The ISC International Journal of Information Security

Abstract Tracking or taking care of elderly people when they live alone is much challenging area. Because most of the aged people suffering from some health issues like Alzheimer, diabetes, and hypertension, so in case happening any abnormal activity or any emergency situation since they live alone and there is no one around them to offer any support, so one of the best choices to care mature people is focusing on smart home technology. Also, one of the essential keys to expand smart home technology is monitoring, detecting, and recognizing human activities called Ambient Assisted Living (AAL) applications. Nowadays our world highly focuses on a smart system because the smart system can learn the habits, and if it finds any problem or any abnormal happenings, it can take automated decisions for residents for example, by learning cooking time, the system can prepare the oven, and by learning spare time which the resident spend for watching, the system can prepare the TV also put it to favorite channel for the residents. To done this, a new and existing established machine learning and deep learning approaches are required to be estimated the system focusing on using real data-sets. So, this study presents machine learning to analyze activities of daily living (ADL) in smart home environments. The data sets were collected from a set of binary sensors installed on two houses. This study used public data sets for detecting and recognition human activities, the data set was tested based on machine learning classification especially Support Vector Machines (SVM) was applied as traditional neural network also for deep learning (1-Dcnn) as Convolutional Neural Network (CNN) also, Long Short-Term Memory (LSTM) as Recurrent Neural Network (RNN) and was used. Also, sliding window (windowing) was used in the preprocessing phase, the study concludes that all used algorithms can detect some activities perfectly, and on the other hand they can’t predict all activities perfectly especially those activities that take short-time, the main key for this situation is imbalanced data.

Abstract This paper is one that explored intelligent decision support systems and Decision support systems. Due to the inception and development of systems and technological advances such as data warehouse, enterprise resource planning, advance plan system & also top trends like Internet of things, big data, internet, business intelligent etc. have brought in more advancement in the operations of decision support systems. This paper gives a systematic review on all the various applications of IDSS based on, knowledge, communication, documents etc. with also heading further to describe and differentiate two DSS methods which are Analytical Network Process (ANP) & Decision-Making Trial & Evaluation Laboratory (DEMATEL)

Abstract In recent years technology and management information system has been an excellent response too many global challenges, technology innovation has expanded over almost all the sectors of, and it made many processes more accurate and very faster than before. Technology systems playeda big role part in election processes in many democratic countries nowadays. The commission, in Iraq, suffers from many problems such as fraud, time-consuming and delays in the election processes that take a long time and also witness a delay in revealing the results. This research paper focuses on adapting the biometric system in Iraq; there are several different perspectives to specify the IHEC’s employees and manager’s attitude towards technology in general and Biometric system specifically. Most of the staff members feel confident about transforming into a technology system. In their responses to the questionnaires, most of them focused on getting trained before they start using the system. In this research, the data is collected by using survey technique from the independent high electoral commission managers and staff members, and the data is analyzed by using SPSS.