In this paper, a new learning algorithm for adaptive network intrusion detection using naive Bayesian classifier and decision tree is presented, which performs balance detections keeps false positives at acceptable level different types of attacks, eliminates redundant attributes as well contradictory examples from training data that make the model complex. The proposed also addresses some difficulties mining such handling continuous attribute, dealing with missing attribute values, reducing...

Recently, research on intrusion detection in computer systems has received much attention to the computational intelligence society. Many learning algorithms applied huge volume of complex and dynamic dataset for construction efficient (IDSs). Despite many advances that have been achieved existing IDSs, there are still some difficulties, such as correct classification large dataset, unbalanced accuracy high speed network traffic, reduce false positives. This paper presents a new approach...

In this paper, we introduce a new learning algorithm for adaptive intrusion detection using boosting and naïve Bayesian classifier, which considers series of classifiers combines the votes each individual classifier classifying an unknown or known example.The proposed generates probability set round updates weights training examples based on misclassification error rate that produced by in round.This addresses problem large dataset, improves rates (DR) reduces false positives (FP) at...

Cricket is the most popular sport in south Asian countries and second globally. And T20 cricket attractive version of this game. Businesses have grown enormously based on cricketing sports events from last decade. A large number research been done to predict winner matches or analyze game statistics. These studies are helping investors franchisees decide which team they can invest gain more profit. Also, coaches, analysts, technicians get facts ideas about other teams, help them make...

Recent intrusion detection have emerged an important technique for information security systems. Its very that the mechanisms system should be designed to prevent unauthorized access of resources and data. Last few years, many intelligent learning techniques machine applied large volumes complex dynamic audit data construction efficient systems (IDS). This paper presents, theoretical overview a new approach based on adaptive Bayesian algorithm. algorithm correctly classify different types...

It is always a good choice to consider multiple sources when analyzing crime. Newspaper can be source of crime analysis as it contains the massive amount data related any particular subject but fact they are not structured enough make definite decision. In this paper, we represent system analyze news from online newspaper using different mining techniques. These techniques help extract useful pieces information about unstructured news. The will provide whether or not, location, similarity...

At present telemedicine is widely used in developing countries for its variety of health services. In this paper, we have developed a low cost portable tool kit remote diagnosis patients. Remote patient monitoring one the vital component any We successfully able to collect data from locations by using our kit. research, collected seven signs patient's such as blood pressure, pulse and oxygen blood, glucose level, position falls, body temperature, electrical muscular functions heart through...

Lung cancer (LC) is a significant global health issue, with smoking as the most common cause. Recent epidemiological studies have suggested that individuals who smoke are more susceptible to COVID-19. In this study, we aimed investigate influence of and COVID-19 on LC using bioinformatics machine learning approaches. We compared differentially expressed genes (DEGs) between LC, smoking, datasets identified 26 down-regulated 37 up-regulated shared 7 6 Integration these resulted in...

In this paper, we introduce a new approach to the classification of streaming data based on bootstrap aggregation (bagging).The proposed creates an ensemble model by using ID3 classifier, naïve Bayesian and k-Nearest-Neighbor classifier for learning scheme where each gives weighted prediction.ID3, Bayesian, classifiers are very well known mining methods, which have been already used in many real life problems.The addresses practical problems successfully tested number benchmark including...

The World Wide Web (www or w3 commonly known as the web) is largest database available with growth at rate of millions pages a day and presents challenging task for mining web data streams.Currently extraction knowledge from streams getting more complex, because structure doesn't match attribute-values when considering large volume data.In this paper, an ensemble decision tree classifiers presented, which efficient method to obtain proper set rules extracting amount streams.We built server...

Cardiovascular diseases such as; heart attack (coronary thrombosis, myocardial infarction), hypertension, stroke, coronary artery disease (CAD), congestive failure, peripheral (PAD) and diabetes create a new concern worldwide due to its harmness. In Bangladesh where majority live in rural areas that lack specialist care, we envision the need for much larger Internet-based telemedicine systems would enable large pool of doctors hospitals collectively provide healthcare services entire...

In this paper, we introduce new learning algorithms for reducing false positives in intrusion detection. It is based on decision tree-based attribute weighting with adaptive naïve Bayesian tree, which not only reduce the (FP) at acceptable level, but also scale up detection rates (DR) different types of network intrusions. Due to tremendous growth network-based services, has emerged as an important technique security. Recently data mining are applied traffic and host-based program behaviors...

The pediatric cardiac intensive care unit (ICU) is a specialized section for children with heart diseases. patients admitted to the ICU are in very critical condition. data each day were collected hourly basis. So, time-series prediction might be beneficial physicians medication process of whose lives danger. This paper proposes multivariate time series where multiple features respect timestamps predicted using deep learning methods order assist doctors decision making tensed moment....

OBJECTIVES: Telemedicine based healthcare service faces different difficulties especially in the remote people of Bangladesh. The objective this study was to implement an advanced telemedicine model order provide services for rural METHODS: We devel oped using ardunio low cost portable tool kit by interfacing android application. Then we collected ECG, blood pressure, temperature, concentration glucose blood, SPO2, body position, airflow, height and weight through our developed model....

Cyber-Physical Systems (CPS) requires big data communications as well integration from several distributed sources. This can usually be interconnected with physical applications, such power grids or SCADA systems. In addition, it publicly accessible for using by third party users scientists. Therefore, becomes imperative to ensure that this is secured. Microaggregation an widely used technique protect a dataset through anonymity in order prevent exposure of person's identity. disclosure may...

Load Forecasting has an important role in load generation, scheduling, planning etc. power system. Different computational intelligent techniques are used Short Term (STLF) to make it more effective. Neural Networks (NN) is effective mapping algorithm that can map complex input-output relationships, which technique do STLF having existing dataset. Usually a proper NN sufficient achieve accepted level of performance. But different dataset may bear some irregular nature demand scenario due...

In this paper we have developed a Telemedicine model with portable tool kit for remote patients to collect vital signs of which are used services. This system is low cost, portable, and easily maintainable can be integrated any complex health system. We the GNU where local doctors communicate cost terminal. Expert also take part through terminal deliver treatment patients. The patient's medical history stored in database accessed from successfully designed collected data. Through our android...

Healthcare systems capture patients' data using different medical equipment and store it in the databases with a continual increase volume. The continuous processing sharing of this massive are rising concerns live transferring over networks. Sending patient to distant remote user without proper compressing format requires high latency communication channels. Any alternation transmitted via medium may also cause issues assuring authentication integrity. For solving problems, watermarking...

Security and privacy have become crucial factors in auction design. Various schemes to ensure the safe conduction of sealed bid auctions been proposed recently. We propose a secure protocol. introduce new standard for auctions, that prevents extraction information despite any collusion participants. Present cryptographic protocol which is realization an electronic being component e-government or e-commerce system. Our provide non-reputation correctness.

This paper presents the development of an Artificial Neural Networks and Particle Swarm Optimization (ANN-PSO) based short-term load forecasting model with improved generalization technique for Regional Power Control Center Saudi Electricity Company, Western Operation Area (SEC-WOA). Weather, demand, wind speed, direction, heat, sunlight, etc. are quite different in a desert land than other places. Thus this is from typical considering inputs outputs. In research two steps have been...

Road traffic congestion remains a global phenomenon that causes great problems in the cities of world; especially developing countries, resulting massive delay, unpredictable travel times, increased fuel consumption, man-hour and monetary loss. In order to get better solution, one preposition is divert less congested route. One solution collecting road condition crowd sourcing. We proposed sourcing information will change network graph city according result. Based on this updated graph,...