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Human resource plays a key role in a society and also for all kind of organization, therefore offering a reasonable and intelligent way for selection of a suitable and essential career. Artificial Intelligence (AI) is used today in science, engineering, business, manufacturing, management and many other fields. Expert systems as a branch of AI have attracted the at-tention of mostly large and medium organizations for doing some human’s activities. Case Based Reasoning (CBR) is also a new problem solving paradigm that in many ways is fun-damentally different from other major AI approaches. Instead of relying solely on general knowledge of a problem domain, or making associations along generalized relationships be-tween problem descriptors and conclusions, CBR is able to utilize the specific knowledge of previously experienced situations. This research work presents a model for designing an intelligent career consultation system using case-based reasoning which recommends suitable jobs for applicants. This system, as a sample, has been implemented in an Iranian organization.

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Under the critical thermal conditions, the human body cannot adapt itself to the environment by using physiological thermoregulatory mechanisms. Under these conditions, using the protective clothing is one of the effective ways to protect the human body against the thermal injuries. Therefore, in the present study, the effect of using Phase Change Materials (PCMs) on the performance of firefighters’ protective clothing has been numerically investigated under the critical scorching conditions. The main contribution of this study is the simultaneous modeling of a PCM based protective clothing with physical and physiological mechanisms of the human body. For this purpose, a multi-layer protective clothing with a PCM layer has been considered and its thermal performance has been investigated under scorching conditions for three different arrangements of the layers. The results show that the middle layer of protective clothing is the best position for implementing the PCM. Also, and is the best melting temperature for the mentioned PCM is about 40˚C. Moreover, the results indicate that using the PCMs in protective clothing can increase the thermal tolerating time from 300 seconds (for non-PCM protective clothing) up to 900 seconds, under the scorching conditions.

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This paper proposes a new inexpensive soft force sensor suitable for soft robotics applications that require high flexibility and wide range of sensing area. All Hall Effect sensors developed so far use a Hall Effect sensor to detect the magnetic field of a piece of solid magnet. The proposed force sensor in this paper uses a Hall Effect sensor to detect the magnetic flux density change induced by aligned magnetic powder blended with silicone rubber when a normal force is applied. The sensor is designed and tested with different magnetic powder density and sensor dimensions to achieve an optimum design in sensitivity as well as linearity. The experimental results show that different force measurement range with specific desired sensitivity can be achieved by adjusting certain physical properties of the sensor. This is a useful feature for lots of soft sensing elements in today's applications requiring more compliance and reliable sensors, especially in soft robotics applications.

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Nowadays, web-based services like E-Commerce and E-Banking make fundamental changes to the ways of using internet and human's life. Web shares direct media with low costs between services of businesses and their customers. Businesses need to record, study and analyze their users' behavior and interests in order to adapt content and interface of their web site with users' interest for targeted marketing and advertising and then complete the process of personalization. For this purpose and for analysis of users’ behavior and making recommendations based on the users’ behavior, web mining approaches can be used. In this paper, a model was developed which can be applied for analyzing and predicting users' behaviors of a specific web site. First, users were clustered with affinity propagation algorithm and then, their behaviors were analyzed using sequential pattern mining algorithm called CM-SPADE. In the next step, for each cluster, Users' profile was created. Then by using these profiles, recommendations can be made for new users. At last, the represented model was evaluated and the final results was acceptable.

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Corebanking is a comprehensive and integrated system for responding timely and accurately to customer's demands and reporting their information. This task is done through various communication channels between customers and banks and a common database between all branches in order to staying in competition. For the optimum and strategical usage and utilizing IT in our goals path, we have to use a roadmap to implement new technologies. So far for different fields and usage and control of technologies this strategic roadmaps have been provided. COBIT as an IT governance framework is one of these frameworks which is used for both guide and control of IT in organizations. In this study, we provide a core banking IT governanvce model based on COBIT framework. For this reason we determine the activities required for operation of corebanking by using structural equation modeling and significance of relationship between COBIT processes and activities with the activities needed to achieve core banking. To allocate the sub-process of the COBIT for each of the activities of corebanking we used questionaries and Delphi technic.