Journal of Research in Engineering and Computer Sciences

Constant Total Energy for a Given Mass and at a Given Temperature Implies Constant Momentum also for Drifting Electrons in Materials Having a Bandgap

Ravi Kumar Chanana — 2024-07-24

Conservation of energy due to constant total energy implies conservation of momentum as well for electrons moving at a constant drift velocity in semiconductor or insulator materials having a bandgap

Conservation of Energy and Momentum of the Free Electrons in Materials at Room Temperature Undergoing Drift

Ravi Kumar Chanana — 2024-08-09

Conservation of energy and momentum due to constant total energy and momentum of the free electrons in materials is illustrated with examples of Si [100] and GaAs [100]. Fused silica forms the example of the insulator material. There is loss in energy of the free electrons while drifting through materials in a particular direction. This loss does not allow for accurate determination of electron effective masses based on conservation of energy or momentum. For this, one has to rely on theoretical technique of density functional theory or the experimental technique of electron cyclotron resonance.

Development of a Smart System for Effective Educational Guidance

Chidi Ukamaka Betrand — 2024-08-19

Smart education is a comprehensive notion of higher education that is based on an interactive culture in the rapidly expanding globe. It is an example of cutting-edge technology that makes it possible for students to process knowledge and skills more accurately, productively, and efficiently. The main issues with smart education range from pupils becoming sidetracked from their studies to low academic achievement due to untrustworthy learning materials. This study proposes the Smart System for Effective Educational Guidance (SSEEG) as a means of enhancing academic achievement and student engagement in higher education using smart education. In order to improve student-teacher interaction and create a more positive learning environment in higher education, artificial intelligence (AI) is employed in interactive systems. Students can assess their achievement in smart education learning in higher education by using the feedback system and dependable learning resources offered by the proposed SSEEG. The outcomes of the experiment demonstrate that enhanced teacher-student contact is effective and has a high degree of accuracy when analyzing academic student performance skills.

Variation of Saturated Drift Velocity of Electrons in Silicon with Temperature

Ravi Kumar Chanana — 2024-08-23

Recently, the author has shown conservation of energy and momentum of free electrons in materials at room temperature undergoing drift, with examples of Si and GaAs. In the present study, the variation of the saturated drift velocity of electrons with temperature is illustrated taking the example of the Silicon material. It is shown that while the free electron energy at room temperature remains constant due to conservation of energy, the saturated drift velocity increases with decreasing temperature as the electron effective mass reduces upon application of the universal mass-energy equivalence relation dE/E = dm/m. The observed total electron kinetic energies are calculated during drift at high fields at different temperatures. Gain or loss of energies at different temperatures due to changes in electron collisions with the lattice atoms and electron trappings in defects are further calculated. The quantitative analysis due to the now available universal mass-energy equivalence relation is one of the main contributions of this research paper.

Enhanced Decision Making in Judicial System of European Court of Human Rights via Bayesian Optimization Boosting Learning

David Opeoluwa Oyewola — 2024-08-23

As the custodians of constitutional rights and principles, courts bear the responsibility of delivering impartial and equitable judgments. However, the surge in caseloads has necessitated innovative measures to tackle backlog issues, leading to the adoption of automated decision-making processes. This research delves into the implementation of automated decision-making in the European Court of Human Rights (ECHR) Mapping Projects, leveraging publicly available data. The study considers two classes, violation and non-violation, and proposes Bayesian Optimization Boosting Learning (BOBL). A comparative analysis with established machine learning models such as Random Forest (RFT), Gradient Boosting (GBT), Decision Tree (DTE), and Logistic Regression (LRN) is conducted to forecast judicial decisions. The court is segmented into 12 sections, including Court First Section, Court Second Section, Court Third Section, Court Fourth Section, Court Fifth Section, Court Third Section Committee, Court Fifth Section Committee, Court Second Section Committee, Court Grand Chamber, Court Fourth Section Committee, and Court First Section Committee. The results consistently demonstrate BOBL's outperformance over traditional classifiers, showcasing superior accuracy across all court sections and committee scenarios. Noteworthy is BOBL exceptional accuracy, peaking at 99.00%, emphasizing its adaptability and efficacy in diverse legal contexts. These findings suggest that the BOBL model holds significant promise as a resilient and versatile tool for legal applications, surpassing traditional classifiers in both performance and reliability.

Quantum Leap for Mobility: Revolutionizing Transportation with Quantum Computing

Ravi Jagirdar — 2024-08-31

Quantum technologies have emerged as a transformative force, poised to revolutionize industries beyond the constraints of conventional technologies. The 2023 Quantum Technology Monitor forecasts substantial economic benefits of up to $1.3 trillion by 2035 across sectors like automotive, chemicals, finance, and life sciences through quantum computing applications. Quantum mechanics, once confined to theoretical realms, now garners widespread attention for its practical implications. Quantum physics delves into the fundamental nature of matter, showcasing phenomena that defy classical intuition, with applications ranging from MRI scanners to cutting edge technologies like solar cells. The evolution of quantum mechanics has birthed quantum computing, a multidisciplinary field merging computer science, physics, and mathematics to tackle complex computational challenges at unparalleled speeds. Industries such as Healthcare, Drug Development, Financial Services, Data Security, and Logistics are poised to reap significant rewards from quantum computing advancements. In the transportation sector, quantum computing offers transformative potential, particularly in traffic engineering, where it can optimize route planning and resource allocation. The exploration of quantum-inspired algorithms for solving fundamental challenges like the shortest path problem further underscores the promise of quantum computing in transportation optimization. Companies like D-Wave lead the charge in quantum computing development, showcasing real-world applications such as optimizing bus routes dynamically. This paper encapsulates the burgeoning landscape of quantum technology, its applications in transportation, and the potential for reshaping industries through quantum computing advancements.