Innovative Computing Review

Comparative Analysis of Breast Cancer Detection using Cutting-edge Machine Learning Algorithms (MLAs)

2023-09-22T10:41:34+00:00

Recently, machine learning techniques have gained popularity for the medical diagnosis. Medical professionals use this approach to learn and detect the abnormalities of life-threatening chronic diseases. The increasing use of ML approaches may be due in part to better disease diagnosis enabled through improved symptom detection. The current study deployed different machine learning algorithms, including Decision Trees (DT), K-Nearest Neighbors (KNN), classifiers Multilayer Perceptron (MP), Support Vector Machines (SVM), and Random Forest (RF) for early predictions and symptoms of the disease. These models were capable of differentiating between benign and harmful cancer cells Benign tumours, which were non-cancerous and in most cases, non-lethal were mostly confined to the area from where they originated, however, it was observed that malignant cancer can start with abnormal cell growth in the human body. This abnormal cell growth can quickly spread to nearby tissues, which can cause infiltration of adjacent cells, resulting in a potentially fatal condition. Thereby, it was observed that Multilayer Perceptron (MLP) model provided the highest accuracy percentage of 86% when compared with all the other techniques in association with the accuracy rate of the models

Role and Effectiveness of IOT in E-Learning: A Digital Approach for Higher Education

2023-09-22T10:46:11+00:00

Internet of things (IOT) is an emerging technology, which has facilitated the abiding connection of real and virtual objects. Its developmental influence has caused a predictable impact on higher education, especially E-learning. Previous studies indicated that the prime aim of IOT is to transform traditional education into a flexible and effective learning approach by creating a digital or virtual learning environment. Consequently, the current study aims to evaluate the effective role of e-learning in higher educational institutions by investigating faculty’s overall interactions with this new learning platform. A comprehensive questionnaire was used for data collection from faculty members of several local universities to assess how instructors see E-learning. The analysis and presentation of the data have all employed tables, graphs, and other pertinent visual representations of the data. Data analysis of teachers’ response displayed that viability, abundant material, affordability, mobility, and enhanced concentration are keys features of e-learning that attract teachers. Thus, teachers believe/see e-learning as an adaptable dynamic change to meet educational needs in challenging times. Additionally, teachers also highlighted certain issues that they face while adapting e-learning such as inadequate internet connectivity, limited access, insufficient internet speed in remote areas, online real-world subjects are harder to understand, and cyber security problems. These problems need to be addressed at large to improve the efficiency and potential of e-learning in Pakistan.

Impact of Social Media Platforms on the Learning Habits of University Students

2023-09-22T10:48:01+00:00

The current study aims to find out the effects of social media sites on the academic performance of university students. Social media has been globally the major source of communication between individuals. Social media includes Cell phones, Facebook, Tick-talk, YouTube, Twitter, Myspace, Instagram, Skype, Tumblr, and many other social media platforms. Researchers all over the world have varied findings on the effect of social media on the academic performance of university students. The current study deployed a survey methodology by filling questionnaires from the respondents, regarding the usage of social media and its effects on the academic performance of students. For this purpose, two hundred students of the social sciences department enrolled in the BS program were the sample for the current study. Data were collected using an adapted questionnaire and for the analysis of data, AMOS Software version 24 was applied to develop a model. This model was developed to represent, the effect of social media on student academic achievement at the university level. The finding indicated study found that social networking media significantly affect the academic performance of university students. With this data, it is recommended that the administration must regulate the proper time usage of SMN by the students to save them from the destruction of excessive media usage.

Information and Communication Technology (ICT), Energy Volatility, and Output Volatility Nexus: A Global Panel Data Analysis

2023-10-20T04:34:02+00:00

The current research contributes to the literature by evaluating the influence of Information and Communication Technology (ICT), energy volatility, and output volatility on global economies over the time period 1971-2020. The analysis was based on panel dataset for 154 nations. For empirical analysis, the study used pooled OLS, fixed effects, and random effects models including 2SLS and GMM methods. Moreover, to ensure the stability of the findings, the study ran a series of robustness analyses. The results suggested that ICT mitigates economic instability and output volatility. Energy use volatility, on the other hand, yielded considerable positive and statistically significant outcomes and augmented output volatility. This study provides important policy recommendations for implementing ICT-enabled technologies. Moreover, it is advised that the government should promote ICT technologies which result in lower volatility and protracted development of the economy.

Three Axis Kinematics Study for Motion Capture Using Augmented Reality

2023-09-22T10:55:09+00:00

MoCap (Motion Capture) refers to the process of tracking, processing, recording, and translating real-world
motions into a 3D model. MoCap provides vital realism to animal and human motion not only in entertainment
but also in other sectors. It is also frequently used in Medical Motion Therapy, robotics, Augmented Reality
(AR), and Virtual Reality (VR). In addition to the well-known optical techniques, appropriate systems based on
Inertial Measurement Unit (IMUs) , the rapid advancement of technology in the manufacture of such IMUs
enables the development of compact sensors that may be worn on the body and send motions to a host computer.
IMU can estimate the orientation of a rigid body. To compute orientation, IMU technology employs data from
three sensors: a magnetometer, an accelerometer, and a gyroscope. The movement of any object can be
monitored multiple IMU devices. This study describes the design and execution of a real-time motion capture
system and a six-degree-of-freedom tracking system using COTS and reduced noise. This includes the general
assembly of the hardware components and the software-side analysis of the obtained motion data and its
implementation to a 3D model. The proposed design prioritizes flexibility and usability. The results of six DoFs,
the overall noise filtration percentages of the system is 10.924 and 40.787 for Gyroscope and Accelerometer
respectively and tracking real-time motion capture reveal that our prototype is competent to collect the values
of motion parameters and track the motion of objects that can be mated with digital characters on the virtual
screen using AR or VR. Several high-end cameras, as well as unique clothes are required. That makes mocap
technologies prohibitively expensive. The primary objective for this effort is to investigate a more cost-effective
and less noisy way to capture movement / postures more accessible to a broader variety of people.