Determining Essential Steps in Designing a Successful System of Organizational Career Development

In the current contemporary and highly competitive business environment, all organizations are encouraged to create a work environment, which fosters growth and development by implementing a career development program. Because through such a program, organizations can achieve their strategic goals and employees’ ideal career will be available for them. It is not exaggerated to say that there are still many organizations that have failed to achieve career development goals, their employees are not motivated to stay and they are always looking for competent individuals to fill the vacancies. Unfortunately, those organizations assume that the development costs are wasted. Therefore, in this paper, we intended to identify the essential steps to design a successful system of organizational career development; a system by which individuals and organizations are able to reach their goals. For the purposes of this study, 25 managers and human resource experts from Iranian large private companies, in Tehran, who have successfully experienced such a system, were interviewed. Six factors were determined as the most influential key factors in system’s success, including goals and needs review, harmonizing the road map, accurate assessment, development program, and matching and creating opportunities. The findings indicate that a positive relationship exists between mentioned factors and the success of the organizational career development system

Determining Essential Steps in Designing a Successful System of Organizational Career Development

In the current contemporary and highly competitive business environment, all organizations are encouraged to create a work environment, which fosters growth and development by implementing a career development program. Because through such a program, organizations can achieve their strategic goals and employees’ ideal career will be available for them. It is not exaggerated to say that there are still many organizations that have failed to achieve career development goals, their employees are not motivated to stay and they are always looking for competent individuals to fill the vacancies. Unfortunately, those organizations assume that the development costs are wasted. Therefore, in this paper, we intended to identify the essential steps to design a successful system of organizational career development; a system by which individuals and organizations are able to reach their goals. For the purposes of this study, 25 managers and human resource experts from Iranian large private companies, in Tehran, who have successfully experienced such a system, were interviewed. Six factors were determined as the most influential key factors in system’s success, including goals and needs review, harmonizing the road map, accurate assessment, development program, and matching and creating opportunities. The findings indicate that a positive relationship exists between mentioned factors and the success of the organizational career development system

Specognitor: Identifying Spectre Vulnerabilities via Prediction-Aware Symbolic Execution

Spectre attacks exploit speculative execution to leak sensitive information. In the last few years, a number of static side-channel detectors have been proposed to detect cache leakage in the presence of speculative execution. However, these techniques either ignore branch prediction mechanism, detect static pre-defined patterns which is not suitable for detecting new patterns, or lead to false negatives. In this paper, we illustrate the weakness of prediction-agnostic state-of-the-art approaches. We propose Specognitor, a novel prediction-aware symbolic execution engine to soundly explore program paths and detect subtle spectre variant 1 and variant 2 vulnerabilities. We propose a dynamic pattern detection mechanism to account for both existing and future vulnerabilities. Our experimental results show the effectiveness and efficiency of Specognitor in analyzing real-world cryptographic programs w.r.t. different processor families

Comparison on Logistic Regression, Random Forest, and CNN for Handwritten Digit Recognition

The technology of handwritten digit and character recognition is the process of identifying handwritten numbers using computers or other devices, machine train itself to recognize the handwritten digits or characters from various sources like bank cheque, mails, images, etc. This paper is about CNN, Logistic Regression, and Random Forest algorithm in handwritten digit or character recognition system, the system works on MNIST dataset for training and testing the models, to get the best accuracy this work rewrites CNN, Logistic Regression, and Random Forest with python libraries. Finally, these algorithms are analyzed by comparing the accuracy and recognition duration. Where CNN got better accuracy than other algorithm