Volume 15, Issue 4, Sep-Oct 2024


Modeling the Impact of Flow Parameters on Fluid Velocity and Temperature in an Electrically Conducting Fluid Past a Wedge

Nyaga Danson, Kirimi Jacob, Ochwach Jimrise, Okongo Mark

Department of Physical Science, Faculty of Science, Engineering and Technology, Chuka University, Chuka, Kenya

Abstract- The main concern of the present paper is to study the impact of flow parameters on fluid velocity and temperature in an electrically conducting fluid past a wedge. MHD mixed convective heat transfer for an incompressible, laminar, and electrically conducting casson nanofluid flow past a permeable wedge investigated via a numerical method, called fourth-order accurate collocation-based solver (BVP4C). The boundary-layer governing partial differential equations (PDEs) are transformed into highly nonlinear coupled ordinary differential equations (ODEs) consisting of the momentum and energy equations using similarity solution. The velocity is found to increase with an increasing Falkner Skan exponent whereas the temperature decreases. With the rise of the Casson fluid parameter, the fluid velocity increases but the temperature is found to decrease in this case. It is found that the temperature decreases as the Prandtl number increases and thermal boundary layer thickness decreases with increasing values of the Prandtl number. A significant finding of this investigation is that flow separation can be controlled by increasing the value of the Casson fluid parameter. The results demonstrates a good agreement with previously published studies for some special cases.

Keywords- Casson Fluid, Nanofluid, Fluid Flow Parameters and Electrically Conducting

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Analysis of Internet of Things & Security Risks

Mirza Ahmad Saeed Baig, M. Junaid Arshad

Department of Computer Science, University of Engineer and Technology, Lahore, Pakistan

Abstract- From the last decades, the Internet of Things (IoT) is becoming a part of our life and they are adopting rapidly by the people. In IoT ecosystems, different devices are connected including mobile devices, computers, embedded systems, security cameras, toys, kitchen accessories, cars, smart homes etc. They send or received the data which can be hacked by the hackers, so, on the basics of these in this research we will discuss the security measures & challenges and the technologies that can be implemented or are implementing to make these IoT devices secure.

Keywords- Internet of Things (IoT), IoT Security, Authorization and Confidentiality

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Evaluation of Integrated Corm Grating and Leaf Sheath Decorticating Machine

Gelgelo Kibi, Gizachew Tefera

Oromia Agricultural Research Institute, Bako Agricultural Engineering, Research Center, P.O Box 07, West Shoa, Bako

Abstract- Enset processing, in Ethiopia at present, is labour demanding and time consuming activity which calls for technology to make it efficient and lighten the burden on women. Multipurpose enste processing machine was adapted. So, integrated corm grate and leaf sheath decorticate machine was evaluated at three levels drum speed 1900, 2000 and 2100rpm for corm grating and four levels of drum speed 800, 900, 1000 and 1100rpm for leaf sheath decorticating for the most dominate two varieties (Baladat, and Lemate local names) at farmers farm. Performance of the machine was evaluated interims of Grating capacity (Kg/hr) and Decorticating capacity for both varieties. Based on the results obtained, the grand mean grating capacity of 1658Kg/hr (~1.5ton/hr) for corm and decorticating capacity, decorticating efficiency of 497.00Kg/hr and 90.33% for leaf sheath is recorded for the prototype at 1mm concave clearance. Fuel consumption of 0.6lit/hr was recorded at drum speed of 1100 rpm and strongest variety as the farmers’ response (Baladati variety) for leaf sheath decorticating. And 1.1lit/hr fuel consumption was recorded at drum speed of 2100 rpm and baladeti variety for corm grate. The machine can be used by farmers for all varieties at drum speed range of 2000 – 2100rpm for corm grating while 900 – 1100rpm and 1mm concave clearance for leaf sheath decorticating.

Keywords- Evaluation, Grating, Decorticating and Enset

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Detection of Acne Lesions in the Skin Using Machine Learning and Image Processing Techniques

Aqsa Latif

Department of Computer Science, SZABIST (Dubai Campus)

Abstract- Skin diseases are common and can lead to severe conditions, making automated diagnosis essential. We propose a method combining Convolutional Neural Networks (CNN) and YOLOv5 for efficient skin disease classification. Our approach uses morphological filtering and Gaussian de-noising for preprocessing, followed by YOLOv5 for accurate lesion segmentation. Features are extracted using the Gray Level Co-occurrence Matrix (GLCM) and then classified with Support Vector Machine (SVM). We validate our models on ISIC 2019 and HAM10000 datasets, where SVM outperforms other classifiers. Our method is compared with state-of-the-art techniques to demonstrate its effectiveness.

Keywords- Biomechanics, Bone Fragility, Finite Element Analysis, Humerus and Osteoporotic Bone

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