Zhengshu Zhou^1,*, Shunya Yamada², Yousuke Watanabe², Hiroaki Takada^1,2

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2109-2127, 2023, DOI:10.32604/csse.2023.029005

Abstract Many traffic accidents occur in parking lots. One of the serious safety risks is vehicle-pedestrian conflict. Moreover, with the increasing development of automatic driving and parking technology, parking safety has received significant attention from vehicle safety analysts. However, pedestrian protection in parking lots still faces many challenges. For example, the physical structure of a parking lot may be complex, and dead corners would occur when the vehicle density is high. These lead to pedestrians’ sudden appearance in the vehicle’s path from an unexpected position, resulting in collision accidents in the parking lot. We advocate that besides vehicular sensing data, high-precision… More >

Ashit Kumar Dutta^1,*, T. Meyyappan², Basit Qureshi³, Majed Alsanea⁴, Anas Waleed Abulfaraj⁵, Manal M. Al Faraj¹, Abdul Rahaman Wahab Sait⁶

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2701-2713, 2023, DOI:10.32604/csse.2023.028984

Abstract Recently, developments of Internet and cloud technologies have resulted in a considerable rise in utilization of online media for day to day lives. It results in illegal access to users’ private data and compromises it. Phishing is a popular attack which tricked the user into accessing malicious data and gaining the data. Proper identification of phishing emails can be treated as an essential process in the domain of cybersecurity. This article focuses on the design of biogeography based optimization with deep learning for Phishing Email detection and classification (BBODL-PEDC) model. The major intention of the BBODL-PEDC model is to distinguish… More >

Khalil Hamdi Ateyeh Al-Shqeerat^*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2095-2107, 2023, DOI:10.32604/csse.2023.028975

Abstract Most remote systems require user authentication to access resources. Text-based passwords are still widely used as a standard method of user authentication. Although conventional text-based passwords are rather hard to remember, users often write their passwords down in order to compromise security. One of the most complex challenges users may face is posting sensitive data on external data centers that are accessible to others and do not be controlled directly by users. Graphical user authentication methods have recently been proposed to verify the user identity. However, the fundamental limitation of a graphical password is that it must have a colorful… More >

S. Prabhakaran^1,*, R. Annie Uthra¹, J. Preetharoselyn²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2683-2700, 2023, DOI:10.32604/csse.2023.028898

Abstract The Problem of Photovoltaic (PV) defects detection and classification has been well studied. Several techniques exist in identifying the defects and localizing them in PV panels that use various features, but suffer to achieve higher performance. An efficient Real-Time Multi Variant Deep learning Model (RMVDM) is presented in this article to handle this issue. The method considers different defects like a spotlight, crack, dust, and micro-cracks to detect the defects as well as localizes the defects. The image data set given has been preprocessed by applying the Region-Based Histogram Approximation (RHA) algorithm. The preprocessed images are applied with Gray Scale… More >

Mohammad Alkhawatrah, Ahmad Alamayreh, Nidal Qasem^*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1911-1919, 2023, DOI:10.32604/csse.2023.028614

Abstract Orbital Angular Momentum (OAM) is an intrinsic property of electromagnetic waves. Great research has been witnessed in the last decades aiming at exploiting the OAM wave property in different areas in radio and optics. One promising area of particular interest is to enhance the efficiency of the available communications spectrum. However, adopting OAM-based solutions is not priceless as these suffer from wave divergence especially when the OAM order is high. This shall limit the practical communications distance, especially in the radio regime. In this paper, we propose a cooperative OAM relaying system consisting of a source, relay, and destination. Relays… More >

S. Gopikha^*, M. Balamurugan

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2727-2742, 2023, DOI:10.32604/csse.2023.028609

Abstract Melanoma is the most lethal malignant tumour, and its prevalence is increasing. Early detection and diagnosis of skin cancer can alert patients to manage precautions and dramatically improve the lives of people. Recently, deep learning has grown increasingly popular in the extraction and categorization of skin cancer features for effective prediction. A deep learning model learns and co-adapts representations and features from training data to the point where it fails to perform well on test data. As a result, overfitting and poor performance occur. To deal with this issue, we proposed a novel Consecutive Layerwise weight Constraint MaxNorm model (CLCM-net)… More >

S. Subha^1,*, S. Baghavathi Priya²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2081-2093, 2023, DOI:10.32604/csse.2023.028451

Abstract This paper presents an efficient prediction model for a good learning environment using Random Forest (RF) classifier. It consists of a series of modules; data preprocessing, data normalization, data split and finally classification or prediction by the RF classifier. The preprocessed data is normalized using min-max normalization often used before model fitting. As the input data or variables are measured at different scales, it is necessary to normalize them to contribute equally to the model fitting. Then, the RF classifier is employed for course selection which is an ensemble learning method and k-fold cross-validation (k = 10) is used to validate the… More >

N. Vanitha^1,*, C. R. Rene Robin¹, D. Doreen Hephzibah Miriam²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2323-2336, 2023, DOI:10.32604/csse.2023.028309

Abstract Abstract: Tropical cyclones (TC) are often associated with severe weather conditions which cause great losses to lives and property. The precise classification of cyclone tracks is significantly important in the field of weather forecasting. In this paper we propose a novel hybrid model that integrates ontology and Support Vector Machine (SVM) to classify the tropical cyclone tracks into four types of classes namely straight, quasi-straight, curving and sinuous based on the track shape. Tropical Cyclone TRacks Ontology (TCTRO) described in this paper is a knowledge base which comprises of classes, objects and data properties that represent the interaction among the… More >

P. Nalayini^1,*, R. Arun Prakash²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2033-2047, 2023, DOI:10.32604/csse.2023.028269

Abstract Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things (IoT) services. After the emergence of IoT-based services, the industry of internet-based devices has grown. The number of these devices has raised from millions to billions, and it is expected to increase further in the near future. Thus, additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user… More >

V. Joseph Raymond^1,2,*, R. Jeberson Retna Raj¹

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2147-2163, 2023, DOI:10.32604/csse.2023.028227

Abstract Android devices are popularly available in the commercial market at different price levels for various levels of customers. The Android stack is more vulnerable compared to other platforms because of its open-source nature. There are many android malware detection techniques available to exploit the source code and find associated components during execution time. To obtain a better result we create a hybrid technique merging static and dynamic processes. In this paper, in the first part, we have proposed a technique to check for correlation between features and classify using a supervised learning approach to avoid Multicollinearity problem is one of… More >