Journal of Engineering

This study presents an integrated solution to the challenges in the global fashion and design
industry, prioritizing worker well-being and environmental sustainability. Through an
ergonomic framework, it aims to achieve sustainability and cost-effectiveness. The research
employs established tools like RULA and REBA and diverse methods, including observations,
interviews, and questionnaires, to quantitatively and qualitatively assess ergonomic risks.
The study guides the clothing sector towards a more ethical, sustainable, and efficient
production paradigm, bridging the gap between ergonomics, sustainability, and cost
effectiveness. It addresses the need for a conscientious transformation, ensuring economic
growth aligns with workers' welfare and environmental responsibility.

Software Defined Networking (SDN) allows for more flexible network administration than
traditional architectures. Software-defined networks (SDNs) efficiently manage data flows
and optimize network resources. However, heterogeneity influences the quality of the
services. (QoS) needs and network resource demands. They behave differently when
traveling to their last point. Currently, numerous data center networks (DCNs) struggle with
the unfair use of several network resources by big packets (Elephant flowing) arriving
during any instant affecting specific flows (mice flow). Elephant Flows (EF) account for just
a small percentage of the entire traffic. Nevertheless, they are considered Long-lasting (LLF)
and often burn network resources. Their actions cause congestion and delays in most Mice
Flows (MF). Forecasting and categorizing flow traffic is essential for optimal resource usage,
QoS provisioning, and reducing network congestion and delays. This paper suggested a
third-generation Single Spike Neural Network (SSNN) supervised learning approach using
temporal coding to identify heterogeneous traffic. The classifier approach uses three
features: flow time, byte rate, and packet rate. The SSNN is then taught to categorize the
traffic into two classes. This training classifies two types of traffic: elephant and mice flow.
The effectiveness of the algorithm was examined when classifying traffic using many metrics
and its efficiency was proven as it was able to reduce the average error and its accuracy
reached 99%. The suggested model's usefulness is demonstrated by its efficient training
procedure, which provides rapid and accurate results.

This research aims to reduce the number of experiments by using the Taguchi technique. It
will be applied on adding copper nano particles and study it's effect on shape recovery for a
shape memory alloy (83% Cu- 13% Al- 4%Ni). Different proportions of nano were added to
the alloy in return for changing the proportion of copper while maintaining the proportions
of nickel and aluminum constant. Powder metallurgy technique was used to manufactured
the samples. Two types of tests were performed: physical tests, including X-ray diffraction
(XRD) and scanning electron microscopy (SEM), were used to inspect raw materials before
manufacturing and to inspect samples after manufacturing. A mechanical test of the shape
memory effect (SME%) was conducted for different a compression ratio. The results indicate
that the addition of copper nano particles reduces shape recovery at a compression ratio of
3%. Analysis of results represented by Signal to Noise ratio (S/N) and ANOVA show the most
significant factor in shape recovery was copper nano particles followed by copper particles
and the most contribution factor was copper nano particles in percentage 87.82%.

The artistic dimension appears as an important factor in urban townscape's identity
shaping, as many cities in the world have a different identity through the different artistic
elements in it, the artistic dimension is meant within the research (set of artistic elements
that can contribute to urban identity shaping, whether on architecture or on urban design in
addition to public, urban arts). Many previous global studies have dealt with one type or
more of art affecting the urban townscape identity of specific cities as a case study. Thus, we
can diagnose the research problem as (the lack of local knowledge about the role of the
artistic dimension in all its components in achieving the urban townscape identity), and the
research assumes that (the artistic dimension has an important and clear impact on shaping
and achieving the identity of the urban townscape, as is the case in the artistic dimension
represented by advertising art in Al-Kindi Street), so the research aims to (Clarifying and
highlighting the importance of the artistic dimension in achieving the identity of the urban
scene and its role in the mental image and memory of society) . Al-Kindi Street in Baghdad is
a local case study to clarify the impact of the artistic dimension represented by advertising
art, the research concluded that advertising art has a clear and strong impact on the urban
townscape and achieving its clear identity, and the research recommends paying attention
to the arts to improve the urban townscape in Baghdad.

This research deals with the review of former research that made to solve the challenges
and complexities of both static and dynamic soil structure interaction through discussing
advanced computational models and their applications and exploring methods of solving
the challenges of soil structure interaction in foundation engineering to provide a guide for
the engineering community through the complexes of soil structure interaction. It was
found that the numerical analysis for both static and dynamic soil structure interaction
using the finite element method with the aid of advanced computional models is ideal for
dealing with the non-linearity of soil and structure properties and loading conditions and
that the use of interface elements which is essential for idealization of forces between two
different mediums and that the interaction effect of adjacent structures cannot be ignored
in the seismic design of high raised buildings especially for buildings in the middle and the
effect of non-linearity of soil properties can be ignored in seismic design upon increasing in
soil stiffness, slenderness ratio of buildings and when the foundation soil was improved.
The cost and time of dynamic soil structure analysis can be reduced by using the equivalent
pier method, Mohr Columb Model in ABAQUS software, multi step and data-based method
and there is a need to add guidelines on the implementation of soil structural interaction in
seismic codes in order to include it in the regular design practice of structures. Moreover, it
was found that the non-linearity and uncertainty of soil properties greatly affect the safety
of structures and it is essential to consider static soil structure interaction analysis to assure
safe and economical design of structures.

Precipitation is the most important weather parameter, which has direct and indirect
effects on life on our planet. One of the most relevant climate change consequences is
extreme weather conditions, such as floods and droughts. Up to now, climate model
projections have remained uncertain, therefore, more accurate precipitation modelling
techniques are necessary. Due to the complexity of relationships among metrological
parameters, traditional statistical modelling tools are ineffective in forecasting and
predicting weather conditions. In this study, data mining techniques were applied to
metrological data to predict daily precipitation using Multilinear regression (MLR) along
with two artificial intelligence (AI) techniques, specifically Artificial Neural Networks (ANN)
and Neuro-Fuzzy Inference System (ANFIS). A total of 10 daily metrological variables, for 13
years, namely Maximum temperature (Tmax), minimum temperature (Tmin), maximum
humidity (Hmax), minimum humidity (Hmin), wind speed (Ws), wind direction (Wd), cloud
cover (Cv), sea pressure (SEAp), station pressure (STAp) and relative humidity (RH) are
used to predict precipitation (P). Both AI systems showed acceptable results predicting daily
precipitation from observed meteorological parameters with a coefficient of determination
(R2) of 0.75 and 0.72 for model calibration of ANN and ANFIS methods, respectively. The
results of the ANN and ANFIS testing methods were 0.55 and 0.62, respectively. Outcomes
of the study showed that the ANN model may have overfitted the results in the calibration
section of the process compared to the ANFIS method, which performed better in the testing
section of the evaluation process. In ANFIS modelling, for several input variables up to 6
variables, this study recommends using the grid partition method to divide variable ranges
into membership functions. For input variables of more than 6 variables, sub-clustering
method is recommended.

Response of cross-ply plates subjected to transient load is obtained using five variables
refined plate theory, and four variables plate theory. Equations of motion are derived
through the principle of virtual work. Navier series used for simply supported laminated
plates. The results of this work are presented for different parameters, such as the ply
number, thickness, and modulus ratio with mechanical load (sinusoidal and step pulses),
which are compared with those obtained using high-order shear plate theory. Five variables
of refined plate theory give results that are considerably different from the four variables of
refined plate theory and higher-order theory. The obtained results from the four variables
theory have the same behavior as those given by higher order theory, but are under
predicted with small time shifting.

The use of lightweight aggregates in cement concrete manufacturing solves the issue of
drying shrinkage over the concrete's life span; nevertheless, the use of artificial lightweight
sand may increase this issue in the cement mortar. This research looks at how using lighter
sand affects the non-mechanical qualities of cement mortar, namely the dry shrinkage
property. It was prepared lightweight sand by pulverising pumice stone, screening it
through a 1.18 mm sieve, and combining it with regular natural sand in varied amounts. It
was tested various replacement percentages for lightweight sand by weight, such as 10%,
12%, 14%, 16%, and 18%, while keeping a single control sample without any lightweight
pulverized pumice sand. As the proportion of pulverized pumice lightweight fine aggregate
increases, the dry shrinkage of cement mortars containing pulverised lightweight pumice
fine aggregate enhanced up to 161%, which has a negative impact on the durability of the
cement mortar despite improved compressive and split tensile strengths of cement mortar.
Moreover, the value of the brittleness index of the cement mortar reduced due to
improvement of the split tensile strength. However, the bulk dry density of the cement
mortar reduces up to 13.2%, which supports the reduction of the dead load in the high-rise
buildings

Recently, implantable antennas have gained prominence in biomedical research owing to
their compact design and efficient performance and extensive potential in biomedical and
wireless communication applications. One such application is in the biomedical field, where
the designed system must function within human body tissues and interact with an external
device. To implement this communication framework, both advanced software and proper
hardware design are essential. The antenna that is designed for biomedical applications
must fulfill several requirements including energy efficiency, compact size, and multi-band
operations. Therefore, designing an antenna with large bandwidth, multiband capability,
circular polarization, and a compact size is essential for medical applications. From that
point of view, this paper aims to survey existing antenna designs in literature for implantable
medical devices (IMDs). The review conducted in this paper will specifically focus on three
types of implantable antennas which are dual-band, circular polarized, and multi-band
circular polarized antennas. Besides, we analyze the results of the most recently published
articles and compare them with existing literature. The key challenges faced in implantable
antenna design will also be discussed in detail.

A road network uses rigid pavement for various purposes, still, it can face several
challenges, including cracking from temperature changes, shrinkage, load stress application,
brittleness, and flexural and tensile weakness. The thickness of rigid pavement significantly
influences its performance and durability. A thicker slab distributes weight more effectively
on the subgrade; however, greater thickness significantly raises construction costs, requires
more resources, and negatively impacts the natural environment. The purpose of this study
is to find out how adding a 1% volume fraction of steel and glass fiber in single and hybrid
shapes changes the mechanical properties of concrete and pavement thickness. The
compressive strength test, the flexural strength test, and the splitting tensile test were used
to investigate the change in mechanical properties and The software (EMS) was selected to
compute the thickness of the concrete pavement. The findings indicated a significant
improvement in the mechanical characteristics resulting from the reinforcement of concrete
with fibers. This was shown by a modest increase in compressive strength, reaching 9.1%
after 90 days, along with significant enhancements in tensile and flexural strength, achieving
72.5% and 70% after 90 days, respectively. These adjustments, along with the use of PCASE
EMS, resulted in a 30% decrease in thickness relative to the reference mixture.

This study used a spray pyrolysis approach to create thin films from SnO2 doped with 2%
Co on a heated glass substrate at 400°C and investigated how the structural and optical
characteristics are affected by non-thermal plasma. X-ray diffraction analysis was initially
employed to look into the structural characteristics, and the results indicate that the SnO2
and SnO2:Co thin film are polycrystalline and have tetragonal structure, peak formation has
occurred in (110), (101), and (211), which correlate to the subsequent diffraction angles,
respectively (26.55⁰), (33.90⁰), and (51.55⁰). A peak associated with Co was also observed
at (311), which is equivalent to the (36.78⁰) diffraction angle. According to AFM analysis, the
grain size decreases from 64.01 nm to 59.10 nm after doping. Roughness and root mean
square also appears to increase after doping, according to the UV-VIS spectrometer analysis,
the transmittance increases with doping and decreases with non-thermal plasma exposure,
the energy gap value increases during Non-thermal plasma exposure and its decrease after
doping. Additionally, the absorbance, absorbance coefficient, refractive index and extinction
coefficient rise following Cold plasma exposure.

The Third Generation Partnership specified the 5th Generation New Radio standard to
fulfill the growing demand of wireless traffic and the increased need for higher data rates.
With the spread of new applications, efficient scheduling algorithms are mandatory to
handle the allocation of the limited spectrum resources to various types of traffic and to
guarantee the requirements of the quality of service and the quality of experience informed
by users. In this paper several scheduling algorithms specifically Round Robin, Best Channel
Quality Indicator, Proportional Fair, Modified Largest Weighted Delay First, Exponential
Proportional Fair, and Logarithm Rule are evaluated and their performances are compared
to each other. The simulation shows that Round Robin and Proportional Fair perform well
for non-real time services and Voice over Internet Protocol traffic, particularly for simple
systems since they offer high level of fairness between users and low packet loss ratio. On
the other hand, Best Channel Quality Indicator produces poor performance for its very low
fairness index, very high packet loss ratio and long delay values making it impractical to
implement in most scenarios. The other three algorithms perform effectively for real time
services specifically for video traffic. While Exponential Proportional Fair algorithm has the
lowest values of delay, Logarithm Rule algorithm gives the highest data rate and the lowest
packet loss ratio with high index of fairness.