Bottleneck

In this graduation thesis the method of simulation is described as one of the methodologies for bottlenecks analysis and process improvement. Further in the content are presented the bottleneck types, the reasons for their occurrence as well as the methods for identifying the bottleneck in the process. The emphasis, with the aim of this paper, is the improvement and analysis of the bottlenecks using the simulation method. With the help of simulation software-Technomatix Plant Simulation, a production process for wooden chairs has been programmed for analysis. With the Bottelenck Analyzer tool the process is analyzed and the bottlenecks are identified. The data obtained from the analyzes were used to improve the model, by experimenting with the basic model. In order to get an improved model, more experiments were made. From the experiment, more improved models have been obtained with increased productivity.

As an agro-based country, Bangladesh has the competitive advantage on vegetable industry since long and due to this fact, many researches has been done on this industry focusing on competitiveness, production & process, trade facilitation, value addition ET el. Being one of the largest producers of vegetable, some bottlenecks on the supply chain are dragging Bangladesh out of the race from global competition. Now, the paper is focused on finding and thus, emancipating the supply chain bottlenecks of this industry. Here, the paper shows, an unnatural price gap between the upstream and downstream parties on the chain. Explains the reasons behind this-which is the present SC model. Also finds the cure to fix the problem by proposing a cross-dock based agent led model to minimize the exploitation of intermediaries toward growers and end consumers. Finally, shows a case study to validate the authenticity of the proposed model.

This paper presents a novel Bottleneck Tree Analysis (BOTA) to cope with the increasing capacities within industrial refineries. BOTA is a clear and concise heuristic graphical debottlenecking method that can accurately pinpoint the process capacity bottlenecks. Coupled with BOTA, four multiple criteria decision-making methods are used for an ensemble with Spearman's correlation to assess the Green and Lean Index (GLI) of industrial processes. The decision-making tool is formulated to improve operational performance with the consideration for environmental conditions. Empirically, BOTA demonstrated a debottleneck stopping mechanism which can be theoretically explained with the reversed onion model. An additional advantage is that retrofit projects can be guided by BOTA with effective scheduling. From an industrial case study, BOTA improved normalized Global Warming Potential by 94.43 %, normalized energy consumption by 93.09 % and return on investment by 58.36 %. Project implementation by scheduling also reduced payback period from 85 to 66 months.

This chapter provides an overview of the communication-human informaton processing (C-HIP) model. CHIP is a framework that describes warning processing and organizes the warning research literature into a coherent structure. As part of the discussion, an overview of the influential factors at each stage of the model is presented. Other separate chapters in this Handbook give more details for each of the stages. Lastly, another practical aspect of the O{IIP model is described whereby it can be used as an investigative tool to determine why a warning failed.

Why should the concept of Imperatively Hidden Elements (IHE) become common knowledge, especially in machine learning and feature selection? Did everyone, except for me, knew all along that our scientific progress-rate limiting bottlenecking factor is proper feature selection but not the lack of advances in improving our machine learning algorithms? I assumed that this could not be the case because most publications present improvements in machine learning algorithms, but neglect to even mention that lack of progress in better feature selection is preventing us from making any significant progress but not poorly performing machine learning algorithms. I thought that if I did not know that until my defense, then most others, especially those who don't know much about machine learning yet, i.e. most of our wet-lab biologists, who need to design their experiments accordingly, are not aware of this problem either. Then I thought I must tell them or else they keep mistakenly misinterpreting unpredictable outcomes as unavoidable noise instead of correctly realizing that still imperatively hidden elements (IHE) affect our predicted outcome in manner, which we cannot yet explain, unless we start observing the last temporal visible object/observation/event, after which we can no longer correctly predict the chain of subsequent events or observations, from many different perspectives and angles in order to really scrutinize it legitimacy, because most likely, it is composed of more than a single visible object (VO), of which we are already aware, because an undetermined number of distinctly different, but yet still imperatively hidden; thus inevitably for us still imperceptible, but nevertheless fully legitimate and truly existing yet invisible objects look too similar to our only visible object, which tricks us into the illusion of erroneously believing that it's only a single object. But the truth is that it is actually 2 or more objects, between which we cannot yet distinguish. Nevertheless, the number of possible outcomes depends on the number of truly existing objects, regardless whether or not we can distinguish them from their background. For example, until this morning, I was not aware of the difference between Python and Cython. Cython was for me in imperatively hidden object, which to me looked exactly like Python, because Cython is almost identical to Python, except for, that its variables must be of a specified type, e.g. string, vector, list, numeric, data frame, etc., which is not the case in Python. This led to my observation that some Python packages run fine on Windows whereas other never worked. Since the PyAffy.py library must have been written in Cython, it tricked me into the illusion that the only way to use a Python package, which fails to run under Windows, is to use Linux. It took us 3 months to set up a Linux laptop I could see. Now I discovered that we could have copied the Cython code and save it as a Python file by omitting specifying the variable type and run it just like a Python file. If we had used machine learning to discover the reason for some Python packages, specifically the PyAffy-package not running under Windows, could machine learning figure out that the feature " variable type selection " , which is a Boolean of present or absent, can be used to distinguish between Python and Cython? If we just gave the programming code of Python libraries and the outcome of running and not running as training data for supervised machine learning, could it figure out without any prior knowledge about Cython, that a programming language other than Python is causing problems under Windows? Can machine learning learn programming? Can it learn to conceptually understand the differences between variable types, If the concept of IHE is true, then most graduates are not well prepared to deal with imperatively hidden elements (IHE), because they appear to be totally left in the dark about this dangerously unnecessarily very time-consuming temporary progress-preventing nettlesome barrier, which can halt progress for many years, because nobody ever shared with them (i.e. our future wet-lab scientists, who must choose wisely, which data they collect for the computational analysts, to reach valid conclusions) the concept that the risk for misinterpreting poor outcome predictability as unavoidable background noise instead of getting alerted that a still imperatively hidden element (IHE), which we cannot perceive yet, creates a much bigger and more dangerous obstacle, than any visible element, which has at least one feature that causes it

This paper contributes to identify systematic problems in NIS using Thinking Process (TOC-TP) and to eliminate the bottlenecks, which results in improving the innovation process and efficiency of NIS. The Case study in this research is the NIS of Iran. The national documents of the innovation system were studied and all problems of NIS mentioned in documents were gathered.
The causal relationships between the systematic problems were identified by the survey and grouped into 6 components by Exploratory Factor Analysis: weakness in technology diffusion mechanisms, the lack of centralized governance on science and technology policy, the government’s pivotal role as an executor in education and research, weak laws and regulations in the field of research and technology, the lack of adequate financial resources in R&D and the lack of any perspective on the creation of wealth and entrepreneurship among the actors of research and technology. Finally the bottleneck of Iran’s NIS was recognized by Thinking Process tools: the small participation of private sector in research and education system as the result of government’s pivotal role as an executor of Iran’s national innovation system. So the researchers could diagnose the policy gaps related to the identified bottlenecks.

This chapter provides an overview of the communication-human informaton processing (C-HIP) model. CHIP is a framework that describes warning processing and organizes the warning research literature into a coherent structure. As part of the discussion, an overview of the influential factors at each stage of the model is presented. Other separate chapters in this Handbook give more details for each of the stages. Lastly, another practical aspect of the O{IIP model is described whereby it can be used as an investigative tool to determine why a warning failed.

As an agro-based country, Bangladesh has the competitive advantage on vegetable industry since long and due to this fact, many researches has been done on this industry focusing on competitiveness, production & process, trade facilitation, value addition ET el. Being one of the largest producers of vegetable, some bottlenecks on the supply chain are dragging Bangladesh out of the race from global competition. Now, the paper is focused on finding and thus, emancipating the supply chain bottlenecks of this industry. Here, the paper shows, an unnatural price gap between the upstream and downstream parties on the chain. Explains the reasons behind this –which is the present SC model. Also finds the cure to fix the problem by proposing a cross-dock based agent led model to minimize the exploitation of intermediaries toward growers and end consumers. Finally, shows a case study to validate the authenticity of the proposed model.

As an agro-based country, Bangladesh has the competitive advantage on vegetable industry since long and due to this fact, many researches has been done on this industry focusing on competitiveness, production & process, trade facilitation, value addition ET el. Being one of the largest producers of vegetable, some bottlenecks on the supply chain are dragging Bangladesh out of the race from global competition. Now, the paper is focused on finding and thus, emancipating the supply chain bottlenecks of this industry. Here, the paper shows, an unnatural price gap between the upstream and downstream parties on the chain. Explains the reasons behind this –which is the present SC model. Also finds the cure to fix the problem by proposing a cross-dock based agent led model to minimize the exploitation of intermediaries toward growers and end consumers. Finally, shows a case study to validate the authenticity of the proposed model.

In this study, we show that the challenging service processes in the health care sector can be improved similarly to those of any other business sector when seeking efficiency and productivity. Two separate case organizations (acute neurology ward and children's dental clinic) from the health care sector were analyzed with the 3VPM (Three View Point Model) methodology that has also been used in several other businesses. A multi-method approach was used to acquire data for the analyses, including interviews and observation completed with numerical data. The first case represents a case where an ICT-related issue acted as a bottleneck, while the second case focuses on renewing the provisioning processes. In both cases, the analysis showed that improvement is possible and also pointed out benefits from different changes. However, the main result is dependent on the decision: will the proposed changes be made or not? Keywords

Bottlenecks are a common feature of people's movement through urban space, and in most cases, squeezing through them is symbolically mundane. But on pilgrimage, people's sacred and subjective imaginations are engaged: they immerse themselves in stories—physically and discursively—as they approach their sacred destination. What happens, therefore, when people squeeze through bottlenecks on pilgrimage? In this chapter, I observe that the bottleneck passage reflects a constellation of interactions between the physical spaces, the meaning pilgrims attribute to their journeys, their ease of passage through the tight spaces, and their perceptions of those who manage the bottleneck flow. The issue of bottleneck-management is particularly relevant in conflicted religious spaces: people's sacred experiences are fused to the perceived legitimacy—or illegitimacy—of those who manage the flow. I define this constellation of dynamics as the bottleneck-optic.

I develop the bottleneck-optic through analysis of Muslim pilgrimage to al-Aqsa Mosque on Ramadan Fridays. During Ramadan, approximately 300,000 Muslims journey to Al-Aqsa Mosque for Friday prayers. While pilgrims come from various places, I focus attention on pilgrims from the West Bank and discuss three separate bottlenecks they encounter along the way: Qalandia Checkpoint, the Damascus Gate, and the Lion’s Gate. Each case illustrates the various and subjective ways the pilgrimage experience is constituted by the physical, aesthetic, and administrative dimensions bottlenecks. I conclude by discussing the relevance of the bottleneck-optic for other sites of urban religious conflict. This chapter is based on ethnographic research conducted in Jerusalem between 2011-2016 and draws from insights in the field of urban studies, sacred sites, pilgrimage, and bottlenecks.

Computer vision strategies have been employed in latest years to produce precise & generic linear regressions of crowd counts. Cross counting is stimulating chore besides serious occlusions, differences in size, inconsistencies in the viewpoint and lighting conditions. For this reason researcher propose a deep spatial regression model for the number & arbitrary tenacity of persons contemporary in still picture. Our suggested model is grounded on CNN & long term memory. To derive a series of high level characteristics, researchers places the images in a pre-trained CNN. The characteristics in adjacent regions are then used to reverse the counts of the locals with an LSTM structure which considers spatial data. A calculation of the local patches is used to achieve the final global count. Crowd counting & density assessment issue is superior to status of art reliable and efficient approaches. Researchers apply oursystem to different difficult crowd count data sets. India is a land of immense culture & tradition in which festivals, social or cultural events take place almost every day. Large quantity of folks are involved in this kind of meeting to control the crowd with the workforce. This research is therefore about this issue being overcome and technology is tracking and managing the crowd. The new technology is about to foresee the bottleneck and give moving crowds the scale, speed and direction. The multitude estimate is grounded on data collected last year i.e. the size of mass, the speed and the direction of the moving crowd which estimates the area and time of the bottleneck occurring by Artificial Neural Network (ANN)

Daily mobility patterns in highly populated urban environments rely on a well-functioning effective road network. Nevertheless, traffic bottlenecks are typical for urban environments with periodic traffic congestion. In this paper, we focus on the investigation of how traffic congestion is related with complicated crossings. First, we select an approach for the classification of the complexity of road partitions and the derivation of complicated crossings based on geodata from Open-StreetMap (OSM). Second, we calculate traffic congestions using Floating Taxi Data (FTD) from Shanghai in 2007. Then, we develop a matching technique to link the congestion and complicated crossings, and subsequently define the concept of traffic bottlenecks represented by polygons. The bottlenecks indicate locations where the transportation infrastructure is complex and traffic congestion appears periodically. Finally, we select suitable cartographic representations of traffic bottlenecks in potential thematic vehicle traffic maps.

Equality of opportunity, once a rather peripheral idea in debates over distributive justice, is receiving increased attention. In his recent book, Bottlenecks: A New Theory of Equality of Opportunity, Joseph Fishkin takes on the task of proposing 'a new way of thinking about equal opportunity and about the myriad of questions in law, public policy, and institutional design that center on notions of equal opportunity' (1). For two reasons this is a quite ambitious task. One is that the literature on equal opportunity is now vast, which makes it hard to flesh out a novel contribution and relate it to existing positions. The other is that the idea of equality of opportunity seems relevant in so many different and diverse areas that discussing specific applications will almost always result in important areas being left out or not given sufficient attention. However, in pursuing his aim, Fishkin delivers an interesting account. Fishkin states that opportunities are important because of what they enable us to do and become, and because the opportunities open to us shape who we are (2, 3). He voices a number of reservations regarding how the literature usually engages with the idea of equality of opportunity. Importantly, he stresses that we tend to discuss equality of opportunities as ex ante structures, and tend to consider the ideal fulfilled once people have equal opportunities from birth (or upon entering adulthood) (7). According to Fishkin such reasoning fails to acknowledge the importance of opportunities available to people 'along the way, including for those who have, for one reason or another, failed to jump through important hoops at particular ages' (7). Caring for people's ability to shape their own lives should also

Information on the demographic and genetic consequences of overexploitation of large marine verte- brates is often difficult to demonstrate on ecological time scales. We investigate the genetic impacts of recent commercial activities along Mexico’s Pacific coast on the nesting colonies of a long-lived verte- brate of conservation concern, the olive ridley turtle (Lepidochelys olivacea). This species was severely impacted by a commercial fishery between 1960 and 1990 (e.g. >350,000 individuals were caught in a single year), depleting important nesting areas within few decades. Microsatellite DNA variation of 334 samples representing 18 nesting sites revealed a clear signature of recent bottlenecks associated with changes in allelic diversity. Consistent with theoretical expectations and other empirical studies, we found no evidence for bottlenecks based on measures of heterozygosity. The bottleneck signal was strong across the highly connected metapopulation and also apparent in six nesting sites in a pattern consistent with the history of demographic disequilibria produced by their overexploitation. In addition, we clarify population structure across Mexico and show that Mismaloya, a key colony where human harvest led to a dramatic change in the species’ reproduction mode, has not been supplemented by gene flow after the bottleneck and has diverged genetically from other demes. This is perhaps the first study to detect recent signatures of anthropogenic-driven population declines in sea turtles using genetics. This enables man- agers to consider information about genetic signatures of contemporary demographic changes during the development of conservation management plans and during population monitoring

The pedestrian walking data collected at nineteen locations in five cities of India are analyzed in this paper. Pedestrian facilities are classified based on their width as sidewalk, wide-sidewalk and precincts. The analysis indicates that the pedestrian free flow speed is high on sidewalks (1.576 m/s) and low on precincts (1.340 m/s). The increase in width of the facility resulted in increased space available to a pedestrian, but reduced maximum flow rate and optimum density. It is found that the relationship between speed and density follows Underwood (exponential) model on sidewalk of varying widths and Greenshield’s (linear) model on a non-exclusive facility. Bi-directional flow on a facility affects the free flow speed and space available to the pedestrian adversely at high density. Squeezing effect at the centre and follow the predecessor near sides is observed under heavy bidirectional flow. The presence of a bottleneck reduces the free flow speed and maximum flow substantial...

In this paper I present an intensively dated chrono-stratigraphic sequence for Cueva Huenul 1 archaeological site (Neuquén Province, Argentina), located in the inland deserts of northwestern Patagonia, which offers a remarkable temporal record of events for a desert region largely unstudied. Then, I connect this local record with available data in a macro-regional scale to reassess (a) the timing of first human colonization and its implications for explaining the extinction of the megafauna (~14000-10000 years B.P.); and (b) the decreased intensity of human occupation recorded at several South American deserts during segments of the mid-Holocene (~8000-6000 years B.P.). The data presented here shows a ~1500 calendar years gap between humans and megafauna. A review of the evidence from northern Patagonia and southern Cuyo regions is consistent with this record, favoring ecological causes for regional extinction of megafauna taxa. Integration of this record with those indicating the earliest human presence in South America (v.g. Monte Verde locality) is consistent with a process of human radiation to the inland Patagonian deserts from nodes of initial occupation.
The chrono-stratigraphic sequence from CH1 also contributes to an assessment of a trough in human occupation along the South American Arid Diagonal around 8000-6000 years B.P. This low-intensity record includes the highland and lowland deserts from southern Mendoza, northern Mendoza and San Juan, the Puna region from northwestern Argentina, the Atacama Desert in Chile, and the possible case of the Pampean region. Previous researchers have suggested that persistent arid conditions would have produced an increasing process of landscape fragmentation affecting desert areas in particular. A more specific understanding of the underlying demographic processes behind this archaeological signal is needed. In this paper I suggest that this trough reflects not only spatial and organizational rearrangements, but also a macro-regional demographic retraction, which could have produced a population bottleneck with lasting biological and cultural spin-offs.

Approximate Bayesian Computation (ABC) has become a popular technique in evolutionary genetics for elucidating population structure and history due to its flexibility. The statistical inference framework has benefited from significant progress in recent years. In population genetics, however, its outcome depends heavily on the amount of information in the dataset, whether that be the level of genetic variation or the number of samples and loci. Here we look at the power to reject a simple constant population size coalescent model in favor of a bottleneck model in datasets of varying quality. Not only is this power dependent on the number of samples and loci, but it also depends strongly on the level of nucleotide diversity in the observed dataset. Whilst overall model choice in an ABC setting is fairly powerful and quite conservative with regard to false positives, detecting weaker bottlenecks is problematic in smaller or less genetically diverse datasets and limits the inferences possible in non-model organism where the amount of information regarding the two models is often limited. Our results show it is important to consider these limitations when performing an ABC analysis and that studies should perform simulations based on the size and nature of the dataset in order to fully assess the power of the study.

Recent years have witnessed an emerging paradigm shift toward embodied artificial intelligence, in which an agent must learn to solve challenging tasks by interacting with its environment. There are several challenges in solving embodied multimodal tasks, including long-horizon planning, vision-and-language grounding, and efficient exploration. We focus on a critical bottleneck, namely the performance of planning and navigation. To tackle this challenge, we propose a Neural SLAM approach that, for the first time, utilizes several modalities for exploration, predicts an affordance-aware semantic map, and plans over it at the same time. This significantly improves exploration efficiency, leads to robust long-horizon planning, and enables effective vision-and-language grounding. With the proposed Affordance-aware Multimodal Neural SLAM (AMSLAM) approach, we obtain more than $40\%$ improvement over prior published work on the ALFRED benchmark and set a new state-of-the-art generalizatio...

In this paper, we address the problem of load balancing in Wireless Mesh Networks. We consider a Cluster Based Wireless Mesh Architecture in which the WMN is divided into clusters that could minimize the updating overhead during topology change due to mobility of mesh nodes or congestion of load on a cluster. Each cluster contains a gateway that has complete knowledge about group memberships and link state information in the cluster. The gateway is often elected in the cluster formation process. We consider load of gateways and try to reduce it. As a matter of fact when a gateway undertakes to be an interface for connecting nodes of a wireless mesh network to other networks or internet, there would be some problems such as congestion and bottleneck, so we introduce a new paradigm for these problems. For solving bottleneck we use clustering to reduce load of gateways and after that by use of dividing cluster we prevent from bottleneck on gateways. We study how to detect congestion on...

Computer vision strategies have been employed in latest years to produce precise & generic linear regressions of crowd counts. Cross counting is stimulating chore besides serious occlusions, dif erences in size, inconsistencies in the viewpoint and lighting conditions. Forthis reason researcher propose a deep spatial regression model for the number & arbitrary tenacity of persons contemporary in still picture. Our suggested model is grounded on CNN & long term memory. To derive a series of high level characteristics, researchers places the images in a pre-trained CNN. The characteristics in adjacent regions are then used to reverse the counts of the locals with an LSTM structure which considers spatial data. A calculation of the local patches is used to achieve the final global count. Crowd counting & density assessment issue is superiorto status of artreliable and efficient approaches. Researchers apply oursystem to dif erent dif icult crowd count data sets. India is a land of immense culture & tradition in which festivals, social or cultural events take place almost every day. Large quantity of folks are involved in this kind of meeting to control the crowd with the workforce. This research is therefore about this issue being overcome and technology is tracking and managing the crowd. The new technology is about to foresee the bottleneck and give moving crowds the scale, speed and direction. The multitude estimate is grounded on data collected last yeari.e. the size of mass, the speed and the direction of the moving crowd which estimatesthe area and time of the bottleneck occurring by Artificial Neural Network (ANN).

Computer vision strategies have been employed in latest years to produce precise & generic linear regressions of crowd counts. Cross counting is stimulating chore besides serious occlusions, differences in size, inconsistencies in the viewpoint and lighting conditions. For this reason researcher propose a deep spatial regression model for the number & arbitrary tenacity of persons contemporary in still picture. Our suggested model is grounded on CNN & long term memory. To derive a series of high level characteristics, researchers places the images in a pre-trained CNN. The characteristics in adjacent regions are then used to reverse the counts of the locals with an LSTM structure which considers spatial data. A calculation of the local patches is used to achieve the final global count. Crowd counting & density assessment issue is superior to status of art reliable and efficient approaches. Researchers apply our system to different difficult crowd count data sets. India is a land of immense culture & tradition in which festivals, social or cultural events take place almost every day. Large quantity of folks are involved in this kind of meeting to control the crowd with the workforce. This research is therefore about this issue being overcome and technology is tracking and managing the crowd. The new technology is about to foresee the bottleneck and give moving crowds the scale, speed and direction. The multitude estimate is grounded on data collected last year i.e. the size of mass, the speed and the direction of the moving crowd which estimates the area and time of the bottleneck occurring by Artificial Neural Network (ANN)

Based on the Nagel-Schreckenberg model (NS) we study the probability of car accidents to occur (Pac) at the entrance of the merging part of two roads (i.e. junction). The simulation results show that the existence of non-cooperative drivers plays a chief role, where it increases the risk of collisions in the intermediate and high densities. Moreover, the impact of speed limit in the bottleneck (V b) on the probability Pac is also studied. This impact depends strongly on the density, where, the increasing of V b enhances Pac in the low densities. Meanwhile, it increases the road safety in the high densities. The phase diagram of the system is also constructed.