31 research outputs found

    Impact of Road Pavement Condition on Vehicular Free Flow Speed, Vibration and In-Vehicle Noise

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    Road infrastructure in good condition is a key requirement for efficient transportation systems which leads to economic prosperity and improved quality of life. However, road surface conditions deteriorate over time according to traffic loads and environmental factors. Poor road conditions lead to congestion, accidents, lost productivity, and driver fatigue. This work considers the relationship between road pavement condition and vehicle speed, vibration, and in-vehicle noise. A 7 km section of the Grand Trunk Road, Peshawar, Pakistan divided into 280 segments (140 for each lane), of length 50 m was observed and the Pavement Condition Index (PCI) of each segment was determined based on the recurrent distress type and density according to ASTM D6433-011 guidelines. The number of very good, satisfactory, fair, poor, and very poor conditions are 51, 52, 81, 48, and 42, respectively. The mobile app BotlnckDectr was employed to measure vehicle speed, RPM, noise, vibration, GPS location, and time. Statistical analysis was employed to determine the relationship between PCI and vehicle speed, vibration, and in-vehicle noise. The results obtained indicate that noise and vibration increase by 3.3% and more than 30%, respectively, as the pavement condition changes from good to very poor, and vehicle speed decreases by 8.8%

    Modeling Sustainable Traffic Behavior: Avoiding Congestion at a Stationary Bottleneck

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    Sustainable traffic behaviour is increasing in importance as traffic volume rises due to population growth. In this paper, a model for traffic flow at a stationary bottleneck is developed to determine the parameters that cause congestion. Towards this goal, traffic density, speed, and delay were acquired during peak and off-peak periods in the morning and afternoon at a stationary bottleneck in Peshawar, KPK, Pakistan. The morning and afternoon peak periods have high densities, low speeds, and considerable delays. Regression models are developed using this data. These results indicate that there is a linear relationship between density and time at the stationary bottleneck and a negative linear relationship between density and speed. Thus, an increase in density increases the time delay and reduces the speed. I comprehensive traffic delay model is characterized by a stationary bottleneck. The Kolmogorov-Smirnov (KS) test and P-values were used to identify the best-fit distribution for speed and density. The binomial and generalized extreme values are considered the best fits for density and speed. The results presented can be used to develop accurate simulation models for stationary bottlenecks to reduce congestion. Doi: 10.28991/CEJ-2022-08-11-02 Full Text: PD

    Internet-of-Video Things Based Real-Time Traffic Flow Characterization

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    Real-world traffic flow parameters are fundamental for devising smart mobility solutions. Though numerous solutions (intrusive and non-intrusive sensors) have been proposed, however, these have serious limitations under heterogeneous and congested traffic conditions. To overcome these limitations, a low-cost real-time Internet-of-Video-Things solution has been proposed. The sensor node (fabricated using Raspberry Pi 3B, Pi cameral and power bank) has the capability to stream 2 Mbps MJPEG video of 640x480 resolution and 20 frames per second (fps). The Camlytics traffic analysis software installed on a Dell desktop is employed for traffic flow characterization. The proposed solution was field-tested with vehicle detection rate of 85.3%. The novelty of the proposed system is that in addition to vehicle count, it has the capability to measure speed, density, time headway, time-space diagram and trajectories. Obtained results can be employed for road network planning, designing and management

    Sustainable and Resilient Smart Water Grids: A Solution for Developing Countries

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    According to a United Nations report, the world population will increase from 7 billion to 9 billion by 2050. Further, the water stress level is more than 70% in 22 countries while in another 31 countries it is between 25% and 70%. More than 2 billion people live in these 53 countries which are all underdeveloped. Water use has increased by 1% per year since the 1980s, so global demand is expected to rise by 30% by 2050. Thus, efficient water grid management is imperative to ensure there is sufficient water for the future. Information and Communication Technology (ICT) can be used to create smart water grids to optimize water distribution, reduce waste and leakage, and resolve quality and overuse issues. In this work, a low cost, real-time, reliable and sustainable IoT based solution called SmartTubewell is proposed for smart water grid management. It is composed of two components, a sensor node installed at tube wells and an application layer on Amazon Web Services (AWS) for data analysis, storage and processing. The sensor node is based on a Raspberry Pi with integrated current and voltage sensors and a local database. The sensor data is transmitted to AWS using a cellular (GPRS) network. A comparison between the proposed system and SCADA is presented which shows that SmartTubewell has a much lower cost. A field test with multiple tube wells in Peshawar, Pakistan indicates that this is a suitable solution for developing countries

    Macroscopic Traffic Flow Characterization at Bottlenecks

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    Traffic congestion is a significant issue in urban areas. Realistic traffic flow models are crucial for understanding and mitigating congestion. Congestion occurs at bottlenecks where large changes in density occur. In this paper, a traffic flow model is proposed which characterizes traffic at the egress and ingress to bottlenecks. This model is based on driver response which includes driver reaction and traffic stimuli. Driver reaction is based on time headway and driver behavior which can be classified as sluggish, typical or aggressive. Traffic stimuli are affected by the transition width and changes in the equilibrium velocity distribution. The explicit upwind difference scheme is used to evaluate the Lighthill, Whitham, and Richards (LWR) and proposed models with a continuous injection of traffic into the system. A stability analysis of these models is given and both are evaluated over a road of length 10 km which has a bottleneck. The results obtained show that the behavior with the proposed model is more realistic than with the LWR model. This is because the LWR model cannot adequately characterize driver behavior during changes in traffic flow

    Analysis of chemical constituents in medicinal plants of selected districts of Pakhtoonkhwa, Pakistan

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    Alkaloids, flavonoids and saponins were determined in the Teraxacam officinale, Cichorium intybus and Figonia tritica. Quantative determinations of crude alkaloids, flavonoids and saponins (g kg-1) and their percentages (%) were determined in C. intybus, T. officinale and F. critica collected from Kohat, Mardan, Nowshera and Peshawar regions. Thin layer chromatography (TLC) study of the alkaloids, flavonoids and saponins were carried out with different solvent systems and color of the spot and Rf value of each constituent was determined. Among the samples of C. intybus, relatively higher contents of alkaloids (14 g kg-1) were found in the sample collected from Mardan region, followed by the sample gathered from Nowshera which is equal to 13.8g kg-1. Higher contents of flavonoids were found in C. intybus collected from Kohat region which was 23.48 g kg-1. The other remaining samples of C. intybus ranged in the decreasing order of 19.7, 17.2 and 10.0 g kg-1 for the ones collected from Nowshera, Mardan and Peshawar, respectively. The overall saponin contents remained almost low as compared to the alkaloid and flavonoid contents.Key words: Alkaloids, flavonoids, saponins, TLC study, medicinal plants

    Heavy metals and inorganic constituents in medicinal plants of selected Districts of Khyber Pakhtoonkhwa, Pakistan

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    Heavy metals such as Cr, Fe, Zn, Mn, Ni, Pb, Cu and Cd, and inorganic ions like HCO3-, CO32-, Ca2+, Mg2+, Cl-, Na+, SO42-, NO3-, Fe2+ and F- were investigated in medicinally important plants: Taraxacam officinale, Cichorium intybus and Figonia critica, applying atomic absorption spectrophotometer techniques. In the studied herbs, there were variable amounts of heavy metals and inorganic ions. The purpose of this study was to standardize heavy metals contamination in various indigenous medicinal plants and to create awareness among the public regarding its safe use at collection areas (containing high level of heavy metals) and their adverse health effects.Key words: Medicinal plants, inorganic constituents, heavy metals, atomic absorption spectrophotometer

    Traumatic Subdural Empyema ÔÇô A Rare Neurosurgical Emergency: Case Report and Review of Literature

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    Subdural empyema is a neurosurgical emergency with potentially overwhelming complications. The prognosis is harmfully affected when early diagnosis is not made. Recent advancement in the imaging techniques, especially contrast enhanced CT Scans and MRI Scans, have improved the precision of radiological diagnosis of this condition, along with reduction in the mortality rate. Regardless of this, there may still be an impediment in diag-nosis, partly due to the subtleness of early radiological signs, especially on non-contrast CT Scan. We present a case report which illustrates some of the radiological manifestations, complications, potential pitfalls in diagnosis and treatment of traumatic subdural empyema.Conclusion: Patient of severe head injury not improving with pharmacotherapy should get a repeat C.T Scan vault to look for delayed hematomas or empyema. Urgent diagnosis and prompt evacuation along with proper anti-biotic therapy can improve the survival of patient having traumatic subdural empyema
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