Journal of Engineering

The rapid growth of the Internet of Things (IoT) demands computing systems that remain
highly intelligent while adhering to tight energy constraints. For always-on edge
applications, traditional processors are too power-hungry. This neuromorphic system is
developed for IoT to achieve computing integrity and has remarkable efficiency. We propose
computer-memory architecture which essentially is event-driven processing and temporal
spike coding. Architectural breakthroughs include clockless processing and adaptive
precision and therefore exploit temporality with hierarchical event encoding. While current
hardware solutions show a power consumption of 70 μW to 680 μW, our system shows 10 – 100× improvement in overall efficiency. Testing proved that with radar gesture
recognition, audio pattern matching and visual event detection, we have more than 96 %
accuracy. Inference energy is 1.38 nJ, and molecular operation cost is 9.9 pJ of the
architecture with these efficient metrics, a new family of autonomous IoT applications can
be developed, from battery-free sensor networks to implantable devices that run for years
off a single charge.

TiO₂ famous the very best uranium elimination performance due to its excessive surface
region, chemical balance, and photocatalytic effectiveness. Titanium dioxide (TiO₂) has
proven promise as a photocatalyst and adsorbent for disposing of uranium from
radioactively contaminated water. The goal of this study was to synthesize and evaluate TiO₂
nanoparticles for uranium removal from radioactively infected water using sol–gel and
hydrothermal techniques. Under top-quality conditions, the synthesized TiO₂ done uranium
removal efficiencies exceeding 70%, demonstrating its potential as a fee-effective and
environmentally friendly fabric for radioactive wastewater treatment. The synthesis and
amendment of TiO₂ to improve uranium adsorption overall performance is the principal
focus of this investigation. To discover an excellent method for producing nano-composed
TiO₂ with advanced surface characteristics, several synthesis techniques, which include sol
Gel and Hydrothermal have been investigated. The effectiveness of uranium removal was
drastically studied on the subject of elements, including pH, temperature, touch time, TiO2,
and crystal form (anatase vs. Rutile). According to the information, the TiO₂ reveals the best
uranium elimination efficiency when synthesized in an acidic environment with anatage
dominance; under ideal occasions, this output can reach over 70% performance. Through
using middle wastewater, our work exhibits TiO₂ as a long-lasting and low-cost medium for
uranium removal.

This study investigated the challenges of implementing Building Information Modeling
(BIM) in residential complexes in Iraq. The research will aim at determining the most
prominent challenges that have affected the implementation of BIM, evaluating the
challenges based on the perceptions of the professionals, and presenting practical insights
that can be used to realize successful implementation. The mixed-method research design
was applied, and it included the literature review, expert interviews, and a questionnaire
survey of 67 professionals who were involved in the construction projects. The identified
challenges were ranked using the collected data with the help of Reliability testing and
Relative Importance Index (RII). The findings are that the most threatening impediments to
BIM implementation are the human and organizational factors. Particularly, the technical
unawareness and BIM perception, along with the insufficiency of training and competence,
were put first on the list of the most crucial challenges. Further, there was poor senior
management support and the absence of an enabling organizational environment, which
was noted to be a barrier to BIM adoption. Financial and infrastructural issues, such as the
software and the internet connectivity, on the other hand, were considered to have a lesser
effect. The conclusion is that the successful use of BIM in residential complexes in Iraq should
be oriented on a complex approach with capacity building, organizational commitment and
the development of effective national policies and regulatory frameworks to support the
digital revolution in housing industry.

The study examines temporal variation in water levels by calculating the surface area of the
Al-Hammar Marsh in southern Iraq over 11 years (2013–2023), because of the consistent
Landsat-8 and Landsat-9 data. Because it represents years of remarkable hydrological
diversity in Iraq, it provides a trusted assessment for the surface changes of Al-Hammar
marsh by using geographic information systems and remote sensing. The change in the
surface was determined by utilizing supervised classification (maximum likelihood) to
classify the region. Water and vegetation were the two land cover classes that we
determined using ArcMap software. Then the thematic maps were created by the same
software. The resulting signalize that the surface area changed a lot over the study years,
where the large area was recorded in 2019 (1144 km2), and the small area was recorded in
2023 (295 km2). The accuracy assessment showed the supervised classification provided
high trust, with overall accuracy ranging between 87 % to 98% and a kappa coefficient
ranging between 0.88 and 0.98, which indicated strong agreement.

This study investigated the effect of nanoclay (NC) additives on the mechanical
performance of high modulus asphalt mixtures (EME). The research studied NC at four
different binder weight percentages (0 %, 2 %, 4 %, 6 %) through Marshall stability tests
and indirect tensile strength (ITS) and resilient modulus (MR) evaluations at 5 °C, 25 °C and
40 °C. The results showed substantial improvements across all performance indicators. The
Marshall stability increased by 20.7 % when NC reached 6% but flow values decreased by
18.2 % for NC values between 4 % and 6 % because of enhanced permanent deformation
resistance. The ITS values showed a 16.5 % increase which demonstrated better tensile
strength performance. The MR values showed significant growth at all test temperatures
which reached 55 % at 5 °C and 66.7 % at 25 °C and 64.6 % at 40 °C. The material
demonstrated better elastic recovery through these tests, which were conducted at different
thermal conditions. The mixture containing 6 % NC reached a richness modulus (K) value
exceeding 3.4, which fulfilled the EME2 classification requirements. Statistical analysis
(ANOVA) and mechanical evaluation identified 4% NC as the optimal dosage, as it achieved
the maximum Marshall stiffness (6.18 kN/mm), while further increases to 6 % did not yield
statistically significant improvements. The research shows nanoclay acts as an effective
modifier that enhances both structural and mechanical properties of EME mixtures.

Constructing a geologically realistic reservoir model and accurately evaluating
petrophysical properties are critical components for effective reservoir management. Such
efforts enable reliable assessment of hydrocarbon potential and support predictive
development scenarios through numerical simulations. This study aims to characterize the
Yamama carbonate reservoir in the Ratawi Field, southern Iraq, and to build a static
geological model as a foundation for future dynamic simulation. Comprehensive well data,
including wireline logs, core analysis, and geological reports, were integrated to interpret
petrophysical parameters such as shale volume, effective porosity, and water saturation.
Additionally, facies classification was performed using cluster analysis to define lithological
variability across the reservoir. A structural framework was established based on contour
maps and well tops, followed by 3D property modeling using geostatistical techniques.
Experimental variogram models were constructed for each facies and zone to enhance
distribution accuracy. The Yamama Formation was confirmed -consistent with previous
studies- to consist of five vertical units, three reservoir-bearing (YA, YB, YC) and two barriers
(C1, C2). However, this study uniquely establishes an evaluation framework using data from
eight wells penetrating the formation, unlike earlier studies constrained by limited wells.
Among these units, YB demonstrated the most favorable properties, accounting for
approximately 63% of the estimated 1800 MMSTB OOIP, consistent with operator reports.
Overall, reservoir quality improves northwestward and declines eastward, with moderate
characteristics in the southern sector.

Thermal management has become a major issue in the latest high performance computing
machines because high CPU temperatures result in inefficient performance and decreased
hardware life span. In this work, the cooling performance of a finned metal foam heat sink
(FMFHS) was examined. The pore density values of tested copper metal foam (CMF) samples
with different values of PPI 5, 10 and 20, with a constant porosity of 90%. For reference,
these samples were measured by a conventional Aluminum plate-fin heat sink (CHS). The
work was performed under experimental conditions in which air directed over the heat sink
surface at air velocities (2.5, 3.0 and 3.5 m/s). The environmental temperature was fixed at
27 °C. Findings indicated that pore density strongly affected on the cooling behavior. The 5
PPI foam showed an improved thermal performance better than CHS, due to the open pores
and increased surface area, which enhance convective heat transfer. By contrast, the 10-PPI
demonstrated moderate copper foam performance, placed between PPI 5 and CHS. The 20
PPI foam showed the lowest heat removal rates. Under these conditions, the 5 PPI design
presented a 21.6 % increase in Nusselt number and a 16.9 % decrease in total thermal
resistance at 3.5 m/s and 120 W compared to CHS. This confirms that using low PPI copper
foams, such as 5-PPI in finned geometries, provides a considerable gain in cooling efficiency
for high-power electronic components. Therefore, in high-power CPU cooling systems
requiring high efficiency and compact size, it is recommended to use low PPI finned CMF
heat sinks.

This study presents a comprehensive methodology to improve monorail route selection in
Kirkuk city, Iraq using a quantitative GIS-based multi-criteria decision analysis. The primary
aim of this study is to develop and apply a quantitative, GIS-based multi-criteria decision
analysis framework for optimizing and objectively selecting the most suitable monorail
route in Kirkuk city, Iraq, by integrating spatial, topographic, accessibility, service coverage,
and economic factors in order to support sustainable and cost-effective urban transport
planning in a post-conflict context. The research area covers 460.89 km², including an
extensive road network of 5,533.27 km and 3,193 points of interest (POI). Four different
monorail routes were analysed and evaluated using OpenStreetMap data derived from an
analytic hierarchy process, digital elevation models and site suitability analysis. The
approach uses weighted graph construction, various shortest path methods, and a wide
range of performance metrics, including cost-effectiveness, service coverage, topographic
conditions, and accessibility. Route optimization includes terrain suitability (scores from
0.50 to 0.78), elevation profile (288–393m), gradient limitations (maximum score 0.20 to
0.32), and points of interest (POIs) within a service radius of 500 m to 1 km. Based on this,
Results shows Route 1 is the ideal choice as it found to be the most economical route (4.15
km, US$214.01 million), had the highest suitability score (0.70), and required the shortest
travel time (9.61 minutes). On the contrary, Route 0 had the widest service coverage (31.37
km² service area, 66.1 points of interest within 500 m).

This study presents a comprehensive methodology to improve monorail route selection in
Kirkuk city, Iraq using a quantitative GIS-based multi-criteria decision analysis. The primary
aim of this study is to develop and apply a quantitative, GIS-based multi-criteria decision
analysis framework for optimizing and objectively selecting the most suitable monorail
route in Kirkuk city, Iraq, by integrating spatial, topographic, accessibility, service coverage,
and economic factors in order to support sustainable and cost-effective urban transport
planning in a post-conflict context. The research area covers 460.89 km², including an
extensive road network of 5,533.27 km and 3,193 points of interest (POI). Four different
monorail routes were analysed and evaluated using OpenStreetMap data derived from an
analytic hierarchy process, digital elevation models and site suitability analysis. The
approach uses weighted graph construction, various shortest path methods, and a wide
range of performance metrics, including cost-effectiveness, service coverage, topographic
conditions, and accessibility. Route optimization includes terrain suitability (scores from
0.50 to 0.78), elevation profile (288–393m), gradient limitations (maximum score 0.20 to
0.32), and points of interest (POIs) within a service radius of 500 m to 1 km. Based on this,
Results shows Route 1 is the ideal choice as it found to be the most economical route (4.15
km, US$214.01 million), had the highest suitability score (0.70), and required the shortest
travel time (9.61 minutes). On the contrary, Route 0 had the widest service coverage (31.37
km² service area, 66.1 points of interest within 500 m).

Many industrial systems involve multiple criteria and objectives, and they are very complex
problems in computational science, such as task scheduling. We propose bi-criteria and bi
objective scheduling problems, which are solved by two nature-inspired evolutionary
algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is
characterized by scheduling a batch of tasks on multiple machines, and it is fundamental
because the solution should focus on the simultaneous optimization of two conflicting
objectives: the makespan minimization and the total tardiness minimization. This problem
is NP-Hard, and therefore, two evolutionary methods were used to search for solutions
intelligently in this huge, very complex space. In this research, A mathematical model of the
scheduling problem was developed based on the above objectives. Here, we proposed a
tailored tune-up of SA and BA, both of which have been specifically developed and
implemented to solve the proposed model for integrated scheduling and delivery, geared for
the bifunctional nature of the problem. Quantitative results indicate that the Bee Algorithm
(BA) achieves a more diverse Pareto front, with an average improvement of approximately
12–18 % in solution diversity compared to Simulated Annealing (SA). In contrast, SA
converges faster, reducing computational time by about 30–40 % for large problem
instances (n ≥ 80). Overall, BA provides better trade-offs between objectives, while SA offers
superior computational efficiency. The results showed that both algorithms can generate
solutions that are balanced and time-efficient

This paper proposes a hybrid speech enhancement estimator that integrates the
Perceptually-motivated Karhunen–Loève Transform (PKLT) with the Dual-Masking
Harmonic-based (DMH) algorithm in a unified framework termed PKDMH. The main novelty
lies in combining perceptual subspace projection with harmonic-residual suppression,
enabling the system to jointly remove noise while preserving speech-relevant spectral cues.
PKLT first performs perceptual subspace projection and suppresses inaudible components,
after which DMH eliminates remaining broadband and harmonic residuals. The proposed
PKDMH system was evaluated using the TIMIT dataset contaminated with five noise types:
White, Pink, F16, Airport, and Car noise—across five SNR levels (−10 dB, −5 dB, 0 dB, +5 dB,
+10 dB). Objective evaluation used the standard perceptual and signal-level measures of
PESQ, STOI, SNRseg, Csig, Cbak and Covl. Results show that the enhanced quality of
separation and speech signal ratio between enhanced signals and original target binary
mask cause obvious improvements in quantity, with average PESQ gains of 1.099, 0.888 and
0.824 for White, Pink and F16 noise, respectively. These results bring out the subjective
benefit of the PKDMH cascade, in terms of being a more robust enhancement approach under
low SNR and acoustically varying cases.

Groundwater resources in arid and semi-arid regions are highly sensitive to climate
variability, and assessing future water balance conditions is essential for sustainable
management. This study evaluates the effect of climate change on the water balance of the
Al-Teeb district in southern Iraq under both historical (1993–2023) and future (2031–2050)
climate conditions. The analysis was performed with the Thornthwaite-Lerner method,
combined with statistically downscaled climate projections produced through Long Ashton
Research Station Weather Generator (LARS-WG, v8) that was driven by HadGEM3-GC31-LL
GCM for the SSP2-4. 5 scenarios. During the reference period, mean annual precipitation
amounted to 178.9 mm/yr, and corrected potential evapotranspiration (PETc) was 2535
mm/yr, resulting in a large annual water deficit (2414 mm/yr) and indicating arid
conditions in this region. Future simulations indicate a rise in precipitation (258.4 mm/yr),
but a sharper increase in PETc to 4011 mm/yr, resulting in a larger deficit (3853 mm/yr)
while the region remains arid. Groundwater recharge, estimated using the coefficient
approach, was 8.9 mm/yr in the baseline and 12.9 mm/yr in the future scenario. Although
rainfall is projected to increase, the strong evaporative demand severely restricts recharge
opportunities. These findings highlight the urgent need for adaptive groundwater
management strategies to mitigate intensifying aridity and secure long-term water
availability in the Al-Teeb district.

In this work, an experimental (hardware-in-the-loop) and numerical study of a 50W
photovoltaic (PV) module with an ML2440 solar charge controller is presented under
different levels of solar irradiance conditions, using a resistive load. Three test cases were
considered: no tracking and two resistive loads (90 Ω and 115 Ω). Theoretical power and
efficiency were predicted from the incident solar irradiance, panel temperature and module
characteristics, and experimental measurements were then juxtaposed with the calculated
values to assess both the model’s accuracy and the controller’s performance. The maximum
measured output reached 49.70 W when the irradiance was 1000 W/m², and the load
resistance was set to its optimum of 115 Ω, which nearly matches the predicted 50.30 W;
this corresponds to a relative discrepancy of roughly 1.2 %. By contrast, the highest power
recorded without tracking was 46.51 W, and the average departures from the ideal power
were larger. An examination of the RMSE revealed that the scenario without tracking
incurred the greatest deviations—7.92 W in power and a 2.84 % drop in efficiency—
whereas the 115 Ω and 90 Ω loads each produced smaller RMSE values than the other load
conditions, reflecting a reduction of the error to as low as 4.12 W and 1.87 %.The results of
the relative error analysis also verified the outstanding characteristics of MPPT-based
configurations. The results achieved confirm the effectiveness of the ML2440 controller for
improving PV output by optimal load matching and demonstrate that the proposed
numerical model can be utilized as a predictive tool to evaluate the performance of PV
systems.