درخت حوزه‌های تخصصی

The purpose of this research study is to measure the impact of governance on the organizational performance of schools in administrative, financial and pedagogical aspects. This governance approach will be approached using a methodology respecting several principles in terms of participation, transparency, accountability and evaluation (CSEFRS, 2015). Furthermore, we added in our frame of reference the primordial aspect of good governance, which is the new technologies. Considering the difficulty of an etymological and polysemic consensus on the concept of governance. It would be wise to set up operational indicators for applying this notion of governance with a perspective to enhance management skills, multi-stakeholder strategic planning, internal collaborative management, effective and efficient steering, control and evaluation. Methodology / approach: Our methodological approach based on a descriptive exploratory study. The researcher carried out an empirical study involving 20 principals of qualifying secondary schools from the Nouaceur-Casablanca region. Our measurement instrument is related to a survey which is appraised as one of the five principles of effective governance (transparency, accountability, participation, evaluation and technology). Findings: data analysis shows difficulties in applying governance principles, influencing organizational performance in administrative management. Additionally, the educational management and financial management of these establishments have seen a positive application of these governance mechanisms. It would be wise to apply the multidimensional aspects of governance, through the harmonious, complete and balanced integration of the three management mechanisms: administrative, pedagogic and financial management. The relationship between the study variables is demonstrated by the application of the five principles of governance, the results of the study recommended that we apply them to contribute significantly to improve the effectiveness of strategic planning, collaborative management and community steering.  

VANET (Vehicular Ad-hoc Network) is a developing technology, which is a combination of cellular technology, ad-hoc network & wireless LAN to improve the safety of vehicle as well as driver. VANET communication can be of two types, first one is broadcast and second one is unicast. Either communication may be broadcast or unicast both are sensitive to different types ofassaults, for example message forgery, (DOS) denial of service, Sybil assault, Greyhole, Blackhole & Wormhole assault. In this paper machine learning method is used to detect the wormhole assault in VANET’s multi-hop communication. We have created a scenario of VANET by using AODV routing protocol on NS-3.24.1 simulator, which utilizes the overall mobility traces generated by the simulator SUMO-0.32.0 to model the wormhole assault. The simulation is performed by using NS-3.24.1 simulator, and the statistics created by flow monitor are collected. The collected data is pre-processed and the k-NN & Random Forest algorithms are applied on this data, to make the model such type so that it can memorize the wormhole attack. The novelty of this research work is that with the help of proposed detection & prevention technique, vehicular ad-hoc network can be made free from wormhole assault by using ML approach. The performance of proposed machine learning models is compared with existing work. In this way it is clear that our proposed approach by using ML is powerful tool by which the wormhole assaults can be detected in VANETs. A scheme based on packet lease and cryptographic techniques is used to prevent the wormhole attack in VANET

Brand community interactions and online customer support have become major platforms of brand sentiment strengthening and loyalty creation. Rapid brand responses to each customer request though inbound tweets in twitter and taking proper actions to cover the needs of customers are the key elements of positive brand sentiment creation and product or service initiative management in the realm of intense competition. In this research, there has been an attempt to collect near three million tweets of inbound customer requests and outbound brand responses of international enterprises for the purpose of brand sentiment analysis. The steps of CRISP-DM have been chosen as the reference guide for business and data understanding, data preparation, text mining, validation of results as well as the final discussion and contribution. A rich phase of text pre-processing has been conducted and various algorithms of sentiment analysis were applied for the purpose of achieving the most significant analytical conclusions over the sentiment trends. The findings have shown that the sentiment of customers toward a brand is significantly correlated with the proper response of brands to the brand community over social media as well as providing the customers with a deep feeling of reciprocal understanding of their needs in a mid-to-long range planning.