Stream Patterns Research Articles

A Comparative Investigation of Infiltration and Channel Roughness of Ephemeral and Perennial Streams in a Mountainous Catchment

ABSTRACTInfiltration and channel roughness, two major factors that govern stream discharge, were studied in similar‐sized ephemeral and perennial streams in a mountainous tropical catchment. Seasons were defined based on two ephemeral flow conditions, i.e., with (wet season) and without (dry season) surface flow. A stream was divided transversely into low‐flow areas (close to the thalweg) and high‐flow areas (close to the channel margin). The highest average infiltration (~50 mm/h) was observed in the low flow areas around the thalweg of ephemeral streams in the dry season and was significantly higher than for any other spatial scale or temporal period. The infiltration in high‐flow areas did not show a statistically significant difference between the two stream types, and surprisingly, perennial streams in the dry season showed higher infiltration than ephemeral streams. Since sediment moisture and organic content showed negative and positive correlations with infiltration, respectively, for both stream types and ephemeral streams showed statistically significant negative correlations between litter and infiltration during the dry season, the low infiltration in ephemeral high flow areas was attributed to stream‐type dependent litter processing. The litter of ephemeral stream high‐flow areas was subject to partial decomposition due to rapid drying and had residue of previously buried litter. Ephemeral channels were two to three times rougher than perennial channels. Standing crop biomass and mean particle size increased stream roughness in both stream types but were less prominent in ephemeral streams due to the presence of litter. The study demonstrated that litter has a special role in defining the infiltration pattern, channel roughness, and flood control potential of ephemeral streams.

Redefining Event Detection and Information Dissemination: Lessons from X (Twitter) Data Streams and Beyond

X (formerly known as Twitter), Reddit, and other social media forums have dramatically changed the way society interacts with live events in this day and age. The huge amount of data generated by these platforms presents challenges, especially in terms of processing speed and the complexity of finding meaningful patterns and events. These data streams are generated in multiple formats, with constant updating, and are real-time in nature; thus, they require sophisticated algorithms capable of dynamic event detection in this dynamic environment. Event detection techniques have recently achieved substantial development, but most research carried out so far evaluates only single methods, not comparing the overall performance of these methods across multiple platforms and types of data. With that view, this paper represents a deep investigation of complex state-of-the-art event detection algorithms specifically customized for streams of data from X. We review various current techniques based on a thorough comparative performance test and point to problems inherently related to the detection of patterns in high-velocity streams with noise. We introduce some novelty to this research area, supported by appropriate robust experimental frameworks, to performed comparisons quantitatively and qualitatively. We provide insight into how those algorithms perform under varying conditions by defining a set of clear, measurable metrics. Our findings contribute new knowledge that will help inform future research into the improvement of event detection systems for dynamic data streams and enhance their capabilities for real-time and actionable insights. This paper will go a step further than the present knowledge of event detection and discuss how algorithms can be adapted and refined in view of the emerging demands imposed by data streams.

Detection and treatment of string events in the limit

A string event is a pattern that occurs in a stream of characters. The need to detect and handle string events in infinite texts emerges in many scenarios, including online treatment of logs, web crawling, and syntax highlighting. This paper describes a technique to specify and treat string events. Users determine patterns of interest via a markup language. From such examples, tokens are generalized via a semi-lattice of regular expressions. Such tokens are combined into a context-free language that recognizes patterns in the text stream. These techniques are implemented in a text processing system called Lushu, which runs on the Java Virtual Machine (JVM). Lushu intercepts strings emitted by the JVM. Once patterns are detected, it invokes a user-specified action handler. As a proof of concept, this paper shows that Lushu outperforms state-of-the-art parsers and parser generators, such as Comby, BeautifulSoup4 and ZheFuscator, in terms of memory consumption and running time.

Integrated Morphometric and Hypsometric Analysis of Niragantipalli Micro Watershed Using Remote Sensing and Geographical Information System Techniques

Employing Remote sensing (RS) and geographic information system (GIS) for the morphometric parameters analysis are discovered to be tremendous usefulness in the prioritization of watersheds for soil, water conservation and natural resource management at micro watershed level. The analysis of morphometric parameters plays a crucial role for understanding and managing watersheds. In current study an, attempt was to determine the morphological parameters of Niragantipalli micro-watershed in Chikkaballapura District of Karnataka, India. For detail study, Google earth pro, GPS visualizer conversion toll and Arc GIS were used for preparation of DEM and delineation of the watershed boundary. GIS was used for evaluation of basic, linear, areal and relief aspects of morphometric parameters. The Niragantipalli micro-watershed occupies an area of 632 ha with third order stream (truck order) and dendritic drainage pattern. The mean bifurcation ratio of the micro-watershed is 2.5 it suggests that the drainage system formed on homogeneous rock when the influences of geologic structures on the network of streams were negligible and generate sharp peak flow. With a drainage density of 1.31 km/km2, the drainage network is extremely coarse. The watershed is elongated, as shown by the form factor of 0.27 and elongation ratio of 0.58. The results from the morphometric analysis of the watershed are very beneficial for developing and designing conservation structures of soil and watershed management measures. The hypsometric curves’ structure as well as estimated hypsometric integral results reflects the Niragantipalli Micro Watershed erosional stages. As a result, the study concludes that morphometric and hypsometric analysis findings may be useful to stakeholders participating in catchment development and management projects.

A Survey on Data-Driven Approaches for Reliability, Robustness, and Energy Efficiency in Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are pivotal in health care and wearable technologies, enabling seamless communication between miniature sensors and devices on or within the human body. These biosensors capture critical physiological parameters, ranging from body temperature and blood oxygen levels to real-time electrocardiogram readings. However, WBANs face significant challenges during and after deployment, including energy conservation, security, reliability, and failure vulnerability. Sensor nodes, which are often battery-operated, expend considerable energy during sensing and transmission due to inherent spatiotemporal patterns in biomedical data streams. This paper provides a comprehensive survey of data-driven approaches that address these challenges, focusing on device placement and routing, sampling rate calibration, and the application of machine learning (ML) and statistical learning techniques to enhance network performance. Additionally, we validate three existing models (statistical, ML, and coding-based models) using two real datasets, namely the MIMIC clinical database and biomarkers collected from six subjects with a prototype biosensing device developed by our team. Our findings offer insights into strategies for optimizing energy efficiency while ensuring security and reliability in WBANs. We conclude by outlining future directions to leverage approaches to meet the evolving demands of healthcare applications.

Changes in the Gulf Stream path over the last 3 decades

Abstract. The Gulf Stream transports warm waters from low to high latitudes in the North Atlantic Ocean, impacting Europe's climate. This study investigates the changing pattern of the Gulf Stream over the last 3 decades as observed in the altimetric record (1993–2022) using monthly averaged altimetry maps together with the outputs from an ocean reanalysis product. The seasonal and yearly evolution of the coordinates (destabilization point) where the Gulf Stream starts to meander and convert from a stable to an unstable detached jet is investigated. At the seasonal scale, the location of this destabilization point presents zonal shifts displacing the Gulf Stream path to the north in summer and fall and to the south in winter and spring. In addition, it presents variations at interannual scale and has varied by more than 1400 km in longitude, showing meridional shifts of 300 km over the altimetric era: it exhibits a low-frequency remarkable shift westward and southward between 1995 and 2012. From that year, the destabilization point displacement inverses, exhibiting a previously unreported migration eastward and northward that translates into a larger fraction of the stable detached jet to the detriment of the unstable meandering jet. Changes in the Gulf Stream path impact both associated mesoscale eddy kinetic energy and waters transported towards the subpolar North Atlantic. The observed shifts of the path destabilization point seem to be linked to North Atlantic Oscillation variability during winter that may play an important role: it presents a negative trend associated with a shift from a positive to a negative phase between 1995 and 2011 and an opposite behavior from a negative to a positive phase from that year until 2020 in agreement with the associated southwestward and northeastward observed migration of the destabilization point.

Method for Mining High-utility Patterns in Transaction Stream Data based on Linked List Structure

Mining valuable patterns in data streams presentsa significant challenge in the field of data mining. Thistask is crucial as it allows for the identification of highlyprofitable item sets within transaction databases. However, asnew transactions are continually added, new valuable patternsemerge, thus changing the usefulness of previously analyzeddata. It is essential to promptly update information regardingthese changes to enable effective business decision-making.Consequently, existing mining methods applied to transactionflow datasets require considerable time to identify newpatterns and update information related to new transactions.This article focuses on the research and proposal of a newtransaction stream data mining method called High-UtilityStream Linked-List Mining. The method utilizes a linkedlist structure known as the High-Utility Stream Linked List(HUSLL) to store information about patterns in the database.Mining and updating transaction information are directlyperformed on the HUSLL structure. Experimental resultsdemonstrate that this novel mining method exhibits moreefficient execution times compared to previous solutions.

Influence of Different Submerged Entry Nozzles for Continuous Casting of Ultrathick Slab

Controlling the flow activity at the meniscus in the mold during the continuous casting of ultrathick slab is challenging due to the complex flow behavior, which is not extensively documented. Herein, a multiphase transient model of the ultrathick slab mold has been developed to describe the flow of molten steel, velocity distribution, and stream pattern at different submerged entry nozzle (SEN) outlets. The position of impact points and the fluctuation of liquid level are discussed as well. After ejecting from the port, the stream of the S‐shaped SEN splits into upper and lower streams. The upper stream moves to the liquid level, which improves the liquid level activity near the SEN. However, the reduced mainstream momentum alleviates the occurrence of slag layer exposure. Industrial application of the S‐shaped SEN results in uniform slag distribution and smooth casting operations.

Primary return air or all fresh air? A novel method for air source designing of heat pump desiccant wheel systems

Hybrid desiccant wheel systems are widely adopted for low humidity control in industrial field. The clarification of process and regeneration air management is required to achieve energy saving. The all-fresh air dehumidification and primary return air dehumidification are compared for a high-polymer desiccant wheel and heat pump system. The system simulation model was established and validated by field test results of a low humidity industrial workshop. Firstly, the fresh air flowrate and air stream pattern are analyzed and optimized, for achieving low annual energy consumption. Secondly, the system power of the optimized fresh air mode and primary return air mode were compared for different outdoor air temperature, outdoor air humidity and indoor humidity requirement. At last, energy saving rate of all fresh air dehumidification mode was analyzed for five typical climate zones in China. It was found that the optimized fresh air flowrate numerically equals to the summation of regeneration air flowrate and the positive pressure required air flowrate. With the optimized fresh air flowrate, 20.4% of the annual energy can be saved compared with primary return air system. Outdoor air conditions were divided into three zones on psychrometric chart, and the boundaries are related to indoor temperature and humidity ratio. Fresh air is energy efficient for high temperature high humidity and low temperature low humidity conditions. By using fresh air dehumidification mode, the energy saving rate can reach 69.6% for severe cold region. Primary return air dehumidification mode is suitable for HSCW and HSWW region for indoor relative humidity of 40%, and 41.8% of the energy can be saved.

Factors influencing seasonal chemistry patterns in Virginia mountain streams

The relative influence of seasonal patterns in hydrological flow and seasonal differences in biological and geochemical activity on stream chemistry patterns is difficult to discern because they covary; temperate systems are characterized by lower mean flow in the summer (i.e. corresponding to deeper flow paths, elevated temperature, and biological activity), and higher mean flow in the winter (i.e. corresponding to shallower flow paths, depressed temperature, and biological dormancy). Using 2018 data, when seasonal stream flow conditions reversed, and two prior conventional water years, the relationship between monthly acid-relevant analyte concentrations and streamflow were compared within and between winter and summer to provide insight into controls on characteristic seasonal chemistry patterns at two mid-Appalachian sites with distinct geology (weatherable mafic and weather resistant siliciclastic). Acid neutralizing capacity (ANC) increased (1) with lower flow, in both seasons and (2) in summer, for all flow conditions. The compounding impacts resulted in a doubling of concentration from typical winter with high flow to summer with low flow at both sites. Base cation patterns tracked ANC at the mafic site, resulting in an ~ 60% increase of from winter with high flow to summer with low flow; distinctions between summer and winter contributed more to the seasonal pattern (72%) than changes in flow. Sulfate increased at the mafic site (1) with higher flow, in both seasons and (2) in winter, for all flow conditions, resulting in an ~ 50% increase from summer with low flow to winter with high flow; distinctions between winter and summer conditions and flow contributed similarly (40–60%) to the typical seasonal chemical pattern. The biogeochemical mechanism driving differences in stream chemistry between summer and winter for the same flow conditions is likely increased rates of natural acidification from elevated soil respiration in summer, resulting in greater bedrock weathering and sulfate adsorption. Findings highlight the significance and consistency of growing vs dormant season variations in temperature and biological activity in driving intra-annual patterns of stream solutes. This data set informs parameterization of hydro-biogeochemical models of stream chemistry in a changing climate at a biologically relevant, seasonal, timescale.

Exploring stream patterns of titania-CNTs blended blood in a squeezed artery subject to electro-magnetization, Hall and ion-slip currents

Exploring stream patterns of titania-CNTs blended blood in a squeezed artery subject to electro-magnetization, Hall and ion-slip currents

Geological Mapping of Kaso, Tambaksari, Ciamis, West Java Province Using Lidar Images Interpretation

Abstract Remote sensing nowadays is used to quickly and effectively obtain information about an object, area or phenomenon and can be applied to large areas that are sometimes difficult to reach. Satellites with multispectral imagery are commonly used in geological mapping, but have drawbacks when used in tropical areas such as Indonesia, with dense vegetation, fast sedimentation rates and highly weathered that will cover fresh rocks making it difficult to interpret geological condition through aerial photo. Light Detection And Ranging (LiDAR) images using laser beams to produce elevation data (x,y,z) with high spatial resolution and can penetrate the surface of vegetation are expected to be a solution in areas with dense vegetation that are sometimes difficult to reach. The study was conducted by interpreting the morphometric aspects using Digital Terrain Model (DTM) data processed from LiDAR imagery with a spatial resolution of 1 m/pixel to display the topographical surface in detail. The morphometric aspects used include slope, surface roughness, aspect, hillshade, and stream pattern. Field data validation through surface mapping is carried out to correct the lithology interpretation by comparing the results of LiDAR image interpretation. Field data validation results show that interpretation using LiDAR imagery has good results (79%) through overall accuracy percentage, with the lithology units being sandstones, siltstone, breccias, and andesitic igneous rocks. The lineament interpretation of the DTM data indicates the existence of a geological structure in the form of a normal and strike-slip fault in the study area.

E-Gaze: Gaze Estimation With Event Camera.

Near-eye gaze estimation is a task that maps the recording of an eye captured by an adjacent camera to the direction of a person's gaze in space. In contrast to frame-based cameras, event cameras are characterized by high sensing rates, low latency, sparse asynchronous data outputs, and high dynamic range, which are well suited for recording the fast eye movements. However, algorithms and system designs that operate on frame-based cameras are not applicable to event-based data, due to the natural differences in the data characteristics. In this work, we study the pattern of near-eye event-based data streams and extract eye features to estimate gaze. First, by analyzing eye parts and movements, and harnessing the polar, spatial, and temporal distribution of the events, we introduce a real-time pipeline to extract pupil features. Second, we present a recurrent neural network with a proposed coordinate-to-angle loss function to accurately estimate gaze from pupil feature sequence. We demonstrated that our system achieves accurate real-time estimation with angular accuracy of 0.46 ° and update rates of 950 Hz, thus opening up avenues for novel applications. To our knowledge, this is the first system that operates only on event-based data to perform gaze estimation.

DecoPa: Query Decomposition for Parallel Complex Event Processing

Systems for Complex Event Processing (CEP) enable the detection of predefined patterns in event streams. While the evaluation of CEP queries is computationally hard, scalability may be achieved by parallelization. Yet, existing approaches for parallel CEP are driven by static query properties, such as partitioning keys and states of the evaluation model. They largely neglect the rates with which processing units may ingest and compare events for query evaluation. In this paper, we present an approach for parallel CEP that is based on a flexible decomposition of CEP queries. Our idea is to guide the decomposition by the sustainable throughput of each processing unit, in order to maximize the overall performance. To this end, we introduce DecoPa plans for parallel CEP, provide a cost model for them, elaborate on their correctness and optimality, and present an algorithm for their construction. Experiments using a DecoPa implementation in Flink illustrate throughput gains of up to 12 orders of magnitude compared to state-of-the-art approaches.

Long-short term memory networks aided fault detection of power facilities

In recent years, long-short term memory (LSTM) networks have emerged as a promising tool for time-series analysis, offering the ability to capture temporal dependencies effectively, especially for the fault detection in power facilities which is crucial for maintaining operational integrity and ensuring continuous power supply. This paper presents a study on the utilization of LSTM networks for fault detection in power facilities, focusing on evaluating the detection accuracy as a performance metric. We propose a novel LSTM-based fault detection framework that utilizes historical operational data to identify abnormal patterns indicative of faults or anomalies. The framework is trained on labeled data to learn the normal operational behavior of the power facility, enabling it to detect deviations from expected patterns in practical data streams. To assess the effectiveness of the proposed approach, extensive experiments are conducted using real-world operational data from diverse power facilities. We systematically evaluate the detection accuracy of the LSTM-based fault detection system under various operating conditions, including different types of faults and levels of noise in the data. Comparative analyses are performed against traditional fault detection methods to demonstrate the superiority of the LSTM-based approach in terms of accuracy. Moreover, sensitivity analyses are conducted to investigate the impact of key parameters, such as network architecture and training data size, on the detection performance. The results illustrate the robustness and effectiveness of the proposed LSTM-based fault detection framework, highlighting its potential for enhancing the reliability and efficiency of power facility operations.

Mathematical Modeling and Design of Parboiled Paddy-Impinging Stream Dryer Using the CFD-DEM Model.

Impinging stream dryers (ISDs) are effective for removing moisture from particulate materials because of the complex multiphase transport of air particles in ISDs. Nowadays, computational techniques are powerful to simulate multiphase flows, including dilute and dense-phase gas-solid flows and hence, the use of a reliable computational model to simulate the phenomena and design a dryer has recently received more attention. In this study, computational fluid dynamics, combined with the discrete element method (CFD-DEM) and falling drying rate model, were used to predict the multiphase transport phenomena of parboiled paddy in a coaxial ISD. The design of an impinging stream pattern for improving residence time in a drying chamber of ISD was also investigated. The results showed that the CFD-DEM, in combination with the falling drying model, could be well-utilized to predict the particle motion behavior and lead to more physically realistic results. The predicted change of moisture content in parboiled paddy was in good agreement with the experimental data for 17 cycles of drying. Although the prediction of mean residence time was lower than the experimental data, the predicted mean residence time was a similar trend to the experimental data. For ISD design, the simulation revealed that the use of two stages of impinging stream region (two streams collide at the top of the drying chamber at the first stage and then the gas particles flow on the incline floor to collide with the other stream at second stage) in a drying chamber could increase the residence time approximately 75% and reduce drying cycle from 17 to 10 cycles when it was considered at the same final moisture content.

Rule based complex event processing forIoTapplications: Review, classification and challenges

AbstractIn recent decades, data aggregation and correlation have emerged as a significant and challenging area of research for finding useful relationships between different features of streaming data. Similarly, complex event processing (CEP) has emerged as a vital tool for aggregating and finding patterns from streaming data such as video streaming, real‐time stock trades, sensor data and more. In this context, rule‐based classifier algorithms are widely employed to discover valuable patterns from streaming data and cause‐and‐effect relationships between events. However, streaming data is dynamic and complex in nature, and it is not feasible to update the rules manually by domain experts continuously. On the contrary, dynamic data sometimes fails to adopt rules, which leads to sub optimal CEP implementation. Rule‐based CEP systems come up with their own set of challenges, which primarily includes rules adaptability for streaming IoT data. In dynamic environment, shifting patterns in data streams can impact the performance of the CEP system, as well as the correlation between events, and finding useful patterns is very much challenging. In this article, our objective is to provide a comprehensive survey for CEP using rule‐based algorithms applied across various domain and applications. We present a broad literature review using a sequential expansion of methods used for CEP, which primarily include event producers, preprocessing of events, robust rule implementation, and decision support. Additionally, we present a detailed classification of approaches used for different applications. Finally, after applying the rigorous review, it was feasible to present the state‐of‐the‐art research, which focuses on designing robust rules, application specific insights, scalable event‐driven architectures and finding the domain's trends with significant challenges and future scope.

Prufrock: The Delegate of Modern Man

The ‘Love Song of J. Alfred Prufrock,’ a great work of art by the great modern poet and critic T. S. Eliot, started in 1911 was published in 1917 after the publication of the “Preludes” (1915). It is considered, a dramatic monologue as Tennyson’s ‘Ulysess’ and has been composed in the pattern of Stream of Consciousness. It is the poetry of anguish against the growing materialism augmented by the impact of the World-War I (1914-1919). The trauma of the war lingered, making people apprehensive of the uncertainty of the situation and difference of the gigantic problems of life. Materialism and commercialism appeared to choke the human emotion and feelings that led the poets to attack the trend with wit and irony. The Epigraph taken from Dante’s ‘Inferno’ forms the root image of the poem. The Epigraph suggests the vagueness of the speaker’s thought but the images are quite distinct and the range of wit is very wide. The opening line of the poem with their colloquial language presents a break from Victorian poetry – ‘Let us go then You and I.’ [1] Prufrock has nursed love in his heart but has not been able to convey his feelings to his beloved. He ponders: ‘we have lingered in the chambers of the sea.’ [2] Time has moved to form a bald on the middle portion of his head, yet he has not been able and courageous enough to cough out his feelings to his beloved and nor he feels the need of a face to meet the ‘faces we meet.’ He is in the ‘Autumn’ of life advancing to ‘Winter’, yet is unable to express his love to his beloved, although he has been craving for the same since long and has been procrastinating and idle only fancying: ‘There will be time there will be time.’ [3] suggesting his belief that there is a reason for every happening, taking place everywhere. He evaluates himself that he has lived a club life having no life force save the passing of days and has measured his life with ‘coffee-spoons.’ Prufrock suffers from inaction and indecision that reminds us of Hamlet, the prince of Denmark who had divided-self oscillating between ‘to be or not to be.’

Stream ecosystem puzzle: understanding how water column and sediment variables shape macroinvertebrate patterns in some Afrotropical streams.

Although the interaction of water column and sediment variables in streams is intricate, minimal studies have been conducted on how they influence macroinvertebrate community patterns. This study, therefore, aimed to evaluate the influence of water column and sediment variables on macroinvertebrate community patterns in selected Afrotropical streams. Spatiotemporal scales of water column and sediment variables were analysed following standard methods while macroinvertebrates were sampled using the kick sampling technique. Redundancy analysis (RDA) and variation partitioning were used to assess the relationship of macroinvertebrates with water column and sediment variables. Significant differences were observed between seasons amongst water column variables such as total dissolved solids (p=0.046), turbidity (p=0.027), dissolved oxygen (p=0.011), chemical oxygen demand (p=0.002), bank vegetation (p=0.013), velocity (p=0.04), phosphates (p=0.031), and sediment variables such as total organic matter (p=0.01), pH (p=0.024), electrical conductivity (p=0.014). This accounted for the shift in biotic communities across the two seasons. In the studied area and seasons, Baetidae, Chironomidae, and Thiaridae were the most abundant families of macroinvertebrates representing 21.5%, 17.8%, and 6.9% of the 5266 recorded individuals belonging to 68 families. The water column was the most important predictor of macroinvertebrate community patterns (57%) compared to sediments (35%). Therefore, the use of both water column and sediment variables in ecological studies and biomonitoring should be emphasised because the two compartments provide complementary information. This enables researchers to gain a more complete understanding of the ecological health of aquatic habitats, useful in the development of effective management strategies.

Capacity drop at the bus stop on multilane divided urban roads under mixed traffic conditions

Time headway characteristics are of great importance for planning and design of roadway. The present study determines time headway distribution pattern of vehicular stream at various urban roads and evaluate drop in capacity of roadway section having curb-side bus stops. Field data for present study was collected at 8 different locations on four-lane and six-lane divided sections in the cities of Warangal and Hyderabad in India. The mean time headway of heterogeneous vehicles fitted to various headway distributions for estimating capacity of road section. The factors affecting the capacity have been identified as bus frequency, dwell time, and the average roadway width lost. Percentage reduction in capacity (PRC) is determined to develop regression model. Further, speed-flow diagrams were developed using field observed traffic flow data for determining parameters free-speed, critical speed, and roadway capacity on selected section. After comparing capacity values obtained from two methods, the study determined avg. time headway of vehicular stream under the traffic flow at capacity and free flow conditions. The study also finds capacity value of bus stop section using methodology provided in Indo-HCM (2017). The PRC values estimated based on Indo-HCM guidelines are found to be significantly higher than those estimated by the proposed PRC model. It is due to the Indo-HCM guideline considering only one parameter i.e. bus frequency. The study finds, in addition to bus frequency the dwell time, roadway width lost, and presence of an extra lane also influences the drop in capacity of bus stop section on multilane divided urban roads.