In this paper, we propose genetic algorithm (GA) to improve support vector machines (SVM) based intrusion detection system (IDS). SVM is relatively a novel classification technique and has shown higher performance than traditional learning methods in many applications. So several security researchers have proposed IDS. We use fusions of GA enhance the overall Through SVM, "optimal model" for classifier can be determined. As result fusion, IDS not only select parameters "for but also feature...

In financial risk, credit risk management is one of the most important issues in decision-making. Reliable scoring models are crucial for agencies to evaluate applications and have been widely studied field machine learning statistics. Deep a powerful classification tool which currently an active research area successfully solves problems many domains. Learning provides training stability, generalization, scalability with big data. quickly becoming algorithm choice highest predictive...

Abstract Analyzing the interactions of circular RNAs (circRNAs) is a crucial step in understanding their functional impacts. While there are numerous visualization tools available for investigating circRNA interaction networks, these typically limited to known circRNAs from specific databases. Moreover, existing usually require complex installation procedures which can be time-consuming and challenging users. There lack user-friendly web application that facilitates interactive exploration...

In this paper, we present a flexible combined system, namely the Vehicle mode-driving Activity Detection System (VADS), that is capable of detecting either current vehicle mode or driving activity travelers. Our proposed system designed to be lightweight in computation and very fast response changes travelers' modes events. The detection module responsible for recognizing both motorized vehicles, such as cars, buses, motorbikes, non-motorized ones, instance, walking, bikes. It relies only on...

At the early of 21 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> century, In UK Peer2Peer (P2P) lending began with Zopa at start 2005. After that, it has grown rapidly in United States, China and some other countries. The main challenge for individual investors P2P market is to allocate their money efficiently through different loans by accurately evaluating credit each loan. traditional ranking models cannot conform needs because...

Circular RNA (circRNA), a class of molecule with loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers human diseases. Most the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize mapping information paired-end (PE) reads eliminate false positives. However, much practical RNA-Seq such as cross-linking immunoprecipitation sequencing (CLIP-Seq) usually contain single-end (SE) reads. It is not clear how well...

Because falls are the second leading cause of injury deaths, especially in elderly according to WHO statistics, there have been a lot studies on developing fall detection and warning system. Many approaches based wearable sensors, cameras, Infrared radar, etc., proposed detect efficiently. However, it still faces many challenges due noise no clear definition activities. This paper proposes new way extract 44 features time domain, frequency Hjorth parameters deal with this. The effect feature...

Abstract Background Circular RNA (circRNA) is an emerging class of molecules attracting researchers due to its potential for serving as markers diagnosis, prognosis, or therapeutic targets cancer, cardiovascular, and autoimmune diseases. Current methods detection circRNA from sequencing (RNA-seq) focus mostly on improving mapping quality reads supporting the back-splicing junction (BSJ) a eliminate false positives (FPs). We show that information alone often cannot predict if BSJ-supporting...

In this work, we present a novel method, namely dynamic basic activity sequence matching (DAS), combination of machine learning methods and flexible threshold based for distinguishing normal abnormal driving patterns. Indeed, DAS relies on the detection module (ADM) presented in our previous work to analyze each pattern as activities—stopping (S), going straight (G), turning left (L), right (R). fact, value other parameters like duration long short activities are iteratively induced from...

Stacking goods or items is one of the most common operations in everyday life. It happens abundantly not only transportation applications such as container ports, ships, warehouses, factories, sorting centers, freight terminals, etc., but also computing systems, supermarkets, and so on. We investigate problem stacking a sequence into set capacitated stacks, subject to constraints. In every stack, are accessed last-in-first-out order. So at retrieval time, getting any lower item requires...

TThis paper presents a hybrid method that combines the genetic algorithm (GA) and ant colony system (ACS), namely GACS, to solve traffic routing problem. In proposed framework, we use optimize ACS parameters in order attain best trips travelling time through several novel functions help ants update global local pheromones. The GACS framework is implemented using VANETsim package real city maps from open street map project. experimental results show our achieves considerably higher...