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Formatting a questionnaire for the quality control of river bank roads

  • Zahraa Amad Salem EMAIL logo and Asma Thamir Ibraheem ORCID logo
Published/Copyright: April 8, 2024
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Open Engineering
From the journal Open Engineering Volume 14 Issue 1

Abstract

The quality control of road implementation on the rim and the strengthening of river edges to prevent road collapses need to be studied and developed continuously. In order to carry out maintenance in a cost-effective manner as much as possible, this research aims to provide a way to reach a better understanding of the quality control of riverbank roads. The study conducted an SWOT questionnaire, which is a means of discovering and evaluating the strengths, weaknesses, opportunities, and threats in the field of quality control of river bank roads, and it can help in identifying the optimal path to achieve specific goals and improve the quality of roads in these areas and determine the necessary steps to improve performance and quality in general. It also contributes to enhancing joint cooperation between the concerned parties. The type of questionnaire was closed and included two parts: the first part is the personal information of the respondents, and the second part is related to the subject of the study, which in turn includes four basic axes. It relates to the elements of the SWOT tool and includes questions ranging from 1 to 44. Sixty people from different academic levels in Iraq responded to the questionnaire, and the answers were according to a five-point Likert scale. The Statistical Package for Social Sciences version 26 was used for statistical analysis, and the statistical methods used in this study are Cronbach’s alpha test to measure reliability, validity of the test to measure the validity of the research tool, frequencies, and percentages, or what is known as relative frequencies, arithmetic mean, and standard deviation, relative importance index.

Keywords: cost effective; opportunities; pavement; quality control; riverbank roads; socioeconomic situations; SWOT questionnaire; transportation engineering

Abbreviations

SA

Strongly agree

A

Agree

Amb

Ambivalent

DA

Disagree

SDA

Strongly disagree

RII

Relative importance index

AM

Arithmetic mean

SD

Standard deviation

Imp. Lev

Importance level

1 Introduction

Formatting a questionnaire SWOT for the quality control of river bank roads. It focuses on analyzing the strengths, weaknesses, opportunities, and threats related to the quality control of river bank roads. It helps in evaluating the quality of riverbank roads and identifying common problems and factors affecting quality, and the results of the questionnaire can be used to improve performance. Quality control in the construction and maintenance of roads refers to the level of standardization and consistency of production, which must also enable more efficient material utilization and methodical construction [1]. Consequently, good quality control reduces construction and maintenance costs, as well as vehicle operating, transportation, and maintenance costs. The cost of quality control is estimated to be 1.5–2% of the overall cost of building, with a direct and indirect economic return of 5–10% of the construction cost, and sometimes even more [1,2]. Two forms of quality control may be addressed during construction and maintenance: process control and end-result control [1]. In the process control form, the designer predetermines the sort of equipment to be utilized, the construction technique to be employed, and so on. Falade also determined the amount of effort required to obtain the desired objectives. Sakhare and Chougule [3] offered an innovative road profile estimator that provides essential information (road roughness and frequency) for vehicle dynamics adjustment using conventional sensors, such as accelerometers or displacement/velocity sensors, which are simple to mount, inexpensive, and useful for estimating all suspension variables. After estimating the dynamic road signal, a Fourier analysis is utilized to compute the road roughness condition live. Shinde et al. [4] presented a brief historical overview of the rate-quality control approach and its use in identifying dangerous highway sites. Identifying hazardous locations and the associated problems are provided, with an emphasis on the rate quality control method. One of the weaknesses of the rate quality control method is the limitation of collected data from similar locations. An improvement of the rate quality control method is provided to estimate the crash rate by applying the expected crash rate model. The improvement combines the rate quality control method with the safety performance function, which accounts for factors that probably have a close relationship to the crash rate at the treated site and the reference sites. Locations could be considered reference sites even if they have different roadway characteristics than the treated site [5]. The project aimed to study whether the process of converting an SWOT analysis into a strategic plan could be assisted with some simple rational quantitative model as an augmented SWOT analysis. By using mathematical approaches, including quantifying techniques, the “maximum subarray” method, and fuzzy mathematics, one or more heuristic rules are derived from an SWOT analysis. This technique, which operates by “peeling back layers of the company,” is designed for use in the preliminary stages of decision-making processes and can be used as a tool for evaluation of the strategic position of organizations of many kinds (for-profit enterprises, local and national governments, construction, etc.). The aim of this study is to conduct an SWOT questionnaire and identify strengths, weaknesses, opportunities, and threats in the quality control process, and this questionnaire helps to identify areas that should be focused on and improved to improve the quality control of riverbank roads, reduce risks and threats, and develop future plans to improve quality control. If quality control of riverbank roads is neglected, it is expected that several problems will appear that affect the quality of the roads, leading to road deterioration, traffic disruption, and an increase in maintenance costs. It may also affect the surrounding environment and cause pollution and changes in water flow.

2 Methodology

The methodology of this article can be summarized as the following steps:

  1. Designing the questionnaire form in its final form and determining the axes of the questions.

  2. Choosing the research sample to be questioned.

  3. Determining the sample size.

  4. Distributing the questionnaire form to the sample members to answer the questions contained therein.

  5. Collecting questionnaires from sample members, entering them into the computer, and processing them statistically using the Statistical Package for Social Sciences (SPSS) program.

  6. Extracting, analyzing, and discussing the results.

3 SWOT analysis

SWOT analysis is an analysis technique used to evaluate the “strengths,” “weaknesses,” “opportunities,” and “threats” of an organization, plan, project, person, or business. SWOT analysis is a simple but powerful tool for quantifying an organization’s resource capabilities and deficiencies, market opportunities, and external threats to its future. SWOT analysis is a strategic planning framework used in evaluating an organization, plan, project, or business activity. Therefore, SWOT analysis is an important tool for analyzing the situation [6].

The closed questionnaire consists of two sections that include the subject of the study and personal information about the sample.

Part One: personal information for respondents. Part Two: relates to the subject of the study, which in turn includes four basic axes related to the elements of the SWOT analysis tool and includes questions extending from 1 to 44. To balance its scores, the five-point Likert scale was utilized, which is regarded as one of the most extensively used measures for evaluating opinions. It is also regarded as the most widely used attitude scale for determining what an individual believes or perceives. The following weights were assigned to the five alternatives (Table 1).

Table 1

Five-point Likert scale

Answer Strongly agree (SA) Agree (A) Ambivalent (Amb) Disagree (DA) Strongly disagree (SDA)
Degree 5 4 3 2 1

4 Research sample

The most essential feature of the questionnaire method and its effectiveness is the selection of the study sample, because it affects the accuracy and reliability of the study [5]. As a result, the sample size necessary (per ASTM-E122-1979) is determined by the kind of distribution and the level of confidence. Table 2 presents the desired confidence level for the sample size. The researcher picked the top limit of the confidence level (99.7), that is, with a sample size of (n = 25) [7], and to boost accuracy, the sample size was raised to 60 respondents. In this research, all respondents included in this questionnaire were selected within the specialty of civil engineering in accordance with the research topic. So, the number of received questionnaire forms is greater than 25 and that will achieve a confidence level equal to 99.7%. These 60 forms will be depended on as a basis for the statistical analysis.

Table 2

Sample size for required confidence level organization is identified by examining the elements in its ASTM-E122 [8]

Confidence level (%) Confidence factor Sample size (N)
Normal distribution Triangular distribution
95 1.96 11 16
99 2.58 19 28
99.7 3.00 25 38

5 Statistical methods used in the study

In this study, the software SPSS version 26 was used. The following statistical approaches were utilized for statistical analysis:

  • Cronbach’s alpha test to measure reliability.

  • Validity of the test to measure the validity of the research tool.

  • Frequencies and percentages, or what is known as relative frequencies.

  • Arithmetic mean and standard deviation.

  • Relative importance index (RII).

5.1 Relative importance index

The RII is a measure used in data analysis to determine the importance of each variable in the study compared to others [9]. The researcher used the RII technique to determine the relative importance of the factors – a non-parametric technique usually used by construction and facilities management scholars to assess questionnaire responses that represent an ordinal measurement [10]. The relative importance indices are determined using expression (1) [11]

(1) R I I = ∑ W A × N ,

where W is the weight given to any factor by responders and will range from 1 to 5, A is the highest weight (in this case 5), and N is the total number of respondents.

The RII value ranges from 0 to 1 with 0 not inclusive. It shows that the higher the value of RII, the more important the sustainable criteria and vice versa [12] (Table 3).

Table 3

Importance level from RII [12]

RII values Importance level
0.8 < RII ≤ 1 High H
0.6 < RII ≤ 0.8 High-medium H-M
0.4 < RII ≤ 0.6 Medium M
0.2 ≤ RII ≤ 0.4 Medium-low M-L
0 ≤ RII ≤ 0.2 Low L

5.2 Arithmetic mean

The arithmetic mean is the average of the data set which is calculated by adding all the data values together and dividing it by the total number of data sets [10]. The arithmetic mean for each option was calculated by using the following formula:

(2) AM = ∑ ( X 1 × S 1 + X 2 × S 2 + X 3 × S 3 . . . . . Xn × Sn ) N ,

where AM is the arithmetic mean (1 ≤ MS < 5), X is the frequency of each rating for each factor or option, S is the weight given to each factor by the respondents and will range from 1 to 5 where “1” is less significant and “5” is extremely significant, and N is the total number of responses.

5.3 Standard deviation

The standard deviation (S) measures the value of the dispersion or the difference between the mean. A lower standard deviation value indicates that the data content will be closer to the mean (also called the expected value). A variation of the high standard indicates that the content of the data deviates over a wide range of values [13]. The calculation of the standard deviation model (S) for each measure is based on the following formula:

(3) S = 1 ( n − 1 ) ∑ i = 1 n ( Xi − X ́ ) 2

where S is the standard deviation, X ́ is the sample mean, Xi is the individual sample values, and n is the sample size.

5.4 Validity

Validity simply means that a test instrument is accurately measuring what it is supposed to or validity is the extent to which a test measures what it claims to measure. It is vital for a test to be valid in order for the results to be accurately applied and interpreted [14]. Validity is the same as (square root of the reliability coefficient); the validity of the question can be seen calculated by the formula:

(4) V = α 2 ,

where V is the validity, and α is the reliability.

5.5 Reliability

Reliability refers to the consistency or stability of a measurement. A test or instrument with good reliability means that the respondent will obtain the same score on repeated testing as long as no other extraneous factors affect the score. Lu and Weng [15] represent the method by which it can make sure that you get almost the same results when reusing the questionnaire more than once in the same group of individuals under the same circumstances, or the coherence of the answers to the questions respondents if the same questionnaire is used more than once in the same conditions. To measure the reliability, there are two common methods depending on the type of instrument and its purpose, including

  1. Test–retest (determines repeatability)

  2. Measures of inner consistency (such as Cronbach’s alpha reliability coefficient or split-half analysis) determine how well items contained in the questionnaire measure the “same thing” [16]. The reliability coefficient takes values ranging between 0.00 and 1.00; if there is no reliability in the data, it will be equal to 0.00, and on the contrary, if data have complete reliability, it will be equal to 1.00 [14]. The appropriate reliability coefficient is 0.7 and more, and high-reliability coefficient when it reaches 0.8 and more, and it is medium if it ranges between 0.6 and 0.7, and low if it is less than that [17]. The researcher used the SPSS-V26 to compute the reliability coefficients of the questionnaire (Cronbach’s alpha). Also, it can be calculated by using equation (5)

(5) α = k k − 1 1 − ∑ Si 2 St 2 ,

where k is the number of elements in the group, Si is the total variation of the elements, and St is the total score variation of the element.

6 Results for validity and reliability of the questionnaire

To ensure validity and reliability of the questionnaire as study tools, we use these ways by the SPSS-V26 program.

6.1 Cronbach’s alpha (reliability coefficient)

The researcher performed reliability stages on the sample, where we utilized Cronbach’s alpha technique to test the reliability of the questionnaire and discovered that the reliability coefficients were quite high, ranging between 0.908 and 0.956. The Cronbach’s alpha findings are displayed in Table 4.

Table 4

Cronbach’s alpha coefficient for the questionnaire

Axis title Cronbach’s alpha No. of items
Strengths 0.920 16
Weaknesses 0.930 9
Opportunities 0.956 11
Threats 0.908 8

The validity coefficient was derived by taking the square root of the reliability coefficient. The validity coefficient findings are provided in Table 5.

Table 5

Validity coefficient of the study

Axis title Cronbach’s alpha Validity coefficient
Strengths 0.920 0.959
Weaknesses 0.930 0.964
Opportunities 0.956 0.978
Threats 0.908 0.953

7 SWOT analysis results

7.1 Part one: personal information of the respondents

Following the collection of questionnaire forms from respondents, the findings will be evaluated and discussed in line with the components mentioned, resulting in each axis being investigated and discussed individually. The researcher used SPSSV-26.

7.1.1 Gender

Table 6 shows the frequency distribution of respondents according to gender: with 34 individuals identified as male (56.67%) and 26 individuals as female (43.33%). In this table, the higher percentage goes to males.

Table 6

Frequency distribution according to gender

Gender Frequency Percentage
Male 34 56.67
Female 26 43.33
Total 60 100

7.1.2 Scientific qualification

Table 7 shows the frequency distribution of respondents according to scientific qualification: 61.67% have a B.Sc., 25% have an M.Sc., and finally 13.3% have a Ph.D. In this table, the higher percentage goes to B.Sc. We note the diversity in scientific qualifications, which indicates the presence of a range of expertise and experiences within the sample.

Table 7

Frequency distribution according to scientific qualification

Scientific qualification Frequency Percentage
B.Sc. 37 61.67
M.Sc. 15 25
Ph.D. 8 13.3
Total 60 100

7.1.3 General specialty

Table 8 shows the frequency distribution of respondents according to general specialty. It is worth noting that all of the respondents included in the questionnaire, which constitute 100%, as the researcher focused on them being within the civil engineering specialization in a way that suits the subject of the research. This indicates the presence of a homogeneous group in terms of general specialization.

Table 8

Frequency distribution according to the general specialty

General specialty Frequency Percentage
Civil engineering 60 100
Total 60 100

7.1.4 No. of experience years of the respondents

Table 9 shows the frequency distribution of respondents according to No. of experience years; the study sample consists of four groups: the first one is with experience of less than 5 years by 15%, the second group is for those who have actual experience between 5 and 15 years by 38.33%, the third group is for employees who have actual experience between 16 and 25 years by 30%, and the fourth group is for those who have an actual experience of more than 25 years by 16.67%, and in this table, the higher percentage goes to 5–15 years.

Table 9

No. of experience year frequency distribution

No. of experience years Frequency Percentage
Less than 5 years 9 15
From 5 to 15 years 23 38.33
From 16 to 25 years 18 30
More than 25 years 10 16.67
Total 60 100

7.1.5 Work specialty

Table 10 shows the frequency distribution of respondents according to work specialty: higher management constitutes 8.33%, middle management constitutes 16.67%, planning and follow-up 8.33%, design 6.67%, implementation 13.33%, supervision 35%, operation and maintenance 5%, and finally education institution 8.33%. In this table, the higher percentage goes to supervision.

Table 10

Frequency distribution according to work specialty

Work specialty Frequency Percentage
Higher management 5 8.33
Middle management 10 16.67
Planning and follow-up 5 8.33
Design 3 6.67
Implementation 8 13.33
Supervision 21 35
Operating and maintenance 3 5
Education institution 5 8.33
Total 60 100

7.2 Part two: SWOT analysis components

The SWOT analysis questionnaire was created by containing a group of questions; each group was associated with one of the SWOT analysis parts, each question will be analyzed by RII, AM, and SD. The tables show the questions and the answers that we have collected, and these tables also contain the statistical analysis of these answers.

7.2.1 Strengths

First, the primary skills and attributes of a project are referred to as its strengths. The goal of identifying the project’s strengths is to discover and highlight the positive qualities and traits that define it and make it distinctive and appealing, therefore contributing to its success and sustainability. Identifying the strengths of river bank roads, strengthening and maintaining them, helps to improve road safety and reduce traffic accidents, resulting in a safer and more comfortable traffic environment for everyone. Table 11 shows the questions and answers of the SWOT analysis strength (Figure 1).

Table 11

SWOT analysis strength point questions, answers, and statistical analysis

Questions SA A Amb DA SDA AM SD RII Rank Imp. level
1. Do you support the existence of a plan for the management and maintenance of river bank roads? N 16 30 7 5 2 3.88 1.01 0.78 12 H-M
% 26.7 50 11.7 8.3 3.3
2. Do you support the existence of a plan to use modern systems in the development and maintenance of river bank roads? N 20 26 8 4 2 3.97 1.02 0.79 8 H-M
% 33.3 43.3 13.3 6.7 3.3
3. Are the implementation priorities of road projects determined according to the quality of the soil and the topography of the project lands? N 21 34 5 0 0 4.27 0.61 0.85 2 H
% 35 56.7 8.3 0 0
4. Do you support that the Roads Administration in Iraq has work teams with diverse experience and skills in different fields that enhance the ability to implement and maintain riverbank roads with high quality? N 13 31 9 5 2 3.8 0.99 0.76 14 H-M
% 21.7 51.7 15 8.3 3.3
5. Is the logical relationship between the number and growth of population, the number of vehicles and road capacity taken into account? N 16 29 9 6 0 3.92 0.91 0.78 10 H-M
% 26.7 48.3 15 10 0
6. Are the concepts and requirements of sustainable development taken into account when preparing the integrated feasibility study for riverbank roads projects? N 18 29 8 3 2 3.97 0.97 0.79 9 H-M
% 30 48.3 13.3 5 3.3
7. Are the infrastructure near the project area and ways to best benefit from it taken into account? N 18 30 8 3 1 4.02 0.89 0.80 6 H-M
% 30 50 13.3 5 1.7
8. Do you support the existence of a plan to monitor the environmental impacts of energy uses and waste? N 17 31 5 4 3 3.92 1.05 0.78 11 H-M
% 28.3 51.7 8.3 6.7 5
9. Do you support the existence of a plan for cooperation with scientific institutions in the field of renewable energy uses? N 16 35 6 3 0 4.07 0.76 0.81 4 H
% 26.7 58.3 10 5 0
10. Do you support the identification and classification of construction materials and other materials used in riverbank road projects? N 14 38 5 3 0 4.05 0.72 0.81 5 H
% 23.3 63.3 8.3 5 0
11. Do you support the existence of a plan for the management of tests, quality control and assurance? N 17 36 5 2 0 4.13 0.7 0.83 3 H
% 28.3 60 8.3 3.3 0
12. Do you support the existence of a plan for the management of construction materials waste and construction waste? N 13 30 9 5 3 3.75 1.05 0.75 15 H-M
% 21.7 50 15 8.3 5
13. Do you support the use of modern software in development and processing of designs? N 21 35 4 0 0 4.28 0.58 0.86 1 H
% 35 58.3 6.7 0 0
14. Do you support a consistent methodology for nominating employees to work in positions of responsibility? N 11 31 6 7 5 3.6 1.17 0.72 16 H-M
% 18.3 51.7 10 11.7 8.3
15. Do you support the issuance of periodic bulletins or booklets on concepts and applications of sustainable development related to riverbank road projects? N 12 34 7 5 2 3.82 0.97 0.76 13 H-M
% 20 56.7 11.7 8.3 3.3
16. Do you support the existence of an awareness and guidance program for citizens regarding the importance of riverbank roads and the necessity of preserving them as one of the foundations of national security? N 21 26 7 4 2 4 1.03 0.80 7 H-M
% 35 43.3 11.7 6.7 3.3
Total N 264 505 108 59 24 3.96 0.92 0.79 — H-M
% 27.5 52.6 11.3 6.1 2.5

Note: SA: strongly agree; A: agree; Amb: ambivalent; DA: disagree; SDA: strongly disagree; AM: arithmetic mean; SD: standard deviation; RII: relative importance indices; Imp: importance level.

Figure 1 Frequency distribution of strengths for the axis as a whole.
Figure 1

Frequency distribution of strengths for the axis as a whole.

7.2.2 Weaknesses

Weaknesses are aspects that the project suffers from and limit its efficiency or performance. These points may be challenges or problems that the project faces in achieving its goals. It is important to identify the weak points of riverbank roads to detect problems and factors that may increase the likelihood of traffic accidents or make roads less reliable. SWOT analysis weakness point questions, answers, and statistical analysis are shown in Table 12 (Figure 2).

Table 12

SWOT analysis weakness point questions, answers, and statistical analysis

Questions SA A Amb DA SDA AM SD RII Rank Imp.level
1. Do you support the fact that riverbank roads are suffering from noticeable deterioration and erosion? N 20 28 7 3 2 4.02 0.98 0.80 6 H-M
% 33.3 46.7 11.7 5 3.3
2. Do you support a lack of regular maintenance of the paths and asphalt layers along the road? N 15 37 3 4 1 4.03 0.85 0.81 7 H
% 25 61.7 5 6.7 1.7
3. Do you support the lack of warning signs and directional signs along the road? N 25 33 2 0 0 4.38 0.56 0.88 9 H
% 41.7 55 3.3 0 0
4. Do you support that riverbank roads face problems in preparing traffic control plans during maintenance work? N 20 28 6 4 2 4 1.01 0.80 5 H-M
% 33.3 46.7 10 6.7 3.3
5. Do you support the fact that roads extending along the banks of rivers face problems with water drainage and the accumulation of water on the road? N 16 28 8 6 2 3.83 1.04 0.77 3 H-M
% 26.7 46.7 13.3 10 3.3
6. Do you support that relying on traditional methods in implementing and maintaining riverbank roads is common? N 14 30 7 6 3 3.77 1.08 0.75 1 H-M
% 23.3 50 11.7 10 5
7. Do you support that riverbank roads suffer from a lack of adequate lighting along the road? N 17 35 8 0 0 4.15 0.63 0.83 8 H
% 28.3 58.3 13.3 0 0
8. Do you support that roads along river banks suffer from challenges in maintaining soil stability and river sediments? N 13 31 9 5 2 3.8 0.99 0.76 2 H-M
% 21.7 51.7 15 8.3 3.3
9. Do you support that the process of transporting construction materials to the project site faces problems and difficulties, especially in large loads and special loads? N 16 30 7 5 2 3.88 1.01 0.78 4 H-M
% 26.7 50 11.7 8.3 3.3
Total N 156 280 57 33 14 3.98 0.93 0.80 -- H-M
% 28.89 51.85 10.56 6.11 2.59
Figure 2 Frequency distribution of weaknesses for the axis as a whole.
Figure 2

Frequency distribution of weaknesses for the axis as a whole.

7.2.3 Opportunities

Opportunities are a group of external factors or potential events that can occur during project implementation and affect its results. Opportunities can be opportunities for improvement, growth, development, progress, and effective achievement of goals. Therefore, identifying potential opportunities for river bank roads, exploited and transformed into actual benefits, improvements in performance, and desired results. This requires evaluating and analyzing the environment surrounding the project and interacting with opportunities in a strategic and appropriate manner to achieve the project objectives, SWOT analysis of available opportunities, questions, answers, and statistical analysis shown in Table 13 (Figure 3).

Table 13

SWOT analysis available opportunity questions, answers, and statistical analysis

Questions SA A Amb DA SDA AM SD RII Rank Imp. level
1. Do you support the existence of a specific methodology towards benefiting from the investment law and preparing studies for the implementation of strategic and integrated road projects taking advantage of this law? N 21 26 8 4 1 4.03 0.96 0.81 6 H
% 35.0 43.3 13.3 6.7 1.7
2. Do you support the existence of the preparation of studies in coordination with scientific institutions to develop and produce accessories, devices and tools to increase the productivity of the project? N 17 30 6 5 2 3.92 1.01 0.78 8 H-M
% 28.3 50.0 10.0 8.3 3.3
3. Do you support the necessity of using environmentally friendly building materials and green farming techniques to contribute to regulating and draining water and reducing corrosion? N 13 31 7 6 3 3.75 1.07 0.75 10 H-M
% 21.7 51.7 11.7 10.0 5.0
4. Do you support the use of Geographic Information Systems (GIS) and modern sensors to improve and maintain riverbank roads? N 21 33 4 2 0 4.22 0.72 0.84 4 H
% 35.0 55.0 6.7 3.3 0
5. Do you support the use of environmentally friendly alternative means of transportation, such as bicycles, walking, and public transportation, as it is important for reducing traffic congestion and protecting the environment? N 17 31 8 4 0 4.02 0.83 0.80 7 H-M
% 28.3 51.7 13.3 6.7 0
6. Do you support the use of the early warning system to improve quality control of roads by collecting road data and processing it with data analysis algorithms to detect potential risks such as collapses, erosion, or water level changes and informing the concerned authorities about that? N 21 32 7 0 0 4.23 0.65 0.85 3 H
% 35.0 53.3 11.7 0 0
7. Do you support the need to enhance river transport as an effective means of transporting goods and passengers to reduce accidents, traffic, asphalt protection, and environmental pollution reduction? N 22 33 5 0 0 4.28 0.61 0.86 1 H
% 36.7 55.0 8.3 0 0
8. Do you support the necessity of exploiting river bank roads to develop aquatic economic activities such as fishing, aquaculture, and the use of boats? N 20 31 6 3 0 4.13 0.79 0.83 5 H
% 33.3 51.7 10.0 5.0 0
9. Do you support the use of solar panels or wind power generation devices to generate electricity and use it in lighting systems and traffic signals? N 16 29 7 5 3 3.83 1.08 0.77 9 H-M
% 26.7 48.3 11.7 8.3 5.0
10. Do you support the use of light-colored asphalt that reflects sunlight and maintains temperature The road is low, which reduces the energy consumption required to cool the road in hot areas? N 12 29 8 7 4 3.63 1.13 0.73 11 H-M
% 20.0 48.3 13.3 11.7 6.7
11. Do you support strengthening cooperation between the public and private sectors to improve the management of materials and waste in the road sector? N 22 31 7 0 0 4.25 0.65 0.85 2 H
% 36.7 51.7 11.7 0 0
Total N 202 336 73 36 13 4.03 0.82 0.81 -- H
% 30.61 50.91 11.06 5.45 1.97
Figure 3 Frequency distribution of opportunities for the axis as a whole.
Figure 3

Frequency distribution of opportunities for the axis as a whole.

7.2.4 Threats

Threats are considered one of the negative external factors that can affect the achievement of project objectives and cause delay or failure. Threats represent potential problems that may arise during the project’s life cycle and pose a threat to its success. Therefore, identifying potential threats to quality control of riverbank roads and trying to find appropriate solutions helps improve the quality of roads and implement them more effectively and successfully. SWOT analysis potential threat questions, answers, and statistical analysis are shown in Table 14 (Figure 4).

Table 14

SWOT analysis potential threat questions, answers, and statistical analysis

Questions SA A Amb DA SDA AM SD RII Rank Imp. Level
1. Do you support the fact that roads along river banks face frequent problems with floods and torrents? N 20 28 8 3 1 4.05 0.91 0.81 5 H
% 33.3 46.7 13.3 5.0 1.7
2. Do you support that traffic congestion is a major threat to roads? N 25 30 5 0 0 4.33 0.63 0.87 1 H
% 41.7 50.0 8.3 0 0
3. Do you support that traffic accidents are one of the biggest threats facing roads? N 16 34 7 3 0 4.05 0.77 0.81 6 H
% 26.7 56.7 11.7 5.0 0
4. Do you support that climate changes, such as heavy rain, fog, snow, high temperatures, and thunderstorms, pose a threat to riverbank roads? N 23 31 6 0 0 4.28 0.64 0.86 2 H
% 38.3 51.7 10.0 0 0
5. Do you support the fact that heavy load vehicles may cause damage to the asphalt and deform the road infrastructure, which requires For the road, which requires higher repair and maintenance costs? N 17 34 6 2 1 4.07 0.28 0.81 4 H
% 28.3 56.7 10.0 3.3 1.7
6. Do you support a lack of government support for strategic maintenance programs for riverbank roads? N 16 29 8 5 2 3.87 1.02 0.77 7 H-M
% 26.7 48.3 13.3 8.3 3.3
7. Do you support that in some road projects, low-quality materials are used or that there is negligence in quality control during construction operations, which leads to rapid deterioration of the road and increased maintenance costs in the future? N 17 37 6 0 0 4.18 0.60 0.84 3 H
% 28.3 61.7 10.0 0 0
8. Do you support the existence of a defect in senior management’s support for road projects and those working on them? N 18 23 8 7 4 3.73 1.21 0.75 8 H-M
% 30.0 38.3 13.3 11.7 6.7
Total N 152 246 54 20 8 4.07 0.75 0.82 -- H
% 31.67 51.25 11.25 4.17 1.67
Figure 4 Frequency distribution of threats for the axis as a whole.
Figure 4

Frequency distribution of threats for the axis as a whole.

8 Results

8.1 At the theoretical level

The performance evaluation process is considered one of the most important methods of improving performance, as the performance evaluation process is considered necessary by helping it detect errors and deviations in performance, correcting them, and clarifying the extent of achieving goals. SWOT analysis is an important pillar of strategic analysis and the starting point for developing any plan at the level of organizations and even individuals, which is one of the important strategic analysis tools that should not be overlooked or ignored. SWOT analysis contributes to identifying available strengths that can be activated to confront obstacles, exploit opportunities, reduce or control weak points, and confront potential threats.

8.2 At the applied level

Through our study, we reached the following set of results:

  • The study found that Cronbach’s alpha reliability coefficient between 0.908 and 0.956 is greater than the minimum of 0.6 in all aspects of the questionnaire, which indicates the reliability of the study tool. From this, we conclude that the study tool that we prepared is honest and reliable in all its paragraphs.

  • The study also found that the validity factor reached 0.953–0.978, which is a high and appropriate factor. Thus, we can say that all statements of the research tool are valid, which makes us completely confident of their validity in analyzing the results.

  • The findings of the SWOT analysis of the sample members of respondents, which focuses on strengths, weaknesses, opportunities, and threats in the quality control of riverbank roads in Iraq.

    • Strengths: The results of the table indicate an arithmetic mean for the axis as a whole of 3.96, a standard deviation for the axis as a whole of 0.92, and an RII of 0.79 on a five-point Likert scale.

    • Weaknesses: The results of the table indicate an arithmetic mean for the axis as a whole of 3.98, a standard deviation for the axis as a whole of 0.93, and an RII of 0.80 on a five-point Likert scale.

    • Opportunities: The results of the table indicate an arithmetic mean for the axis as a whole of 4.03, a standard deviation for the axis as a whole of 0.82, and an RII of 0.81 on a five-point Likert scale.

    • Threats: The results of the table indicate an arithmetic mean for the axis as a whole of 4.07, a standard deviation for the axis as a whole of 0.75, and an RII of 0.82 on a five-point Likert scale.

  • It is clear from the tables that there are statements that were rated by respondents as having a “High” level of importance. These “High” levels of importance have an RII range ranging between 0.8 < RII ≤ 1.

    • Strengths: These “High” levels of importance have an RII ranging between 0.81 and 0.86, “Are the implementation priorities of road projects determined according to the quality of the soil and the topography of the project lands,” “Do you support the existence of a plan for cooperation with scientific institutions in the field of renewable energy uses,” “Do you support the identification and classification of construction materials and other materials used in riverbank road projects,” “Do you support the existence of a plan for the management of tests, quality control and assurance,” the phrase was classified as “Do you support the use of modern software in development and processing of designs,” which is the most important among all the statements according to the respondents’ opinion with an RII value of 0.86.

    • Weaknesses: These “High” levels of importance have an RII ranging between 0.81 and 0.88, “Do you support a lack of regular maintenance of the paths and asphalt layers along the road,” “Do you support that riverbank roads suffer from a lack of adequate lighting along the road,” the phrase was classified as” Do you support the lack of warning signs and directional signs along the road,” which is the most important among all the statements according to the respondents’ opinion with an RII value of 0.88.

    • Opportunities: These “High” levels of importance have an RII ranging between 0.81 and 0.86, “Do you support the existence of a specific methodology towards benefiting from the investment law and preparing studies for the implementation of strategic and integrated road projects taking advantage of this law,” “Do you support the use of Geographic Information System (GIS) and modern sensors to improve and maintain riverbank roads,” “Do you support the use of the early warning system to improve quality control of roads by collecting road data and processing it with data analysis algorithms to detect potential risks such as collapses, erosion, or water level changes, and informing the concerned authorities about that,” “Do you support the necessity of exploiting river bank roads to develop aquatic economic activities such as fishing, aquaculture, and the use of boats,” “Do you support strengthening cooperation between the public and private sectors to improve the management of materials and waste in the road sector,” the phrase was classified as “Do you support the need to enhance river transport as an effective means of transporting goods and passengers to reduce accidents Traffic, asphalt protection, and environmental pollution reduction,” which is the most important among all the statements according to the respondents’ opinion with an RII value of 0.86.

    • Threats: These “High” levels of importance have an RII ranging between 0.81 and 0.87, “Do you support the fact that roads along river banks face frequent problems with floods and torrents,” “Do you support that traffic accidents are one of the biggest threats facing roads,” “Do you support that climate changes, such as heavy rain, fog, snow, high temperatures, and thunderstorms, pose a threat to riverbank roads,” “Do you support the fact that heavy load vehicles may cause damage to the asphalt and deform the road infrastructure, which requires For the road, which requires higher repair and maintenance costs,” “Do you support that in some road projects low-quality materials are used or that there is a negligence in quality control during construction operations, which leads to rapid deterioration of the road and increased maintenance costs in the future,” the phrase was classified as “Do you support that traffic congestion is a major threat to roads,” which is the most important among all the statements according to the respondents’ opinion with an RII value of 0.87.

9 Conclusions

Quality is not the only source of competitive advantage; social and environmental concerns have become increasingly important due to shifting socioeconomic conditions and acknowledged trends. It is necessary to continuously research and develop the quality control of road implementation on the rim as well as the reinforcement of river edges to prevent road collapses. To ensure that the maintenance is performed as economically as possible, a methodical and cohesive process must be implemented to determine the most efficient form of maintenance and the ideal time to complete the task. From this article, we can conclude the following:

  1. The answers of the sample members varied depending on the questions of the axes, but the majority of the individuals confirmed their agreement with these statements.

  2. The results of the tables above for the four axes show convergence in the values of the arithmetic averages.

  3. We also note that there are no statistically significant differences in the opinions of the sample members about the statements.

  4. The tables also show the decrease in dispersion in the answers and the members of the study sample, which reflects the convergence in the opinions of the study sample members.

  5. Strengths must be preserved, continued to improve, benefited from, and activated in the face of obstacles.

  6. Weak points must be addressed, effective action plans must be developed to overcome them, and procedures must be improved.

  7. Must take advantage of the available opportunities, exploit it, and develop strategies to deal with them effectively.

  8. Emergency response plans must be developed, risk assessed, and staff provided training and education to respond effectively in emergency situations so we will be able to improve the quality of roads and reduce threats.

10 Recommendations

  1. Compare the results with other methods, for example, the Delphi technique.

  2. Applying an SWOT questionnaire to monitor the quality control of riverbank roads in other countries and deal with different local challenges.

  3. Update questionnaires regularly to identify new risks and improve the quality of riverbank roads.

  4. Commitment to environmental and safety specifications, standards, and regulations in the design, construction, and maintenance of riverbank roads and ensuring their application and monitoring on a periodic and continuous basis to ensure the quality of the roads and preserve the environment and safety.

  5. Improving awareness and training for officials, monitors, and workers in this field and providing the necessary support and resources to implement these standards effectively and continuously.

  6. Benefiting from new technologies and modern research in the field of quality control of riverbank roads.

  1. Funding information: Authors declare that the manuscript was done depending on the personal effort of the author, and there is no funding effort from any side or organization.

  2. Conflict of interest: The authors state no conflict of interest.

  3. Data availability statement: Most datasets generated and analyzed in this study are comprised in this submitted manuscript. The other datasets are available on reasonable request from the corresponding author with the attached information.

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Received: 2024-01-22
Revised: 2024-02-28
Accepted: 2024-03-03
Published Online: 2024-04-08

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/eng-2024-0005
Keywords for this article
cost effective; opportunities; pavement; quality control; riverbank roads; socioeconomic situations; SWOT questionnaire; transportation engineering
Creative Commons
BY 4.0

Articles in the same Issue

  1. Regular Articles
  2. Methodology of automated quality management
  3. Influence of vibratory conveyor design parameters on the trough motion and the self-synchronization of inertial vibrators
  4. Application of finite element method in industrial design, example of an electric motorcycle design project
  5. Correlative evaluation of the corrosion resilience and passivation properties of zinc and aluminum alloys in neutral chloride and acid-chloride solutions
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  31. Evaluation of the creep strength of samples produced by fused deposition modeling
  32. A combined feedforward-feedback controller design for nonlinear systems
  33. Effect of adjacent structures on footing settlement for different multi-building arrangements
  34. Analyzing the impact of curved tracks on wheel flange thickness reduction in railway systems
  35. Review Articles
  36. Mechanical and smart properties of cement nanocomposites containing nanomaterials: A brief review
  37. Applications of nanotechnology and nanoproduction techniques
  38. Relationship between indoor environmental quality and guests’ comfort and satisfaction at green hotels: A comprehensive review
  39. Communication
  40. Techniques to mitigate the admission of radon inside buildings
  41. Erratum
  42. Erratum to “Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy”
  43. Special Issue: AESMT-3 - Part II
  44. Integrated fuzzy logic and multicriteria decision model methods for selecting suitable sites for wastewater treatment plant: A case study in the center of Basrah, Iraq
  45. Physical and mechanical response of porous metals composites with nano-natural additives
  46. Special Issue: AESMT-4 - Part II
  47. New recycling method of lubricant oil and the effect on the viscosity and viscous shear as an environmentally friendly
  48. Identify the effect of Fe2O3 nanoparticles on mechanical and microstructural characteristics of aluminum matrix composite produced by powder metallurgy technique
  49. Static behavior of piled raft foundation in clay
  50. Ultra-low-power CMOS ring oscillator with minimum power consumption of 2.9 pW using low-voltage biasing technique
  51. Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
  52. Optimizing the performance of concrete tiles using nano-papyrus and carbon fibers
  53. Special Issue: AESMT-5 - Part II
  54. Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM
  55. The complex of Weyl module in free characteristic in the event of a partition (7,5,3)
  56. Restrained captive domination number
  57. Experimental study of improving hot mix asphalt reinforced with carbon fibers
  58. Asphalt binder modified with recycled tyre rubber
  59. Thermal performance of radiant floor cooling with phase change material for energy-efficient buildings
  60. Surveying the prediction of risks in cryptocurrency investments using recurrent neural networks
  61. A deep reinforcement learning framework to modify LQR for an active vibration control applied to 2D building models
  62. Evaluation of mechanically stabilized earth retaining walls for different soil–structure interaction methods: A review
  63. Assessment of heat transfer in a triangular duct with different configurations of ribs using computational fluid dynamics
  64. Sulfate removal from wastewater by using waste material as an adsorbent
  65. Experimental investigation on strengthening lap joints subjected to bending in glulam timber beams using CFRP sheets
  66. A study of the vibrations of a rotor bearing suspended by a hybrid spring system of shape memory alloys
  67. Stability analysis of Hub dam under rapid drawdown
  68. Developing ANFIS-FMEA model for assessment and prioritization of potential trouble factors in Iraqi building projects
  69. Numerical and experimental comparison study of piled raft foundation
  70. Effect of asphalt modified with waste engine oil on the durability properties of hot asphalt mixtures with reclaimed asphalt pavement
  71. Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network
  72. Numerical study on discharge capacity of piano key side weir with various ratios of the crest length to the width
  73. The optimal allocation of thyristor-controlled series compensators for enhancement HVAC transmission lines Iraqi super grid by using seeker optimization algorithm
  74. Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
  75. Effect of nano-TiO2 on physical and rheological properties of asphalt cement
  76. Performance evolution of novel palm leaf powder used for enhancing hot mix asphalt
  77. Performance analysis, evaluation, and improvement of selected unsignalized intersection using SIDRA software – Case study
  78. Flexural behavior of RC beams externally reinforced with CFRP composites using various strategies
  79. Influence of fiber types on the properties of the artificial cold-bonded lightweight aggregates
  80. Experimental investigation of RC beams strengthened with externally bonded BFRP composites
  81. Generalized RKM methods for solving fifth-order quasi-linear fractional partial differential equation
  82. An experimental and numerical study investigating sediment transport position in the bed of sewer pipes in Karbala
  83. Role of individual component failure in the performance of a 1-out-of-3 cold standby system: A Markov model approach
  84. Implementation for the cases (5, 4) and (5, 4)/(2, 0)
  85. Center group actions and related concepts
  86. Experimental investigation of the effect of horizontal construction joints on the behavior of deep beams
  87. Deletion of a vertex in even sum domination
  88. Deep learning techniques in concrete powder mix designing
  89. Effect of loading type in concrete deep beam with strut reinforcement
  90. Studying the effect of using CFRP warping on strength of husk rice concrete columns
  91. Parametric analysis of the influence of climatic factors on the formation of traditional buildings in the city of Al Najaf
  92. Suitability location for landfill using a fuzzy-GIS model: A case study in Hillah, Iraq
  93. Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
  94. Assessment of indirect tensile stress and tensile–strength ratio and creep compliance in HMA mixes with micro-silica and PMB
  95. Density functional theory to study stopping power of proton in water, lung, bladder, and intestine
  96. A review of single flow, flow boiling, and coating microchannel studies
  97. Effect of GFRP bar length on the flexural behavior of hybrid concrete beams strengthened with NSM bars
  98. Exploring the impact of parameters on flow boiling heat transfer in microchannels and coated microtubes: A comprehensive review
  99. Crumb rubber modification for enhanced rutting resistance in asphalt mixtures
  100. Special Issue: AESMT-6
  101. Design of a new sorting colors system based on PLC, TIA portal, and factory I/O programs
  102. Forecasting empirical formula for suspended sediment load prediction at upstream of Al-Kufa barrage, Kufa City, Iraq
  103. Optimization and characterization of sustainable geopolymer mortars based on palygorskite clay, water glass, and sodium hydroxide
  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
  109. Evaluation of the operational performance of Karbala waste water treatment plant under variable flow using GPS-X model
  110. Design and simulation of photonic crystal fiber for highly sensitive chemical sensing applications
  111. Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery
  112. Inductive 3D numerical modelling of the tibia bone using MRI to examine von Mises stress and overall deformation
  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
  114. Experimental investigation of generating superheated steam using a parabolic dish with a cylindrical cavity receiver: A case study
  115. Effect of surface roughness on the interface behavior of clayey soils
  116. Investigated of the optical properties for SiO2 by using Lorentz model
  117. Measurements of induced vibrations due to steel pipe pile driving in Al-Fao soil: Effect of partial end closure
  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
  119. Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake
  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
  171. Behavior of container berth structure under the influence of environmental and operational loads
  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
  205. Modification of the 5D Lorenz chaotic map with fuzzy numbers for video encryption in cloud computing
  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
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