Search results for: Mais Haj Qasem
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22

Search results for: Mais Haj Qasem

22 The Successful Implementation of Management Accounting Innovations (MAIs) within Jordanian Industrial Sector Using Cross-Case Analysis

Authors: Mahmoud Nassar

Abstract:

This paper was designed for interviews with companies that had implemented Management Accounting Innovations (MAIs) within Jordanian Industrial Sector in full. Each company in this paper was examined as an entity to obtain an understanding of the process of MAIs adoption and implementation as well as the respondents’ opinions and perspectives of each individual company as to what are considered to be the important factors in the company. By firstly using within-case analysis has the potential to aid in-depth views of the issues and their impact on each particular company. Then, cross-case analysis was used to analyse the similarities and differences of the six companies. The study concludes that, the six companies interviewed gradually moved to using MAIs over the last ten years. The length of time required to implement the MAIs varied across the companies. Interviewees revealed several factors from both the demand and supply side that influence implementation of MAIs within the Jordanian industrial companies. Respondents mentioned and emphasised the important effect of the following factors: top management support, education about ABC concept and benefits, training programmes, shortcoming of existing cost system, competition, size of company, professional accounting bodies, management accounting journals, management accounting research and PhD degrees, and cooperation between universities and companies.

Keywords: industrial sector, innovations, Jordan, management accounting

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21 Data Mining Approach for Commercial Data Classification and Migration in Hybrid Storage Systems

Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

Abstract:

Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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20 Auditory and Language Skills Development after Cochlear Implantation in Children with Multiple Disabilities

Authors: Tamer Mesallam, Medhat Yousef, Ayna Almasaad

Abstract:

BACKGROUND: Cochlear implantation (CI) in children with additional disabilities can be a fundamental and supportive intervention. Although, there may be some positive impacts of CI on children with multiple disabilities such as better outcomes of communication skills, development, and quality of life, the families of those children complain from the post-implant habilitation efforts that considered as a burden. OBJECTIVE: To investigate the outcomes of CI children with different co-disabilities through using the Meaningful Auditory Integration Scale (MAIS) and the Meaningful Use of Speech Scale (MUSS) as outcome measurement tools. METHODS: The study sample comprised 25 hearing-impaired children with co-disability who received cochlear implantation. Age and gender-matched control group of 25 cochlear-implanted children without any other disability has been also included. The participants' auditory skills and speech outcomes were assessed using MAIS and MUSS tests. RESULTS: There was a statistically significant difference in the different outcomes measure between the two groups. However, the outcomes of some multiple disabilities subgroups were comparable to the control group. Around 40% of the participants with co-disabilities experienced advancement in their methods of communication from behavior to oral mode. CONCLUSION: Cochlear-implanted children with multiple disabilities showed variable degrees of auditory and speech outcomes. The degree of benefits depends on the type of the co-disability. Long-term follow-up is recommended for those children.

Keywords: children with disabilities, Cochlear implants, hearing impairment, language development

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19 Effect of Transmission Distance on the Performance of Hybrid Configuration Using Non Return to Zero (NRZ) Pulse Format

Authors: Mais Wa'ad

Abstract:

The effect of transmission distance on the performance of hybrid configuration H 10-40 Gb/s with Non-Return to Zero (NRZ) pulse format, 100 GHz channel spacing, and Multiplexer/De-Multiplexer Band width (MUX/DEMUX BW) of 60 GHz has been investigated in this study. The laser Continuous Wave (CW) power launched into the modulator is set to 4 dBm. Eight neighboring DWDM channels are selected around 1550.12 nm carrying different data rates in hybrid optical communication systems travel through the same optical fiber and use the same passive and active optical modules. The simulation has been done using Optiwave Inc Optisys software. Usually, increasing distance will lead to decrease in performance; however this is not always the case, as the simulation conducted in this work, shows different system performance for each channel. This is due to differences in interaction between dispersion and non-linearity, and the differences in residual dispersion for each channel.

Keywords: dispersion and non-linearity interaction, optical hybrid configuration, multiplexer/de multiplexer bandwidth, non-return to zero, optical transmission distance, optisys

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18 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems

Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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17 A Predictive Machine Learning Model of the Survival of Female-led and Co-Led Small and Medium Enterprises in the UK

Authors: Mais Khader, Xingjie Wei

Abstract:

This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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16 UPPAAL-based Design and Analysis of Intelligent Parking System

Authors: Abobaker Mohammed Qasem Farhan, Olof M. A. Saif

Abstract:

The demand for parking spaces in urban areas, particularly in developing countries, has led to a significant issue in the absence of sufficient parking spaces in crowded areas, which results in daily traffic congestion as drivers search for parking. This not only affects the appearance of the city but also has indirect impacts on the economy, society, and environment. In response to these challenges, researchers from various countries have sought technical and intelligent solutions to mitigate the problem through the development of smart parking systems. This paper aims to analyze and design three models of parking lots, with a focus on parking time and security. The study used computer software and Uppaal tools to simulate the models and determine the best among them. The results and suggestions provided in the paper aim to reduce the parking problems and improve the overall efficiency and safety of the parking process. The conclusion of the study highlights the importance of utilizing advanced technology to address the pressing issue of insufficient parking spaces in urban areas.

Keywords: preliminaries, system requirements, timed Au- tomata, Uppaal

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15 Safe Routes to Schools (SRTS): Children’ Safety Improvement Under COVID-19 Pandemic Conditions in Jordan

Authors: Khair Jadaan, Qasem Alqasem

Abstract:

School children are vulnerable road user groups and are particularly at high risk calling for the need to improve their safety. Safe Routes to Schools (SRTS) concept is considered as one safety improvement approach that would effectively help improve school children’s safety. This paper aims to determine the best practice SRTS for Jordan based on the international experience attained through extensive and selected literature review falling under the 5 E’s and additionally on information/data collected through a survey performed using an online predesigned questionnaire to investigate the reactions and attitudes of students and their parents towards the proposed SRTS program. Data are analyzed using SPSS and MS software, especially Excel, in addition to some literature reviews inserted in this study. The results represent some recommendations that are strongly believed to help decision makers to develop the current safety conditions of the school routes. The challenges that the implementation of this program would face including COVID-19 protection for teachers and students are addressed.

Keywords: children, COVID-19, Jordan, safety, school, SRTS, 5 E’s

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14 Comparison of Student Grades in Dual-Enrollment Courses Taken Inside and Outside of Texas High Schools

Authors: Cynthia A. Gallardo, Kelly S. Hall, Kristopher Garza, Linda Challoo, Mais Nijim

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Dual-enrollment programs have become more prevalent in college and high school settings. Also known as early college programs, dual-enrollment programs help students acquire a head start in earning college credit for post-secondary studies. The number and percentage of high school students who take college courses while in high school is growing. However, little is known about how dual-enrolled students fare. The classroom environment is important to learning. This study compares dually enrolled high school students who take courses that yield college credit either within their high school or at some other location. Mann-Whitney U was the statistical test used. Mean proportions were compared for each of the five standard letter grades earned across the state of Texas. Results indicated that students earn similar passing A, B, and C grades when they take dual-enrollment courses at their high school location but are more likely to fail if they take dual-enrollment courses at non-high school locations. Implications of results are that student success rate of dual-enrollment college courses may have a significant difference between the locations and student performance.

Keywords: educational leadership, dual-enrollment, student performance, college

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13 Accounting Legislation, Corporate Governance Codes and Disclosure in Jordan

Authors: Ayman Haddad, Wafaa Sbeiti, Amr Qasem

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The main aim of this paper is to provide an overview of the most influential economic changes and accounting legislation affecting financial reporting and disclosure practices in Jordan. It also provides an overview of disclosure studies conducted in Jordan covering the year(s) between 1986 and 2014. The economic changes in Jordan required conducting economic reform and revising/issuing new regulations and financial market reforms that led to an improvement in disclosure practices. The issuance of Temporary Securities Law and its Directives of Disclosure in 1997, which came into effect in 1998, is considered as the turning point in the improvement of disclosure practice in Jordan. Based on a review of prior disclosure studies, we conclude that disclosure practices have improved overtime. We also observe that that firm size as a factor has always affected the level of disclosure in Jordan and followed by external auditing while liquidity was found to have the least effect. The paper also addresses the disclosure items required in Corporate Governance Codes that exist for listed shareholding companies, banks, and insurance companies. Finally, the paper discusses the quality of accounting education in Jordan since prior studies noted its impact on accounting practice.

Keywords: accounting legislation, corporate governance, disclosure practice, Jordan

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12 Sensing Characteristics of Gold Nanoparticles Decorated Sputtered Tin Oxide Thin Films as Nitrogen Oxide Sensor

Authors: Qasem Drmosh, Zain Yamai, Amar Mohamedkhair, Abdulmajid Hendi

Abstract:

In recent years, there has been a growing interest in the reduction of the nitrogen oxides NOx (NO2, NO) gases resulting from automotive or combustion emissions. Recently, metal additives in nanometer dimension onto the surface of SnO2 nanorods, nanowires and nanotubes sensitizer to further increase the sensor response have been used. In contrast, there is a lack study focused on modifying the surface of SnO2 thin films by nanoparticles. The challenge in case of thin films is how to fabricate these nanoparticles on the surfaces in cost-effective method, high purity as well as without hampering electrical and topographical properties. Here in this report, a simple and facile strategy has been demonstrated to acquire high sensitive and fast response NO2 gas sensor. Structural, electrical, morphological, optical, and compositional properties of the fabricated sensors were investigated through different analytical technique including X-ray diffraction (XRD), Field emission scanning emission microscope (FESEM) and X-ray photoelectron spectroscopy (XPS). The sensing performance of the prepared sensors are studied at different temperatures for various concentrations of NO2 and compared with pristine SnO2 film.

Keywords: NO2 sensor, SnO2, sputtering, thin films

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11 Recent Advances of Photo-Detectors in Single Photon Emission Computed Tomography Imaging System

Authors: Qasem A. Alyazji

Abstract:

One of the main techniques for Positron emission tomography (PET), Single photon emission computed tomography (SPECT) is the development of radiation detectors. The NaI(Tl) scintillator crystal coupled to an array of photomultiplier tubes known as the Anger camera, is the most dominant detectors system in PET and SPECT devices. Technological advances in many materials, in addition to the emerging importance of specialized applications such as preclinical imaging and cardiac imaging, have encouraged innovation so that alternatives to the anger camera are now part in alternative imaging systems. In this paper we will discuss the main performance characteristics of detectors devices and scanning developments in both scintillation detectors, semiconductor (solid state) detectors, and Photon Transducers such as photomultiplier tubes (PMTs), position sensitive photomultiplier tubes (PSPMTs), Avalanche photodiodes (APDs) and Silicon photomultiplier (SiPMT). This paper discussed the detectors that showed promising results. This study is a review of recent developments in the detectors used in single photon emission computed tomography (SPECT) imaging system.

Keywords: SPECT, scintillation, PMTs, SiPMT, PSPMTs, APDs, semiconductor (solid state)

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10 Monitoring Blood Pressure Using Regression Techniques

Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

Abstract:

Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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9 Equality and Non-Discrimination in Israel: The Use of Land

Authors: Mais Qandeel

Abstract:

Within the Jewish and democratic Israeli state, as dually characterized, the treatment of citizens differs according to their religious groups and nationalities. The laws and policies against Arab citizens concerning ownership and use of land are the main focus of this article. As the Jewish character has led to Jewish based legal provisions which give the privilege to Jews, first, this article examines the legal bases which distinguish between citizens in Israel based on their religion. It examines the major Israeli laws which are used to confiscate, manage, and lease properties. Second, the article demonstrates the de facto practices against Arab citizens in using lands. Most of the Palestinian land was confiscated and turned over to Jewish owners or to state land, Palestinian citizens are distinguished in using the state administered lands. They are also restricted in using full ownership rights and denied using plots of lands and housing units. Such policies have created, within the same state, a class of secondary citizens who are categorized as non-Jews. Last, within the Basic Law: Human Dignity and Freedom which has served as the constitutional bill of rights for Israelis and also the International law, particularly the International Convention on the Elimination of All Forms of Racial Discrimination, it will be concluded whether these restricted policies against Arab citizens in using land constitute a religion-based-discrimination among Israeli citizens and create a situation of separation and inequality between two groups of people in Israel.

Keywords: Israel, citizens, discrimination, equality

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8 Modeling the Performance of Natural Sand-Bentonite Barriers after Infiltration with Polar and Non-Polar Hydrocarbon Leachates

Authors: Altayeb Qasem, Mousa Bani Baker, Amani Nawafleh

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The complexity of the sand-bentonite liner barrier system calls for an adequate model that reflects the conditions depending on the barrier materials and the characteristics of the permeates which lead to hydraulic conductivity changes when liners infiltrated with polar, no-polar, miscible and immiscible liquids. This paper is dedicated to developing a model for evaluating the hydraulic conductivity in the form of a simple indicator for the compatibility of the liner versus leachate. Based on two liner compositions (95% sand: 5% bentonite; and 90% sand: 10% bentonite), two pressures (40 kPa and 100 kPa), and three leachates: water, ethanol and biofuel. Two characteristics of the leacahtes were used: viscosity of permeate and its octanol-water partitioning coefficient (Kow). Three characteristics of the liners mixtures were evaluated which had impact on the hydraulic conductivity of the liner system: the initial content of bentonite (%), the free swelling index, and the shrinkage limit of the initial liner’s mixture. Engineers can use this modest tool to predict a potential liner failure in sand-bentonite barriers.

Keywords: liner performance, sand-bentonite barriers, viscosity, free swelling index, shrinkage limit, octanol-water partitioning coefficient, hydraulic conductivity, theoretical modeling

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7 The Use of Continuous Improvement Methods to Empower the Osh MS With Leading Key Performance Indicators

Authors: Maha Rashid Al-Azib, Almuzn Qasem Alqathradi, Amal Munir Alshahrani, Bilqis Mohammed Assiri, Ali Almuflih

Abstract:

The Occupational Safety and Health Management System in one of the largest Saudi companies has been experiencing in the last 10 years extensive direct and indirect expenses due to lack of proactive leading indicators and safety leadership effective procedures. And since there are no studies that are associated with this department of safety in the company, this research has been conducted. In this study we used a mixed method approach containing a literature review and experts input, then a qualitative questionnaire provided by Institute for Work and Health related to determining the company’s occupational safety and health management system level out from three levels (Compliance - Improvement - Continuous Learning) and the output regarding the company’s level was in Continuous Learning. After that Deming cycle was employed to create a set of proactive leading indicators and analyzed using the SMART method to make sure of its effectiveness and suitability to the company. The objective of this research is to provide a set of proactive indicators to contribute in making an efficient occupational safety and health management system that has less accidents which results in less expenses. Therefore, we provided the company with a prototype of an APP, designed and empowered with our final results to contribute in supporting decisions making processes.

Keywords: proactive leading indicators, OSH MS, safety leadership, accidents reduction

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6 A Supervised Learning Data Mining Approach for Object Recognition and Classification in High Resolution Satellite Data

Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

Abstract:

Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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5 Automatic Classification of Lung Diseases from CT Images

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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4 Developing a Sustainable Business Model for Platform-Based Applications in Small and Medium-Sized Enterprise Sawmills: A Systematic Approach

Authors: Franziska Mais, Till Gramberg

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The paper presents the development of a sustainable business model for a platform-based application tailored for sawing companies in small and medium-sized enterprises (SMEs). The focus is on the integration of sustainability principles into the design of the business model to ensure a technologically advanced, legally sound, and economically efficient solution. Easy2IoT is a research project that aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements, and potential solutions for smart services are derived. The structuring of the business ecosystem within the application plays a central role, whereby the roles of the partners, the management of the IT infrastructure and services, as well as the design of a sustainable operator model are considered. The business model is developed using the value proposition canvas, whereby a detailed analysis of the requirements for the business model is carried out, taking sustainability into account. This includes coordination with the business model patterns, according to Gassmann, and integration into a business model canvas for the Easy2IoT product. Potential obstacles and problems are identified and evaluated in order to formulate a comprehensive and sustainable business model. In addition, sustainable payment models and distribution channels are developed. In summary, the article offers a well-founded insight into the systematic development of a sustainable business model for platform-based applications in SME sawmills, with a particular focus on the synergy of ecological responsibility and economic efficiency.

Keywords: business model, sustainable business model, IIoT, IIoT-platform, industrie 4.0, big data

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3 Dynamics Pattern of Land Use and Land Cover Change and Its Driving Factors Based on a Cellular Automata Markov Model: A Case Study at Ibb Governorate, Yemen

Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

Abstract:

Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

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2 An Exploratory Study on the Impact of Climate Change on Design Rainfalls in the State of Qatar

Authors: Abdullah Al Mamoon, Niels E. Joergensen, Ataur Rahman, Hassan Qasem

Abstract:

Intergovernmental Panel for Climate Change (IPCC) in its fourth Assessment Report AR4 predicts a more extreme climate towards the end of the century, which is likely to impact the design of engineering infrastructure projects with a long design life. A recent study in 2013 developed new design rainfall for Qatar, which provides an improved design basis of drainage infrastructure for the State of Qatar under the current climate. The current design standards in Qatar do not consider increased rainfall intensity caused by climate change. The focus of this paper is to update recently developed design rainfalls in Qatar under the changing climatic conditions based on IPCC's AR4 allowing a later revision to the proposed design standards, relevant for projects with a longer design life. The future climate has been investigated based on the climate models released by IPCC’s AR4 and A2 story line of emission scenarios (SRES) using a stationary approach. Annual maximum series (AMS) of predicted 24 hours rainfall data for both wet (NCAR-CCSM) scenario and dry (CSIRO-MK3.5) scenario for the Qatari grid points in the climate models have been extracted for three periods, current climate 2010-2039, medium term climate (2040-2069) and end of century climate (2070-2099). A homogeneous region of the Qatari grid points has been formed and L-Moments based regional frequency approach is adopted to derive design rainfalls. The results indicate no significant changes in the design rainfall on the short term 2040-2069, but significant changes are expected towards the end of the century (2070-2099). New design rainfalls have been developed taking into account climate change for 2070-2099 scenario and by averaging results from the two scenarios. IPCC’s AR4 predicts that the rainfall intensity for a 5-year return period rain with duration of 1 to 2 hours will increase by 11% in 2070-2099 compared to current climate. Similarly, the rainfall intensity for more extreme rainfall, with a return period of 100 years and duration of 1 to 2 hours will increase by 71% in 2070-2099 compared to current climate. Infrastructure with a design life exceeding 60 years should add safety factors taking the predicted effects from climate change into due consideration.

Keywords: climate change, design rainfalls, IDF, Qatar

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1 Crash and Injury Characteristics of Riders in Motorcycle-Passenger Vehicle Crashes

Authors: Z. A. Ahmad Noor Syukri, A. J. Nawal Aswan, S. V. Wong

Abstract:

The motorcycle has become one of the most common type of vehicles used on the road, particularly in the Asia region, including Malaysia, due to its size-convenience and affordable price. This study focuses only on crashes involving motorcycles with passenger cars consisting 43 real world crashes obtained from in-depth crash investigation process from June 2016 till July 2017. The study collected and analyzed vehicle and site parameters obtained during crash investigation and injury information acquired from the patient-treating hospital. The investigation team, consisting of two personnel, is stationed at the Emergency Department of the treatment facility, and was dispatched to the crash scene once receiving notification of the related crashes. The injury information retrieved was coded according to the level of severity using the Abbreviated Injury Scale (AIS) and classified into different body regions. The data revealed that weekend crashes were significantly higher for the night time period and the crash occurrence was the highest during morning hours (commuting to work period) for weekdays. Bad weather conditions play a minimal effect towards the occurrence of motorcycle – passenger vehicle crashes and nearly 90% involved motorcycles with single riders. Riders up to 25 years old are heavily involved in crashes with passenger vehicles (60%), followed by 26-55 year age group with 35%. Male riders were dominant in each of the age segments. The majority of the crashes involved side impacts, followed by rear impacts and cars outnumbered the rest of the passenger vehicle types in terms of crash involvement with motorcycles. The investigation data also revealed that passenger vehicles were the most at-fault counterpart (62%) when involved in crashes with motorcycles and most of the crashes involved situations whereby both of the vehicles are travelling in the same direction and one of the vehicles is in a turning maneuver. More than 80% of the involved motorcycle riders had sustained yellow severity level during triage process. The study also found that nearly 30% of the riders sustained injuries to the lower extremities, while MAIS level 3 injuries were recorded for all body regions except for thorax region. The result showed that crashes in which the motorcycles were found to be at fault were more likely to occur during night and raining conditions. These types of crashes were also found to be more likely to involve other types of passenger vehicles rather than cars and possess higher likelihood in resulting higher ISS (>6) value to the involved rider. To reduce motorcycle fatalities, it first has to understand the characteristics concerned and focus may be given on crashes involving passenger vehicles as the most dominant crash partner on Malaysian roads.

Keywords: motorcycle crash, passenger vehicle, in-depth crash investigation, injury mechanism

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