdens in other countries. Current diagnostic tests are inadequate to differentiate between a third of the global population infected with latent TB and those destined to develop active TB i.e. who may be asymptomatic or have subclinical forms of the disease. In addition to a seemingly endless repertoire of antibiotic resistance mechanisms, transiently tolerant M. tuberculosis subpopulations called persisters can survive treatment. In this article, I synthesize relevant preclinical and clinicals studies, as well as review articles, detailing the past, present, and future of TB research. A proposal is made to tailor management and prevention strategies, taking into account knowledge regarding treatment limitations and the availability of new management options.
A Study on Data Security In Fog Computing

During the years, Cloud Computing is a popular paradigm which provide access to configurable resources on devices at any time,with on demand. Cloud Computing provides many benefits to enterprises by reducing the cost and allowing them to concentrate on their core business. Apart from this , the Development of Internet of Things came into existence, where the cloud divulge a long distance between users and its environment. Cloud Computing is also referred as heavy computing and dense form of computing power. In Spite of this a new computing has been proposed called Fog Computing also known as Fogging, which overcomes the problem of cloud. Fog computing which majority supports the concepts of Internet of Things(IoT), where many IoT devices are used by users on daily basis which are connected to each other. Fog Computing is also an extended version of cloud computing.
Underwater Wireless Optical Communication

The Wireless communication technology has became a part of our daily life. The earth is covered by 75% of water. With the intensive development in technology, Underwater wireless optical communication are the best emerging solutions for broadband links in oceans and seas. UOWC plays a vital role in tactical surveillance, pollution monitoring, oil control, climate change monitoring, offshore study, military field, scientific field and oceanography research. The signals that carries the digital information through an underwater channel are not radio signals, since electro-magnetic waves propagate only over extremely short distances. Instead, acoustic waves are improvised, which can be propagated over long distances. This paper provides an in-depth outlook of recent trending advancements in UOWC and therefore it’s mainly focus is to understand the reliability and feasibility high data rate underwater optical links. This research not only provides exhaustive research in underwater optical communications but also aims to implement the new ideas that would help in the development of the UOWC.