Integrated vector management (IVM) is an acknowledged strategy of choice for the prevention and control of vector-borne diseases. The paper describes and documents the progress countries of the World Health Organization (WHO) Eastern Mediterranean Region have made in endorsing and translating the strategy into action at the national level. These include increased political commitment; strengthe...

As global efforts to control and eliminate malaria intensify, vector control interventions are being extensively deployed in the context of the World Health Organization (WHO)-led integrated vector management (IVM) strategy [1]. Indoor residual spraying (IRS) and insecticide treated nets (ITNs), supplemented by focalized larval source management, have been harnessed for interrupting transmissio...

human snake bitten poisoning is a serious threat in many tropical and subtropical countries such as iran. the best acceptable treatment of envenomated humans is antivenoms; however they have a series of economic and medical problems and need more improvements. in this study a combinatorial human immunoglobulin gene library against some of iranian snakes venoms was constructed. total rna prepare...

The volume and quality of data, but also their relevance, are crucial when performing data analysis. In this paper, a study of the influence of different types of data is presented, particularly in the context of educational data obtained from Learning Management Systems (LMSs). These systems provide a large amount of data from the student activity but they usually do not describe the results o...

An analysis of acoustic features for a ternary cognitive load classification task and an application of a classification boosting method to the same task are presented. The analysis is based on a data set that encompasses a rich array of acoustic features as well as electroglottographic (EGG) data. Supervised and unsupervised methods for identifying constitutive features of the data set are inv...

Skin color segmentation by a block histogram-based Support Vector Machine (SVM) is proposed in this paper. The color model used is the Hue-Saturation (HS) model. Color information is represented by histogram of a block image on the HS space. To represent histogram information as accurately as possible, an irregular quantization partition approach on HS space is proposed. Histogram information o...

This paper proposes an English lexical stress detection approach using acoustic features. The approach classifies the vowels of English words into two patterns: primary stress and unstress. We firstly choose the frame-averaged basic feature set of the individual syllable nucleus in polysyllabic words as the baseline to decide the stress pattern. This feature set includes the semitone, the durat...

The state of the art in traffic incident detection is dominated by approaches that require significant manual tuning. Our hypothesis is that these time-consuming solutions can be sucessfuly eliminated with the help of machine learning methods and past traffic data collected nowadays on major highways. We show that combining the output of a set of simple, imperfectly tuned, “offthe-shelf” detect...

Nosocomial infections (NIs)---those acquired in health care settings---are among the major causes of increased mortality among hospitalized patients. They are a significant burden for patients and health authorities alike; it is thus important to monitor and detect them through an effective surveillance system. This paper describes a retrospective analysis of a prevalence survey of NIs done in ...

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning proto...