Search results for: tractor driver vibrations

Authors: Kariman Abdelaziz Ahmed Ali Hamzawy

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Amidst the growing global challenges facing communities, from climate change to educational gaps, sustainable community education has emerged as a vital tool for ensuring comprehensive and enduring development. This research aims to explore effective strategies for sustainable community education that can lead to long-term impacts on local communities. The study begins by defining the concept of sustainable education within a community context and reviews the current literature on the topic. It then presents case studies from various communities around the world where sustainable educational strategies have been successfully implemented. These case studies illustrate how sustainable education can enhance community engagement, build local capacities, and improve quality of life in sustainable ways. The findings from these studies are analyzed to identify the key factors contributing to the success of sustainable educational programs. These factors include partnerships between different sectors (governmental, private, and community), the innovative use of technology, and the adaptation of educational curricula to meet the unique needs of the community. The research also offers practical recommendations on designing and implementing sustainable educational programs, emphasizing the integration of formal and informal education, promoting lifelong learning, and developing local resources. It addresses potential challenges and ways to overcome them to ensure the long-term sustainability of these programs. In conclusion, the research provides a future vision of the role of sustainable education in building resilient and prosperous communities and highlights the importance of investing in education as a key driver of sustainable development. This study contributes to the ongoing discussion on achieving lasting impact through sustainable community education and offers a practical framework for stakeholders to adopt and implement these strategies.

Keywords: sustainable education, community education, Community engagement, local capacity building, educational technology

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Authors: Saila Tykkyläinen

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The purpose of this study is to pave the way for more focused accumulation of knowledge on social enterprise growth. The body of research touching upon the phenomenon is somewhat fragmented. In order to make an effort to create a solid common ground, this study draws from the theoretical starting points and guidelines developed within small firm growth research. By analyzing their use in social enterprise growth literature, the study offers insights on whether the proven theories and concepts from small firm context could be more systematically applied when investigating growth of social enterprises. Towards this end, the main findings from social enterprise growth research are classified under the three research streams on growth. One of them focuses on factors of growth, another investigates growth as a process and the third is interested in outcomes of growth. During the analysis, special attention is paid on exploring how social mission of the company and the pursuit of augmenting its social impact are dealt within those lines of research. The next step is to scrutinize and discuss some of the central building blocks of growth research, namely the unit of analysis, conceptualization of a firm and operationalizing growth, in relation to social enterprise studies. It appears that the social enterprise growth literature stresses the significance of 'social' both as a main driver and principle outcome of growth. As for the growth process, this emphasis is manifested by special interest in strategies and models tailored to disseminate social impact beyond organizational limits. Consequently, this study promotes more frequent use of business activity as a unit of analysis in the social enterprise context. Most of the times, it is their products, services or programs with which social enterprises and entrepreneurs aim to create the impact. Thus the focus should be placed on activities rather than on organizations. The study also seeks to contribute back to the small firm growth research. Even though the recommendation to think of business activities as an option for unit of analysis stems from there, it is all too rarely used. Social entrepreneurship makes a good case for testing and developing the approach further.

Keywords: conceptual study, growth, scaling, social enterprise

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Authors: Sharareh Khodami, Mohammad Seddiq Mortazavi, Seyedeh Laili Mohebbi-Nozar, Fereshteh Saraji, S. Behzadi, Gholam Ali Akbarzadeh, Mitra Naemi

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Water quality is a critical driver of healthy marine ecosystems and a cornerstone of the blue economy, particularly fisheries. The coastal waters of Hormozgan Province, located in the northern Persian Gulf and Gulf of Oman, are increasingly threatened by wastewater discharges from industrial, urban, and agricultural activities. This study evaluates the spatial and temporal patterns of coastal water quality over two decades (2001–2021), drawing on a comprehensive dataset from 200 sampling stations along the province’s shoreline. Key environmental parameters -temperature, dissolved oxygen, salinity, turbidity, chlorophyll-a, nitrate, nitrite, ammonium, and phosphate- were analyzed. Using geographic information systems (GIS), spatial distributions were mapped, and a water quality index (WQI) was derived to classify overall water quality conditions. The WQI values ranged from weak to excellent, reflecting notable spatial variability. The interquartile range (IQR) method was applied to determine acceptable parameter ranges and establish early-warning thresholds for management. Zones were categorized into “caution” and “action” areas, guiding targeted interventions. Results highlight the significant impacts of sustained nutrient loading, particularly from nitrate and phosphate linked to anthropogenic sources, on coastal ecosystem health. These findings underscore the urgent need for stringent nutrient management policies to protect marine ecosystems, ensuring the long-term sustainability of fisheries and other marine resources in this region.

Keywords: coastal area, Hormozgan, Persian Gulf, water quality

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: Fulufhelo Oscar Makananise

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Digital technologies have played a significant role in bridging the information gap between the haves and the have nots in society. In developing countries such as South Africa, historically marginalised groups such as women in rural communities have an opportunity to use digital technologies to network among themselves as well as interact with their government, thereby enhancing prospects for poverty eradication, political participation, community development and democracy. However, the extent to which these goals can be achieved in a developing context through harnessing digital technologies is not quite clear, particularly given the fact that access to these technologies is not evenly distributed and the fact that women’s access to digital technologies is hampered by factors that go beyond the question of infrastructure. Informed by the technological dependency theory, this paper is about how female youth in rural South Africa are deploying digital media tools for socio-economic empowerment. In particular, the study investigated the extent to which female youth in Limpopo province, South Africa access and use digital media platforms and gadgets and the extent to which those technologies are breaking down barriers that stand in the way of female youth empowerment. Data were gathered using a self-administered questionnaire disseminated to selected 100 female youth in Limpopo Province, South Africa. The data were analysed using SPSS version 9, and the results were analysed using descriptive statistics. The paper argues that wider and constant access to digital media by female youth in rural areas is indicative of the great potential for empowering female youth in rural areas through harnessing digital media. The study established that the majority of female youth had access to digital media technologies and used them to share valuable information among themselves. The study further established that female youth are active users of digital media in South Africa, which is the significant driver for socio-economic empowerment.

Keywords: digital technologies, empowerment, female youth, South Africa, survey, technological dependency

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Authors: Rosalina Penaloza, Joanna Navarro, Pauline Jolly, Anna Junkins, Carlos Seas, Larissa Otero

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Background: Tuberculosis (TB) case detection in Peru relies on passive case finding. This strategy relies on the assumption that the community is aware that a persistent cough is a possible symptom of TB and that formal health care needs to be sought. Despite its importance, health knowledge specific to TB is underexplored in Peru. This study aimed to assess health literacy and level of TB knowledge among outpatients attending a referral hospital in Lima, Peru. The goal was to ascertain knowledge gaps in key areas relating to TB, to identify and prioritize subgroups for intervention, and to provide insight for policy and community interventions considering health literacy. Methods: An observational cross-sectional study was conducted using a survey to measure sociodemographic factors, tuberculosis knowledge, and health literacy. Bivariate and Multivariate logistic regression was performed to study the associations between variables and to account for potential confounders. The study was conducted at Hospital Cayetano Heredia in Lima, Peru from June – August 2017. Results: 272 participants were included in the analysis. 57.7% knew someone who had had TB before, 9% had had TB in the past. Two weeks a cough was correctly identified as a symptom that could be TB by 69.1%. High TB knowledge was found among 149 (54.8%) participants. High health literacy was found among 193 (71.0%) participants. Health literacy and TB knowledge were not significantly associated (OR 0.9 (95%CI 0.5-1.5)). After controlling for sex, age, district, education, health insurance, frequency of hospital visits and previous TB diagnosis: High TB knowledge was associated with knowing someone with TB (aOR 2.7 (95%CI 1.6-4.7)) and being a public transport driver, (aOR 0.2 (95%CI 0.05-0.9)). Not being poor was the single factor associated with high health literacy (aOR 3.8 (95%CI 1.6-8.9)). Conclusions: TB knowledge was fair, though 30% did not know the most important symptom of TB. Tailoring educational strategies to risk groups may enhance passive case detection especially amongst transport workers in Lima, Peru.

Keywords: health literacy, Peru, tuberculosis, tuberculosis knowledge

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Authors: Sharda Kumari, Saiman Shetty

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Autonomous trucking is just one of the numerous significant shifts impacting fleet management services. The Society of Automotive Engineers (SAE) has defined six levels of vehicle automation that have been adopted internationally, including by the United States Department of Transportation. On public highways in the United States, organizations are testing driverless vehicles with at least Level 4 automation which indicates that a human is present in the vehicle and can disable automation, which is usually done while the trucks are not engaged in highway driving. However, completely driverless vehicles are presently being tested in the state of California. While autonomous trucking can increase safety, decrease trucking costs, provide solutions to trucker shortages, and improve efficiencies, logistics, too, requires advancements to keep up with trucking innovations. Given that artificial intelligence, machine learning, and automated procedures enable people to do their duties in other sectors with fewer resources, CRM (Customer Relationship Management) can be applied to the autonomous trucking business to provide the same level of efficiency. In a society witnessing significant digital disruptions, fleet management is likewise being transformed by technology. Utilizing strategic alliances to enhance core services is an effective technique for capitalizing on innovations and delivering enhanced services. Utilizing analytics on CRM systems improves cost control of fuel strategy, fleet maintenance, driver behavior, route planning, road safety compliance, and capacity utilization. Integration of autonomous trucks with automated fleet management, yard/terminal management, and customer service is possible, thus having significant power to redraw the lines between the public and private spheres in autonomous trucking logistics.

Keywords: autonomous vehicles, customer relationship management, customer experience, autonomous trucking, digital transformation

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Authors: M. Belén Prendes-Gero, Celestino González-Nicieza, M. Inmaculada Alvarez-Fernández

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Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Keywords: forensic analysis, hypothesis modelling, roof failure, seismic monitoring

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Authors: Felice De Luca, Vincenzo Galdi, Piera Stella, Vito Calderaro, Adriano Campagna, Antonio Piccolo

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Sustainable mobility has become one of the major issues of recent years. The challenge in reducing polluting emissions as much as possible has led to the production and diffusion of vehicles with internal combustion engines that are less polluting and to the adoption of green energy vectors, such as vehicles powered by natural gas or LPG and, more recently, with hybrid and electric ones. While on the one hand, the spread of electric vehicles for private use is becoming a reality, albeit rather slowly, not the same is happening for vehicles used for public transport, especially those that operate in the congested areas of the cities. Even if the first electric buses are increasingly being offered on the market, it remains central to the problem of autonomy for battery fed vehicles with high daily routes and little time available for recharging. In fact, at present, solid-state batteries are still too large in size, heavy, and unable to guarantee the required autonomy. Therefore, in order to maximize the energy management on the vehicle, the optimization of driving profiles offer a faster and cheaper contribution to improve vehicle autonomy. In this paper, following the authors’ precedent works on electric vehicles in public transport and energy management strategies in the electric mobility area, an eco-driving strategy for electric bus is presented and validated. Particularly, the characteristics of the prototype bus are described, and a general-purpose eco-drive methodology is briefly presented. The model is firstly simulated in MATLAB™ and then implemented on a mobile device installed on-board of a prototype bus developed by the authors in a previous research project. The solution implemented furnishes the bus-driver suggestions on the guide style to adopt. The result of the test in a real case will be shown to highlight the effectiveness of the solution proposed in terms of energy saving.

Keywords: eco-drive, electric bus, energy management, prototype

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Authors: Liu Canqi, Zeng Junsheng

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This study identifies two typical bottlenecks that occur when a vehicle cannot change lanes: car following and car stopping. The ideas of traffic field and traffic mass are presented in this work. When there are other vehicles in front of the target vehicle within a particular distance, a force is created that affects the target vehicle's driving speed. The characteristics of the driver and the vehicle collectively determine the traffic mass; the driving speed of the vehicle and external variables have no bearing on this. From a physical level, this study examines the vehicle's bottleneck when following a car, identifies the outside factors that have an impact on how it drives, takes into account that the vehicle will transform kinetic energy into potential energy during deceleration, and builds a calculation model for traffic mass. The energy-time conversion coefficient is created from an economic standpoint utilizing the social average wage level and the average cost of motor fuel. Vissim simulation program measures the vehicle's deceleration distance and delays under the Wiedemann car-following model. The difference between the measured value of deceleration delay acquired by simulation and the theoretical value calculated by the model is compared using the conversion calculation model of traffic mass and deceleration delay. The experimental data demonstrate that the model is reliable since the error rate between the theoretical calculation value of the deceleration delay obtained by the model and the measured value of simulation results is less than 10%. The article's conclusion is that the traffic field has an impact on moving cars on the road and that physical and socioeconomic factors should be taken into account while studying vehicle-following behavior. The deceleration delay value of a vehicle's driving and traffic mass have a socioeconomic relationship that can be utilized to calculate the energy-time conversion coefficient when dealing with the bottleneck of cars stopping and starting.

Keywords: traffic field, social economics, traffic mass, bottleneck, deceleration delay

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Authors: M. Vadivel, R. Ramesh Babu

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Spinel ferrite magnetic nanomaterials have received a great deal of attention in recent years due to their wide range of potential applications in various fields such as magnetic data storage and microwave device applications. Among the family of spinel ferrites, cobalt ferrite (CoFe2O4) has been widely used in the field of high-frequency applications because of its remarkable material qualities such as moderate saturation magnetization, high coercivity, large permeability at higher frequency and high electrical resistivity. For aforementioned applications, the materials should have an improved electrical property, especially enhancement in the dielectric properties. It is well known that the substitution of rare earth metal cations in Fe3+ site of CoFe2O4 nanoparticles leads to structural distortion and thus significantly influences the structural and morphological properties whereas greatly modifies the electrical and magnetic properties of a material. In the present investigation, we report on the influence of lanthanum (La3+) ion substitution on the structural, morphological, dielectric and magnetic properties of CoFe2O4 magnetic nanoparticles prepared by co-precipitation method. Powder X-ray diffraction patterns reveal the formation of inverse cubic spinel structure with the signature of LaFeO3 phase at higher La3+ ion concentrations. Raman and Fourier transform infrared spectral analysis also confirms the formation of inverse cubic spinel structure and Fe-O symmetrical stretching vibrations of CoFe2O4 nanoparticles, respectively. Transmission electron microscopy study reveals that the size of the particles gradually increases with increasing La3+ ion concentrations whereas the agglomeration gets slightly reduced for La3+ ion substituted CoFe2O4 nanoparticles than that of undoped CoFe2O4 nanoparticles. Dielectric properties such as dielectric constant and dielectric loss were recorded as a function of frequency and temperature which reveals that the dielectric constant gradually increases with increasing temperatures as well as La3+ ion concentrations. The increased dielectric constant might be the reason that the formation of LaFeO3 secondary phase at higher La3+ ion concentrations. Magnetic measurement demonstrates that the saturation magnetization gradually decreases from 61.45 to 25.13 emu/g with increasing La3+ ion concentrations which is due to the nonmagnetic nature of La3+ ions substitution.

Keywords: cobalt ferrite, co-precipitation, dielectric properties, saturation magnetization

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Authors: A. Sohouli, A. Suleman

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This study focuses on reliability analysis of variable stiffness composite laminate structures to investigate the potential structural improvement compared to conventional (straight fibers) composite laminate structures. A computational framework was developed which it consists of a deterministic design step and reliability analysis. The optimization part is Discrete Material Optimization (DMO) and the reliability of the structure is computed by Monte Carlo Simulation (MCS) after using Stochastic Response Surface Method (SRSM). The design driver in deterministic optimization is the maximum stiffness, while optimization method concerns certain manufacturing constraints to attain industrial relevance. These manufacturing constraints are the change of orientation between adjacent patches cannot be too large and the maximum number of successive plies of a particular fiber orientation should not be too high. Variable stiffness composites may be manufactured by Automated Fiber Machines (AFP) which provides consistent quality with good production rates. However, laps and gaps are the most important challenges to steer fibers that effect on the performance of the structures. In this study, the optimal curved fiber paths at each layer of composites are designed in the first step by DMO, and then the reliability analysis is applied to investigate the sensitivity of the structure with different standard deviations compared to the straight fiber angle composites. The random variables are material properties and loads on the structures. The results show that the variable stiffness composite laminate structures are much more reliable, even for high standard deviation of material properties, than the conventional composite laminate structures. The reason is that the variable stiffness composite laminates allow tailoring stiffness and provide the possibility of adjusting stress and strain distribution favorably in the structures.

Keywords: material optimization, Monte Carlo simulation, reliability analysis, response surface method, variable stiffness composite structures

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Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 envisages 'smart' manufacturing and services, taking the automation of the 3rd Industrial Revolution to the autonomy of the 4th Industrial Revolution. Powered by innovations in technology and business models, this disruptive transformation is revitalising industry by integrating silos across and beyond value chains. Motivated by the challenges faced by SMEs and Startups in understanding and adopting Industry 4.0, this paper aims to analyse the concept of Growth Poles and evaluate the possibility of its application to Innovation Clusters that strive to propel Industry 4.0 adoption and capacity building. The proposed paper applies qualitative research methodologies including focus groups and survey questionnaires to identify the various factors that affect formation and development of Innovation Clusters. Employing content analysis, the interaction between SMEs and other ecosystem players in such clusters is studied. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position these cluster-based growth poles at the forefront of industrial renaissance. Motivated by this argument, and based on the results of the qualitative research, a roadmap will be proposed to position Innovation Clusters as Growth Poles and effective ecosystems to support Industry 4.0 adoption in a region in the medium to long term. This paper will contribute to the current understanding of the role of Innovation Clusters in capacity building. Relevant management and policy implications stem from the analysis. Furthermore, the findings will be helpful for academicians and policymakers alike, who can leverage an ‘innovation cluster policy’ to enable Industry 4.0 Growth Poles in their regions.

Keywords: digital transformation, fourth industrial revolution, growth poles, industry 4.0, innovation clusters, innovation policy, SMEs and startups

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: J. D. Ho, D. M. Dawes, B. Driver

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Introduction: TASER Conducted Electrical Weapons (CEWs) are the dominant CEWs in use and have been used in modern police and military operations since the late 1990s as a form of non-lethal weaponry. The 3rd generation of CEWs has been recently introduced and is known as The TASER 7. This new CEW will be replacing current CEW technology and has a new dart design that is important for emergency medical professionals to be familiar with because it requires a different method of removal and will leave a different marking pattern in human tissue than they may have been previously familiar with. features of this new dart design include: higher velocity impact, larger impact surface area, break away dart body segment, dual back-barb retention, newly designed removal process. As the TASER 7 begins to be deployed by the police and military personnel, these new features make it imperative that emergency medical professionals become familiar with the signature markings that this new dart design will make on human tissue and how to remove them. Methods: Multiple observational studies using high speed photography were used to record impact patterns of the new dart design on fresh tissue and also the newly recommended dart removal process. Both animal and human subjects were used to test this dart design prior to production release. Results: Data presented will include dart design overview, flight pattern accuracy, impact analysis, and dart removal example. Tissue photographs will be presented to demonstrate examples of signature TASER 7 dart markings that emergency medical professionals can expect to see. Conclusion: This work will provide the reader with an understanding of this newest generation CEW dart design, its key features, its signature marking pattern that can be expected and a recommendation of how to remove it from human tissue.

Keywords: TASER 7, conducted electrical weapon, dart mark, dart removal

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Authors: Mahmoud T. Alwidyan, Ahmad Alrawashdeh, Alaa O. Oteir

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Background: Emergency medical service (EMS) providers, oftentimes, use the lights and sirens (L&S) of their ambulances to warn road users, navigate through traffic, and expedite transport to save lives of ill and injured patients. Despite the contribution of road users in the effectiveness of reducing transport time of EMS ambulances using L&S, there is a lack of empirical assessments exploring the road user’s attitude and behavior in such situations. This study, therefore, aimed to assess the attitude and behavior of road users in response to EMS ambulances with warning L&S in use. Methods: This was a cross-sectional survey developed and distributed to adult road users in Northern Jordan. The questionnaire included 20 items addressing demographics, attitudes, and behavior toward emergency ambulances. We described the participants’ responses and assessed the association between demographics and attitude statements using logistic regression. Results: A total of 1302 questionnaires were complete and appropriate for analysis. The mean age was 34.2 (SD± 11.4) years, and the majority were males (72.6%). About half of road users (47.9%) in our sample would perform inappropriate action in response to EMS ambulances with L&S in use. The multivariate logistic regression model show that being female (OR, 0.63; 95% CI = 0.48-0.81), more educated (OR, 0.68; 95% CI = 0.53-0.86), or public transport driver (OR, 0.55; 95% CI = 0.34-0.90) is significantly associated with inappropriate response to EMS ambulances. Additionally, a significant proportion of road users may perform inappropriate and lawless driving practices such as crossing red traffic lights or following the passing by EMS ambulances, which would, in turn, increase the risk on ambulances and other road users. Conclusions: A large proportion of road users in Jordan may respond inappropriately to the EMS ambulances, and many engage in risky driving behaviors due perhaps to the lack of procedural knowledge. Policy-related interventions and educational programs are crucially needed to increase public awareness of the traffic law concerning EMS ambulances and to enhance appropriate driving behavior, which, in turn, improves the efficiency of ambulance services.

Keywords: EMS ambulances, lights and sirens, road users, attitude and behavior

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Authors: Iman Shabanzadeh

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In terms of its geopolitical position, Iran has been one of the main centers of migration movements in the world in recent decades. However, the policy makers' lack of preparation in completing the cycle of social integration of these immigrants, especially the second and third generation, has caused these people to always be prone to leave the country and immigrate to developed and industrialized countries. In this research, the issue of integration of immigrants in Iran from the perspective of four indicators, "Identity Documents", "Access to Banking Services", "Access to Health and Treatment Services" and "Obtaining a Driver's License" will be analyzed. The research method is descriptive-analytical. To collect information, library and document sources in the field of laws and regulations related to immigrants' rights in Iran, semi-structured interviews with experts have been used. The investigations of this study show that none of the residence documents of immigrants in Iran guarantee the full enjoyment of basic citizenship rights for them. In fact, the function of many of these identity documents, such as the census card, educational support card, etc., is only to prevent crossing the border, and none of them guarantee the basic rights of citizenship. Therefore, for many immigrants, the difference between legality and illegality is only in the risk of crossing the border, and this has led to the spread of the habit of illegal presence for them. Despite this, it seems that there is no clear and coherent policy framework around the issue of foreign immigrants in the country. This policy incoherence can be clearly seen in the diversity and plurality of identity and legal documents of the citizens present in the country and the policy maker's lack of planning to integrate and organize the identity of this huge group. Examining the differences and socioeconomic inequalities between immigrants and the native Iranian population shows that immigrants have been poorly integrated into the structures of Iranian society from an economic and social point of view.

Keywords: immigrants, social integration, citizen services, structural inequality

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Authors: A. Abdulla Khairi Mohamed, Mohamed Gamal Abdelmonem, Gehan Selim

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Walkability in civic and public spaces in Libyan cities is challenging due to the lack of accessibility design, informal merging into car traffic, and the general absence of adequate urban and space planning. The lack of accessible and pedestrian-friendly public spaces in Libyan cities has emerged as a major concern for the government if it is to develop smart and sustainable spaces for the 21st century. A walkable urban space has become a driver for urban development and redistribution of land use to ensure pedestrian and walkable routes between sites of living and workplaces. The characteristics of urban open space in the city centre play a main role in attracting people to walk when attending their daily needs, recreation and daily sports. There is significant gap in the understanding of perceptions, feasibility and capabilities of Libyan urban space to accommodate enhance or support the smart design of a walkable pedestrian-friendly environment that is safe and accessible to everyone. The paper aims to undertake observations of walkability and walkable space in the city of Tripoli as a benchmark for Libyan cities; assess the validity and consistency of the seven principal aspects of smart design, safety, accessibility and 51 factors that affect the walkability in open urban space in Tripoli, through the analysis of 10 local urban spaces experts (town planner, architect, transport engineer and urban designer); and explore user groups’ perceptions of accessibility in walkable spaces in Libyan cities through questionnaires. The study sampled 200 respondents in 2015-16. The results of this study are useful for urban planning, to classify the walkable urban space elements which affect to improve the level of walkability in the Libyan cities and create sustainable and liveable urban spaces.

Keywords: walkability, sustainability, liveability, accessibility

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Authors: Haritha Saranga

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Service quality has become an important driver of competition in manufacturing industries of late, as many products are being sold in conjunction with service offerings. With increase in computational power and data capture capabilities, it has become possible to analyze and estimate various aspects of service quality at the granular level and determine their impact on business performance. In the current study context, dealer level, model-wise warranty data from one of the top two-wheeler manufacturers in India is used to estimate service quality of individual dealers and its impact on warranty related costs and sales performance. We collected primary data on warranty costs, number of complaints, monthly sales, type of quality upgrades, etc. from the two-wheeler automaker. In addition, we gathered secondary data on various regions in India, such as petrol and diesel prices, geographic and climatic conditions of various regions where the dealers are located, to control for customer usage patterns. We analyze this primary and secondary data with the help of a variety of analytics tools such as Auto-Regressive Integrated Moving Average (ARIMA), Seasonal ARIMA and ARIMAX. Study results, after controlling for a variety of factors, such as size, age, region of the dealership, and customer usage pattern, show that service quality does influence sales of the products in a significant manner. A more nuanced analysis reveals the dynamics between product quality and service quality, and how their interaction affects sales performance in the Indian two-wheeler industry context. We also provide various managerial insights using descriptive analytics and build a model that can provide sales projections using a variety of forecasting techniques.

Keywords: service quality, product quality, automobile industry, business analytics, auto-regressive integrated moving average

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Authors: Sanyka Banerjee, Saikat Nandi, P. K. Dan

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Synchronizers as an integral part of gearbox is a key element in the transmission system in automotive. The performance of synchronizer affects transmission efficiency and driving comfort. Synchronizing mechanism as a major component of transmission system must be capable of preventing vibration and noise in the gears. Gear shifting efficiency improvement with an aim to achieve smooth, quick and energy efficient power transmission remains a challenge for the automotive industry. Performance of the synchronizer is dependent on the features and characteristics of its sub-components and therefore analysis of the contribution of such characteristics is necessary. An important exercise involved is to identify all such characteristics or factors which are associated with the modeling and analysis and for this purpose the literature was reviewed, rather extensively, to study the mathematical models, formulated considering such. It has been observed that certain factors are rather common across models; however, there are few factors which have specifically been selected for individual models, as reported. In order to obtain a more realistic model, an attempt here has been made to identify and assimilate practically all possible factors which may be considered in formulating the model more comprehensively. A simulation study, formulated as a block model, for such analysis has been carried out in a reliable environment like MATLAB. Lower synchronization time is desirable and hence, it has been considered here as the output factors in the simulation modeling for evaluating transmission efficiency. An improved synchronizer model requires optimized values of sub-component design parameters. A parametric optimization utilizing Taguchi’s design of experiment based response data and their analysis has been carried out for this purpose. The effectiveness of the optimized parameters for the improved synchronizer performance has been validated by the simulation study of the synchronizer block model with improved parameter values as input parameters for better transmission efficiency and driver comfort.

Keywords: design of experiments, modeling, parametric optimization, simulation, synchronizer

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Authors: Armando Cartenì, Ilaria Henke

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The perceived public transport quality is an important driver that influences both customer satisfaction and mobility choices. The competition among transport operators needs to improve the quality of the services and identify which attributes are perceived as relevant by passengers. Among the “traditional” public transport quality attributes there are, for example: travel and waiting time, regularity of the services, and ticket price. By contrast, there are some “non-conventional” attributes that could significantly influence customer satisfaction jointly with the “traditional” ones. Among these, the beauty/aesthetics of the transport terminals (e.g. rail station and bus terminal) is probably one of the most impacting on user perception. Starting from these considerations, the point stressed in this paper was if (and how munch) the travel experience of the overall travel (e.g. how long is the travel, how many transport modes must be used) influences the perception of the public transport quality. The aim of this paper was to investigate the weight of the terminal quality (e.g. aesthetic, comfort and service offered) within the overall travel experience. The case study was the extra-urban Italian bus network. The passengers of the major Italian terminal bus were interviewed and the analysis of the results shows that about the 75% of the travelers, are available to pay up to 30% more for the ticket price for having a high quality terminal. A travel experience effect was observed: the average perceived transport quality varies with the characteristic of the overall trip. The passengers that have a “long trip” (travel time greater than 2 hours) perceived as “low” the overall quality of the trip even if they pass through a high quality terminal. The opposite occurs for the “short trip” passengers. This means that if a traveler passes through a high quality station, the overall perception of that terminal could be significantly reduced if he is tired from a long trip. This result is important and if confirmed through other case studies, will allow to conclude that the “travel experience impact" must be considered as an explicit design variable for public transport services and planning.

Keywords: transportation planning, sustainable mobility, decision support system, discrete choice model, design problem

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Authors: Saad Roustom, Hajo Ribberink

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In most cities in the world, traffic has increased strongly over the last decades, causing high levels of congestion and deteriorating inner-city air quality. This study analyzes the impact of connected and automated vehicles (CAVs) on traffic performance and greenhouse gas (GHG) emissions under different CAV penetration rates in mixed fleet environments of CAVs and driver-operated vehicles (DOVs) and under three different traffic demand levels. Utilizing meso-scale traffic simulations of the City of Ottawa, Canada, the research evaluates the traffic performance of three distinct CAV driving behaviors—Cautious, Normal, and Aggressive—at penetration rates of 25%, 50%, 75%, and 100%, across three different traffic demand levels. The study employs advanced correlation models to estimate GHG emissions. The results reveal that Aggressive and Normal CAVs generally reduce traffic congestion and GHG emissions, with their benefits being more pronounced at higher penetration rates (50% to 100%) and elevated traffic demand levels. On the other hand, Cautious CAVs exhibit an increase in both traffic congestion and GHG emissions. However, results also show deteriorated traffic flow conditions when introducing 25% penetration rates of any type of CAVs. Aggressive CAVs outperform all other driving at improving traffic flow conditions and reducing GHG emissions. The findings of this study highlight the crucial role CAVs can play in enhancing urban traffic performance and mitigating the adverse impact of transportation on the environment. This research advocates for the adoption of effective CAV-related policies by regulatory bodies to optimize traffic flow and reduce GHG emissions. By providing insights into the impact of CAVs, this study aims to inform strategic decision-making and stimulate the development of sustainable urban mobility solutions.

Keywords: connected and automated vehicles, congestion, GHG emissions, mixed fleet environment, traffic performance, traffic simulations

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: Xinxiu Li, Chuqian Zheng, Yanyan Qian, Hong Fan

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Objectives: In hepatocellular carcinoma (HCC), oncogenes are continuously and robustly transcribed due to aberrant expression of essential components of the trans-acting super-enhancers (SE) complex. Preclinical and clinical trials are now being conducted on small-molecule inhibitors that target core-transcriptional components, including as transcriptional bromodomain protein 4 (BRD4) and cyclin-dependent kinase 7 (CDK7), in a number of malignant tumors. This study aims to explore whether co-overexpression of BRD4 and CDK7 is a potential marker of worse prognosis and a combined therapeutic target in HCC. Methods: The expression pattern of BRD4 and CDK7 and their correlation with prognosis in HCC were analyzed by RNA sequencing data and survival data of HCC patients from TCGA and GEO datasets. The protein levels of BRD4 and CDK7 were determined by immunohistochemistry (IHC), and survival data of patients were analyzed using the Kaplan-Meier method. The mRNA expression levels of genes in HCC cell lines were evaluated by quantitative PCR (q-PCR). CCK-8 and colony formation assays were conducted to assess cell proliferation of HCC upon treatment with BRD4 inhibitor JQ1 or/and CDK7 inhibitor THZ1. Results: It was shown that BRD4 and CDK7 were often overexpressed in HCCs and were associated with poor prognosis of HCC by analyzing the TCGA and GEO datasets. BRD4 or CDK7 overexpression was related to a lower survival rate. It's interesting to note that co-overexpression of CDK7 and BRD4 was a worse prognostic factor in HCC. Treatment with JQ1 or THZ1 alone had an inhibitory effect on cell proliferation; however, when JQ1 and THZ1 were combined, there was a more notable suppression of cell growth. At the same time, the combined use of JQ1 and THZ1 synergistically suppresses the expression of HCC driver genes. Conclusion: Our research revealed that BRD4 and CDK7 coupled can be a useful biomarker in HCC prognosis and the combination of JQ1 and THZ1 can be a promising therapeutic therapy against HCC.

Keywords: BRD4, CDK7, cell proliferation, combined inhibition

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: transportation networks, freight delivery, data flow, monitoring, e-services

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Authors: Michelle V. Tomczak, Reyhaneh Bakhtiari, Aaron Granley, Anthony Singhal

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Objective: Cannabis and cocaine are associated with a range of mental and physical effects that can impair aspects of human behavior. Driving is a complex cognitive behavior that is an essential part of everyday life and can be broken down into many subcomponents, each of which can uniquely impact road safety. With the growing movement of jurisdictions to legalize cannabis, there is an increased focus on impairment and driving. The purpose of this study was to identify driving-related cognitive-performance deficits that are impacted by recreational drug use. Design and Methods: With the assistance of law enforcement agencies, we recruited over 300 participants under the influence of various drugs including cannabis and cocaine. These individuals performed a battery of computer-based tasks scientifically proven to be re-lated to on-road driving performance and designed to test response-speed, memory processes, perceptual-motor skills, and decision making. Data from a control group with healthy non-drug using adults was collected as well. Results: Compared to controls, the drug group showed def-icits in all tasks. The data also showed clear differences between the cannabis and cocaine groups where cannabis users were faster, and performed better on some aspects of the decision-making and perceptual-motor tasks. Memory performance was better in the cocaine group for simple tasks but not more complex tasks. Finally, the participants who consumed both drugs performed most similarly to the cannabis group. Conclusions: Our results show distinct and combined effects of cannabis and cocaine on human performance relating to driving. These dif-ferential effects are likely related to the unique effects of each drug on the human brain and how they distinctly contribute to mental states. Our results have important implications for road safety associated with driver impairment.

Keywords: driving, cognitive impairment, recreational drug use, cannabis and cocaine

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Authors: Apra Sinha

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The inverted U-shaped Environmental Kuznets curve (EKC) demonstrates(pollution-income relationship)that initially the pollution and environmental degradation surpass the level of income per capita; however this trend reverses since at the higher income levels, economic growth initiates environmental upgrading. However, what effect does increased environmental degradation has on growth is the missing feedback link which has not been addressed in the EKC hypothesis. This paper examines the missing feedback link in EKC hypothesis in Indian context by examining the casual association between fossil fuel consumption, carbon dioxide emissions and economic growth for India. Fossil fuel consumption here has been taken as a proxy of driver of economic growth. The casual association between the aforementioned variables has been analyzed using five interventions namely 1) urban development for which urbanization has been taken proxy 2) industrial development for which industrial value added has been taken proxy 3) trade liberalization for which sum of exports and imports as a share of GDP has been taken as proxy 4)financial development for which a)domestic credit to private sector and b)net foreign assets has been taken as proxies. The choice of interventions for this study has been done keeping in view the economic liberalization perspective of India. The main aim of the paper is to investigate the missing feedback link for Environmental Kuznets Curve Hypothesis before and after incorporating the intervening variables. The period of study is from 1971 to 2011 as it covers pre and post liberalization era in India. All the data has been taken from World Bank country level indicators. The Johansen and Juselius cointegration testing methodology and Error Correction based Granger causality have been applied on all the variables. The results clearly show that out of five interventions, only in two interventions the missing feedback link is being addressed. This paper can put forward significant policy implications for environment protection and sustainable development.

Keywords: environmental Kuznets curve hypothesis, fossil fuel consumption, industrialization, trade liberalization, urbanization

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

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Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: connected vehicles, GLOSA, intelligent transport systems, vehicle-to-infrastructure communication

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Authors: Michael Scott Evans, Andrew Smith

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The feeling of fatigue at work could potentially have devastating consequences. The aim of this study was to investigate whether the well-established objective indicator of fatigue – the Fatigue Risk Index (FRI) calculator used by the rail industry is an effective indicator to the number of safety incidents, in which fatigue could have been a contributing factor. The study received ethics approval from Cardiff University’s Ethics Committee (EC.16.06.14.4547). A total of 901 safety incidents were recorded from a single British rail franchise between 1st June 2010 – 31st December 2016, into the Safety Management Information System (SMIS). The safety incident types identified that fatigue could have been a contributing factor were: Signal Passed at Danger (SPAD), Train Protection & Warning System (TPWS) activation, Automatic Warning System (AWS) slow to cancel, failed to call, and station overrun. From the 901 recorded safety incidents, the scheduling system CrewPlan was used to extract the Fatigue Index (FI) score and Risk Index (RI) score of all train drivers on the day of the safety incident. Only the working rosters of 64.2% (N = 578) (550 men and 28 female) ranging in age from 24 – 65 years old (M = 47.13, SD = 7.30) were accessible for analyses. Analysis from all 578 train drivers who were involved in safety incidents revealed that 99.8% (N = 577) of Fatigue Index (FI) scores fell within or below the identified guideline threshold of 45 as well as 97.9% (N = 566) of Risk Index (RI) scores falling below the 1.6 threshold range. Their scores represent good practice within the rail industry. These findings seem to indicate that the current objective indicator, i.e. the FRI calculator used in this study by the British rail franchise was not an effective predictor of train driver’s FI scores and RI scores, as safety incidents in which fatigue could have been a contributing factor represented only 0.2% of FI scores and 2.1% of RI scores. Further research is needed to determine whether there are other contributing factors that could provide a better indication as to why there is such a significantly large proportion of train drivers who are involved in safety incidents, in which fatigue could have been a contributing factor have such low FI and RI scores.

Keywords: fatigue risk index calculator, objective indicator of fatigue, rail industry, safety incident

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Authors: Nazaitul Idya Hamzah, Muhammad Syafiq Mazli, Maszatul Akmar Mustafa

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The peak demand forecast is crucial to identify the future generation plant up needed in the long-term capacity planning analysis for Peninsular Malaysia as well as for the transmission and distribution network planning activities. Currently, peak demand forecast (in Mega Watt) is derived from the generation forecast by using load factor assumption. However, a forecast using this method has underperformed due to the structural changes in the economy, emerging trends and weather uncertainty. The dynamic changes of these drivers will result in many possible outcomes of peak demand for Peninsular Malaysia. This paper will look into the independent model of peak demand forecasting. The model begins with the selection of driver variables to capture long-term growth. This selection and construction of variables, which include econometric, emerging trend and energy variables, will have an impact on the peak forecast. The actual framework begins with the development of system energy and load shape forecast by using the system’s hourly data. The shape forecast represents the system shape assuming all embedded technology and use patterns to continue in the future. This is necessary to identify the movements in the peak hour or changes in the system load factor. The next step would be developing the peak forecast, which involves an iterative process to explore model structures and variables. The final step is combining the system energy, shape, and peak forecasts into the hourly system forecast then modifying it with the forecast adjustments. Forecast adjustments are among other sales forecasts for electric vehicles, solar and other adjustments. The framework will result in an hourly forecast that captures growth, peak usage and new technologies. The advantage of this approach as compared to the current methodology is that the peaks capture new technology impacts that change the load shape.

Keywords: hourly load profile, load forecasting, long term peak demand forecasting, peak demand

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