Ethical Issues in Computer Use: A Study from Islamic Perspective

Computer users are continuously facing ethical challenges as society adopts new and increasingly complex tools and technologies. These ethical challenges can be managed by Islamic code of life. In this paper, we have studied and tried to identify, how computer affects the ethical issues of the society. In this regards, we have traced some highly related issues to the ethics of computer usage, namely 2013; misuse of time, honesty and integrity, privacy, security, intellectual property right, and computer crime. We have also tried to explain these issues in the light of Qur2019;an and Hadith. At the end of this paper, we have also suggested some measures that can help in promoting proper use of computer facilities by the Muslim masses without compromising the Islamic principles

Ethical Issues in Computer Use: A Study from Islamic Perspective

Abstract Computer users are continuously facing ethical challenges as society adopts new and increasingly complex tools and technologies. These ethical challenges can be managed by Islamic code of life. In this paper, we have studied and tried to identify, how computer affects the ethical issues of the society. In this regards, we have traced some highly related issues to the ethics of computer usage, namely -misuse of time, honesty and integrity, privacy, security, intellectual property right, and computer crime. We have also tried to explain these issues in the light of Qur'an and Hadith. At the end of this paper, we have also suggested some measures that can help in promoting proper use of computer facilities by the Muslim masses without compromising the Islamic principles

A Fuzzy ANP Based Grey Relational Approach to Evaluate CRM System in Context of Bangladesh

This study aims to select a suitable CRM (customer relationship management) system among different possible alternatives for organization’s in Bangladesh. Since, evaluating CRM system on the basis of lot of attributes leads us to Multiple-criteria decision analysis (MCDA) problems. In this study, a hybrid MCDA models were used. FuzzyANP (Analytic Network Process) and GRA (Grey Relational Analysis) approaches were adopted to solve the problem. The study explored that the Hubspot CRM was optimal solution in context of Bangladesh. Our research will beneficial to the organizing for better customer support. As far our knowledge goes, this is the first attempt to select CRM softwares in context of Bangladesh. Keywords: Analytic network process; Customer relationship management system; Grey relational analysis; Multiple-criteria decision analysis DOI: 10.7176/IKM/11-4-06 Publication date:June 30th 202

Delicar: A smart deep learning based self driving product delivery car in perspective of Bangladesh

The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install.publishedVersio

Active sense: Early staging of non-insulin dependent diabetes mellitus (niddm) hinges upon recognizing daily activity pattern

The Human Activity Recognition (HAR) system allows various accessible entries for the early diagnosis of Diabetes as one of the nescient applications domains for the HAR. Long Short-Term Memory (LSTM) was applied and recognized 13 activities that resemble diabetes symptoms. Afterward, risk factor assessment for an experimental subject identified similar activity pattern attributes between diabetic patients and the experimental subject. Because of this, a trained LSTM model was deployed to monitor the average time length for every activity performed by the experimental subject for 30 consecutive days. Concurrently, the symptomatic diabetes activity patterns of diabetic patients were explored. The cosine similarity of activity patterns of the experimental subject and diabetic patients measured 57.39%, putting the experimental subject into moderate risk factor class. The experimental subject was clinically tested for risk factors using the diabetic clinical diagnosis process, known as the A1C. The A1C level was 6.1%, recognizing the experimental subject as a patient suffering from Diabetes. Thus, the proposed novel approach remarkably classifies the risk factor level based on activity patterns.publishedVersio

Intelligent human resource information system (i-HRIS): A holistic decision support framework for HR excellence

Nowadays, Human Resource Information System (HRIS) plays a strategic role in the decision making process for effective and efficient Human Resource Management (HRM). For Human Resource (HR) decision making, most of the researchers propose expert systems or knowledge-based systems. Unfortunately, there are some limitations in both of expert system and knowledge-based system. In this paper, we have proposed a framework of Intelligent Human Resource Information System (i-HRIS) applying Intelligent Decision Support System (IDSS) along with Knowledge Discovery in Database (KDD) to improve structured, especially semistructured and unstructured HR decision making process. Moreover, the proposed HR IDSS stores and processes information with a set of Artificial Intelligent (AI) tools such as knowledge-based reasoning, machine learning and others. These AI tools are used to discover useful information or knowledge from past data and experience to support decision making process. We have likewise attempted to investigate IDSS applications for HR problems applying hybrid intelligent techniques such as machine learning and knowledge-based approach for new knowledge extraction and prediction. In summation, the proposed framework consists of input subsystems, decision making subsystems and output subsystems with ten HR application modules