Current Issue

Sana'a University Journal of Applied Sciences and Technology

Vol. 4 No. 4 (2026)

2026-04-28

11 Articles

The fourth volume – the fourth issue in the Sana'a University Journal of Applied Sciences and Technology

Article

9 Articles

The map of Yemen shows Dhamar City and the Location of the Study sites

Forensic Insect Succession and Carrion Decomposition in Indoor and Outdoor Habitats:Implications for Post-mortem Interval Estimation in Dhamar, Yemen

Wed Abdullah Al Raeeini, Abbas Mohammed Al-Azab, Fahd Mohammed Abd Al Galil

1903-1913

2026-04-28

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DOI: 10.59628/jast.v4i4.2778

Abstract

Forensic entomology is a branch of forensic science that utilizes insects to assist in criminal investigations. Building on the foundational principles of forensic entomology, this study investigates of entomofauna’s role in decomposing rabbit carcasses ( Oryctolagus cuniculus L.), across varied environments. Using a consistent collection and analysis protocol, we monitored the decomposition process and insect activity in three different environments in Dhamar City, Yemen. Two carcasses were outdoors: one in a botanical garden and another in an open agricultural area. The third was indoors in a laboratory at the Faculty of Agriculture at Thamar University. The research was conducted over two periods: September and November 2023, as well as October 2024. Urban environments, including both botanical gardens and controlled indoor settings, typically exhibit higher temperatures and lower humidity, which accelerates decomposition more than in agricultural sites. The dry stage was reached by day 30 in urban environments, whereas in agricultural areas, it took approximately 52 days. A total of 1270 adult insect specimens were collected, with outdoor habitats exhibiting the highest abundance. Chrysomya albiceps (Calliphoridae) was the dominant species at all sites in the early phases of decomposition, confirming its forensic usefulness in determining postmortem intervals (PMIs). This study describes insect succession resulting from carrion decomposition in both indoor and outdoor habitats in Dhamar City, Yemen. It establishes baseline data essential for estimating the post-mortem interval (PMI) in the locality.

Keywords

Forensic Insect Carrion decomposition Insect succession PMI Dhamar Outdoor Indoor habitat

A Comparative Model to Analyze the Impact of Tax Dataset Augmentation on the Accuracy of Machine Learning Models

Abeer Abdullah Shujaaaddeen, Ammar T.Zahary, Fadl Mutaher Ba-Alwi

1914-1923

2026-04-28

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DOI: 10.59628/jast.v4i4.2121

Abstract

Many factors influence the efficiency of a classification model in Machine Learning, including the dataset’s size and the type of Machine Learning (ML) technique utilized in the classification process. Primarily, the accuracy varies among different machine learning methods. This paper develops a model that analyses and measures the impact of Tax Dataset Augmentation on the Accuracy of Machine Learning Models. The paper compares the performance of different models based on the most common machine learning techniques, namely: DT, RF, SVM, and ANN (MLP). Based on three datasets provided by Yemen’s Tax Authority. The first dataset contains 1083 records, while the second dataset is identical to the previous one, but with nearly five times the number of records, following data preprocessing, which resulted in approximately 5000 additional records. The last dataset is the same as the original dataset, but it has been duplicated nearly ten times, resulting in almost 10,000 records. The dataset partitioning technique utilized k-fold validation using the three datasets. Results show that the performance of ML classifiers such as ANN (MLP), DT, RF, and SVM is affected by dataset augmentation in terms of accuracy, recall, precision, and F-score. Results also show that the performance varies among the first three techniques; however, the SVM Classifier yields the lowest results. In general, despite some techniques leading to overfitting, it is found that most machine learning models utilizing tax datasets with five times the duplicates produced better outcomes than those using the original dataset. These findings provide practical guidance for tax authorities in selecting robust machine learning models under limited data availability and highlight risks associated with naïve dataset expansion.

Keywords

ML Techniques DT, RF ANN Performance Measures Tax Dataset

Location map of Block 9 in the Sayun- Masila Basin, Yemen, showing the Al Roidhat Field (study area).

3D Static Geological Model and Volumetric Assessment of the Upper Qishn Clastic in Al Roidhat Field, Yemen

Saddam AL-Sofi, Mohammed Hail Hakimi, Adel Mohammad Al-Matary, Bassim S. Al khirbash

1924-1937

2026-04-28

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DOI: 10.59628/jast.v4i4.2602

Abstract

This study addresses a critical knowledge gap by presenting the first comprehensive 3D static geological model of the heavy-oil-bearing Upper Qishn Clastic Member in the Al Roidhat Field, Yemen. The model integrates data from eight wells. The workflow encompassed structural modeling, stratigraphic zonation into three reservoir units (S1, S2, S3), facies modeling using Sequential Indicator Simulation (30 realizations), and petrophysical property modeling using Sequential Gaussian Simulation. Probabilistic volumetric assessment was based on 100 stochastic realizations. Uncertainty analysis yields a P50 Stock-Tank Oil Initially in Place (STOIIP) of 56.81 million barrels (P10–P90 range: 44.40–73.39 MMSTB). The S3 unit exhibits the best reservoir quality (62.8% sand, 0.15 porosity, 47mD permeability), while the S1 unit shows good quality (48.1% sand, 0.14 porosity, 60 mD permeability). Yet, the S1 unit contains 58% of the STOIIP because it lies entirely within the oil column, whereas a significant portion of S3 is submerged below the oil-water contact. Together, S1 and S3 account for approximately 85% of the total resource. This pioneering 3D model quantifies reservoir heterogeneity and structural controls, establishing an essential digital foundation for the field. It demonstrates that structural position can override intrinsic rock quality in governing hydrocarbon distribution, and it clearly identifies the S1 and S3 units as priority targets for future development and enhanced oil-recovery planning in this challenging heavy-oil reservoir.

Keywords

3D Geological Model Heavy Oil Upper Qishn Clastic Uncertainty Analysis Reservoir Characterization Al Roidhat Field STOIIP

General Architecture of the proposed approach

A Proposed Incremental Distance Based Clustering of Interesting Patterns for Big Data

Akram A. M. Mustafa, Abdulmajed A. G. Al-Khulidi, Ahmed S. Al-Hegami

1938-1949

2026-04-28

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DOI: 10.59628/jast.v4i4.2271

Defining a new type of α-supra open soft sets using parametric supra topologies

Tareq M. Al-shami, S. Saleh, Mohammed Jameel

1950-1958

2026-04-28

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DOI: 10.59628/jast.v4i4.2704

Performance of Encryption schemes in 5G Networks

Mohamed Hankal

1959-1966

2026-04-28

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DOI: 10.59628/jast.v4i4.2317

The Discriminate Analysis with Applied on Diabetes non- Diabetes in Sana’a, Yemen for the Year 2025

Amtalteef M.A. Al-Hamzi, Amani M.A. Al-Hamzi

1967-1976

2026-04-28

PDF

DOI: 10.59628/jast.v4i4.2555

نسبة الانبات للمعاملات المختلفة في فترتين حيث تشير T1 الى معاملة الشاهد، T2 الى ازيد الصوديوم، وT3 لمعاملة مستخلص بذور الحرمل، وG.R1 الانبات في الفترة الاولى بعد 75 يوم وG.R2 الانبات في الفترة الثانية بعد 125يوم من الزراعة.

Mutation Induction in a Yemeni Coffee Variety Using Sodium Azide and Peganum harmala seeds Extract

Buthaina Othman Abdullah Bahwirth, Amin Abdo Sofian AL-Hakimi, Mahasen Al-Munibari

1977-1997

2026-04-28

PDF

DOI: 10.59628/jast.v4i4.2538

Abstract

The research was carried out during 2023/2024, in the laboratory of the Participatory Foundation for Research and Dissemination and the Faculty of Agriculture, Foods, and Environment, Sana'a University, Yemen under controlled condition, for the objective to improve genetic variation in Yemeni coffee. The seeds of a local variety "Udini" were used, and four treatments, namely the control without any treatment of the seeds, the second treatment was soaked with sodium azide solution at a concentration of 0.1 molar and the third treatment was treated with the seeds extract of the Harmel plant (Peganum harmala L.), and the fourth by dipping the roots of the coffee seedlings after germination with the extract of Harmel, in this treatment all the plants were died within the first weeks of dipping the seedling roots in the Harmal extract, this indicates the importance of using lower concentrations and immersion times. The results showed that the use of mutational chemicals had a role in causing changes in the speed and rate of seed germination, in the length of seedlings, and in the number and length of roots, and the analysis of the frequency curves showed that the distribution of the frequency of the natural plant population was clearly affected in the treatments by the mutagenic substances compared to the natural control group in relation to the most traits. The phenotypic transformations that appeared on the cotyledon leaves and on the real leaves developing on the first node were recorded, and seven forms of deformations were distinguished, represented in heterogeneity in the cotyledon leaves and in the real leaves and in the cotyledon leaves and real leaves together. These results clearly indicate that mutations can be used as a tool to improve genetic variation in Yemeni coffee.

Keywords

.Coffea arabica L Mutations Sodium Azaid .Peganum harmala L Genetic Improvement Foliar transformations

The eigenfunctions ψn (x) for ν = 1, ω = 1, β = 1. The functions are based on the exact solutions for the unperturbed case (β = 0), which involve generalized Laguerre polynomials L(ν+1/2) n (ωx2). They exhibit the correct xν+1 behavior near the origin, Gaussian decay at infinity, and the proper number of nodes (n). The logarithmic perturbation (β̸ = 0) modifies the polynomial coefficients and shifts the node positions, but preserves these qualitative features

A New Family of Self-Adjoint Quantum Operators with Logarithmic Potential: From Self-Adjointness to Sharp Spectral Asymptotics and Green’s Function Analysis

Osama Aldahyani, Abdu A. Alkelly

1998-2009

2026-04-28

PDF

DOI: 10.59628/jast.v4i4.2966

Abstract

The Schrödinger operator with a combined singular, confining, and logarithmic potential arises in diverse physical contexts—from quantum dots and Bose–Einstein condensates to effective field theories. Despite its broad relevance, a rigorous spectral analysis of this operator family has remained elusive due to the simultaneous presence of three challenging features: a $1/x^{2}$ singularity at the origin, an unbounded logarithmic term, and harmonic confinement at infinity.
We introduce and rigorously analyze the one-parameter family of operators
\[H = -\frac{d^2}{dx^2} + \frac{\nu(\nu + 1)}{x^2} + \omega^2 x^2 + \beta \ln x,\qquad \nu > 0,\;\beta \in \mathbb{R},\;\omega > 0,\]
acting on $L^{2}(0,\infty)$. Self-adjointness is established through a combination of Weyl's limit-point/limit-circle classification and the KLMN theorem for quadratic forms, circumventing the failure of standard Kato–Rellich perturbation theory. The spectrum is shown to be purely discrete and bounded below, with simple eigenvalues that depend analytically on the logarithmic coupling $\beta$.
The central result of this work is the sharp asymptotic expansion of the eigenvalues for large quantum numbers:
\[E_{n} = 2\omega n + \beta \ln n + \gamma_{0} + \frac{\beta}{2n} + \mathcal{O}\left(\frac{1}{n^{2}}\right),\]
where the constant
\[\gamma_{0} = \omega \left(\nu + \tfrac{3}{2}\right) + \beta \left(\ln \sqrt{\tfrac{2}{\omega}} - \tfrac{1}{2}\right)\]
is determined explicitly from the Langer-corrected WKB quantization condition. This expansion reveals a distinctive logarithmic growth that modifies the standard linear Weyl law, yielding the spectral counting function
\[N(E) = \frac{E}{2\omega} - \frac{\beta}{2\omega}\ln E + \mathcal{O}(1).\]
To complement the asymptotic analysis, we construct the exact Green's function and prove the Hilbert–Schmidt property of the resolvent. Numerical diagonalization using a logarithmic grid confirms the asymptotic formula with relative errors below $0.02\%$ for all $n \geq 5$, validating both the analytic predictions and the underlying WKB methodology.
These results provide the first complete spectral characterization of Schrödinger operators with logarithmic potentials in the presence of singular and confining terms, with potential applications to few-body quantum systems, spectral geometry, and the analysis of trace formulae.

Keywords

Schrödinger operators logarithmic potential spectral asymptotics WKB method Langer correction self-adjointness Green’s function Hilbert-Schmidt property modified Weyl law quantum dots Bose-Einstein condensates.

Review

2 Articles

Assessment Framework Construction Methodology

Organizational AI Readiness for Telecom Project Management: A Conceptual Review and Diagnostic Framework

Mohammed Abdullah Thabit Al-maazi, Ibrahim Alameri, Farouk A. Al-Fahaidy

2010-2024

2026-04-28

PDF

DOI: 10.59628/jast.v4i4.2682

Abstract

Telecommunications operators are under increasing pressure to use Artificial Intelligence (AI) to keep up with the recent technologies and stay ahead in the service provision advancement. However, within organizations that are not adequately prepared for AI adoption, many of these initiatives fail to gain traction. The study explores how existing academic research and practical frameworks can conceptualize organizational AI readiness in project-based telecom contexts. It synthesizes six peer-reviewed academic studies on AI readiness and digital transformation and four telecom-relevant AI readiness and maturity frameworks from industry bodies. Using a hybrid Technology–Organization–Environment (TOE) and People Process–Technology-in-use–Data (PPTD) lens, the 80 readiness indicators derived from the academic and practical resources were coded. Then, analyzed them through reflexive thematic analysis and identified nine interrelated AI readiness themes: strategic AI vision and business alignment; leadership, culture and change climate; human capital and AI skills; data assets, governance and protection; technology and infrastructure backbone; AI solutions, lifecycle and experimentation; organizational processes, governance and project operations; value realization and performance impact; and external ecosystem, regulation and partnerships. These themes are integrated into a conceptual diagnostic framework tailored to project management in telecom organizations and motivated by the challenges of communication service providers in contexts such as Yemen. The resulted framework addresses the gap of fragmented academic and practical perspectives. This offers telecom project management offices (PMOs) a conceptualizing mechanism to reflect on AI readiness, identify potential gaps and prioritizing interventions. In the same time, it provides a basis for future empirical validation and cross-sector comparison.

Keywords

Artificial Intelligence Organizational Readiness Project Management Telecommunications Digital Transformation Readiness Framework

Hierarchical taxonomy of DRL-based cybersecurity systems across learning paradigms, application domains, al- gorithms, environments, and explainability mechanisms

Smart cybersecurity strategies based on deep reinforcement learning : A Literature Review

Aleah Abdulkaher Alshamiri, Ghaleb H. Al Gaphari

2025-2033

2026-04-28

PDF

DOI: 10.59628/d80zj848

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