Drop Probability Research Articles

Defect patterns study of pick-and-place machine using automated optical inspection data

PurposeThis paper aims to study the component pick-and-place (P&P) defect patterns for different root causes based on automated optical inspection data and develop a root cause identification model using machine learning.Design/methodology/approachThis study conducts experiments to simulate the P&P machine errors including nozzle size and nozzle pick-up position. The component placement qualities with different errors are inspected. This study uses various machine learning methods to develop a root cause identification model based on the inspection result.FindingsThe experimental results revealed that the wrong nozzle size could increase the mean and the standard deviation of component placement offset and the probability of component drop during the transfer process. Moreover, nozzle pick-up position can affect the rotated component placement offset. These root causes of defects can be traced back using machine learning methods.Practical implicationsThis study provides operators in surface mount technology assembly lines to understand the P&P machine error symptoms. The developed model can trace back the root causes of defects automatically in real line production.Originality/valueThe findings are expected to lead the regular preventive maintenance to data-driven predictive and reactive maintenance.

Non-native plant removal and high rainfall years promote post-fire recovery of Artemisia californica in southern California sage scrub.

Non-native plant invasions, changes in fire regime, and increasing drought stress all pose important threats to biodiverse mediterranean-climate shrublands. These factors can also interact, with fire and drought potentially creating opportunities for non-native species to establish dominance before native shrubs recover. We carried out post-fire demographic monitoring of the common native shrub Artemisia californica in a southern California sage scrub fragment for 7 years, including several with very low rainfall. Experimental removals of non-native plants were included for the first 4 years. We quantified A. californica post-fire crown resprouting and seedling emergence, and tested effects of precipitation, non-native plants, and their interactions on seedling and adult survival. Only 7 A. californica were confirmed as resprouts; almost all individuals established after the fire from seedlings, with 90% of emergence occurring in the second growing year after fire (spring 2015). Higher spring precipitation increased both adult and seedling survival. Non-native grasses and forbs rapidly recolonized control plots, but the removal treatment reduced non-native cover by nearly 60%. For seedlings, non-native removal reduced the probability of dropping leaves by start of summer drought and increased survival both directly and through positive interactions with rainfall. Non-native removal also reduced mortality in smaller adult plants. By 2020, mean A. californica canopy area was nearly four times greater in non-native removal plots. These findings reinforce the high vulnerability of sage scrub habitat to post-fire loss of shrub cover and potential type conversion, particularly with increasing drought frequency and in stands and species with limited crown resprouting. Yet they also illustrate the potential for targeted management of non-natives immediately after fire to promote recovery of native shrubs in this increasingly endangered community.

Distributed Event Triggering Algorithm for Multi-Agent System over a Packet Dropping Network.

The availability of wireless networked control systems (WNCSs) has increased the interest in controlling multi-agent systems. Multiple feedback loops are closed over a shared communication network in such systems. An event triggering algorithm can significantly reduce network usage compared to the time triggering algorithm in WNCSs, however, the control performance is insecure in an industrial environment with a high probability of the packet dropping. This paper presents the design of a distributed event triggering algorithm in the state feedback controller for multi-agent systems, whose dynamics are subjected to the external interaction of other agents and under a random single packet drop scenario. Distributed event-based state estimation methods were applied in this work for designing a new event triggering algorithm for multi-agent systems while retaining satisfactory control performance, even in a high probability of packet drop condition. Simulation results for a multi-agent application show the main benefits and suitability of the proposed event triggering algorithm for multi-agent feedback control in WNCSs with packet drop imperfection.

Persistence of Underrepresented Minorities in STEM Fields: Are Summer Bridge Programs Sufficient?

Disparities in undergraduate STEM degree completion across different racial/ethnic groups have been a topic of increasing national concern. This study investigates the long-term outcomes of a STEM intervention program designed to increase the academic preparation, achievement and persistence of under-represented minority students.In particular, this study examines the extent to which participation in a STEM intervention program can impact the long-term persistence and graduation of first-time in college under-represented minority students. Using discrete-time competing risks analysis, results demonstrated that participants of the intervention program had a lower probability of drop out and higher probability of persisting in a STEM field of study compared to non-participants of the program. Additionally, descriptive results demonstrated that participants of the STEM intervention program had higher rates of graduation in any field compared to non-participants of the program, while program participation was not a significant predictor of six-year graduation. Findings highlight the importance of early academic preparation in Calculus and total credit accumulation to student success outcomes of URM students enrolled in STEM fields. Recommendations from this study focus on early intervention efforts, particularly in the areas of mathematics, that ensure URM students are adequately prepared with the skills needed to succeed in a STEM field of study.

Fractional squirrel–dolphin echolocation with deep belief network for network‐controlled vertical handoff in disparate and heterogeneous wireless network

SummaryThe innovative characteristics of different heterogeneous wireless networks provide better service. The disparate wireless access networks consist of wireless metropolitan access network (WMAN) and cellular networks. Various techniques are devised for dynamic network selection, but these techniques concentrated on attaining improved performance. To address this issue, a novel method is devised to improve the energy efficiency of disparate heterogeneous wireless networks. Here, the proposed fractional squirrel–dolphin echolocation (FrSqDE) algorithm is devised by integrating squirrel search optimization (SSA) and fractional dolphin echolocation (fractional DE) algorithm. In addition, the fitness function is considered with certain factors that include delay, bit error rate (BER), jitter, packet loss, energy consumption, probability of hot spot, average bit rate (ABR), and received signal strength (RSS). The proposed FrSqDE optimization algorithm is used for training deep belief networks (DBNs) to select optimal weights. Here, the network selection factors are given as input to the proposed FrSqDE‐based DBN, wherein optimal decision is made to handle vertical handoff. The proposed FrSqDE‐based DBN offered improved performance with a minimal call drop probability of 0.050, minimal delay of 0.013 s, minimal energy consumption of 0.393 J, and maximal throughput of 117.972 kbps.

Design and implementation of a novel two-phase spectrum handoff scheme for QoS aware mobile users in cognitive radio networks

Quality of Service (QoS) aware spectrum handoff operation is critical for Secondary Users (SUs) executing real-time applications like Voice over IP (VoIP) in Cognitive Radio Networks (CRNs). The problem is aggravated by the inclusion of occasionally mobile SUs where pre-selected target channels are often rendered insignificant during handoff under dynamic conditions. Conventional proactive and reactive schemes may underperform due to channel obsolescence issues and unacceptable handoff latency respectively while a combined approach is not yet explored under the constraints of practical applicability. In view of these challenges and enormous significance of VoIP based CRN in 5G networks, this paper proposes a practically feasible two-phase spectrum handoff methodology with I_Phase and S_Phase operating under alternate conditions. I_Phase deploys a three-level dropping decision scheme followed by a two-tier spectrum handoff policy and is motivated by an integrated approach spanning every CR operation. S_Phase incorporates user mobility and application-oriented aspects where channel drop is governed by a joint two-order Hidden Markov Model — custom Damerau–Levenshtein distance metric based policy and spectrum handoff is monitored by a novel non-cooperative TOPSIS method. These phases are assisted by two proposed prerequisite techniques namely ACT (Adaptive Call Transmission) involving CR timing parameters and VER (VoIP Early Resumption) dealing with early call resumption. Comparative analysis of QoS metrics including per-instance handoff latency, transmission duration per target channel, channel drop and call drop probabilities, etc. in analytical and simulation platforms record significant performance improvement. Novelty of this work further relies on design and execution of SU prototype with the proposed scheme in test-bed that successfully provides QoS guarantees during spectrum handoff.

Joint Use of Guard Capacity and Multiconnectivity for Improved Session Continuity in Millimeter-Wave 5G NR Systems

The intermittent nature of millimeter wave (mmWave) links caused by human-body blockage is an intrinsic property of the 5G New Radio (NR) technology that may cause drops of sessions already accepted for service. To improve the session continuity, multiconnectivity and guard capacity mechanisms have been proposed recently. Multiconnectivity enables dynamic handover between multiple pre-established spatially-diverse links, while guard capacity reserves a fraction of radio resources for the already accepted sessions by ensuring that they will have sufficient provisions in case of link blockage. In this study, we combine the tools of queuing theory and stochastic geometry to develop a mathematical framework for capturing the joint operation of these two schemes as well as the features of mmWave radio propagation. The metrics are related to user- and system-centric performance including the system resource utilization and the new and ongoing session drop probabilities. Our results show that multiconnectivity benefits all of the considered parameters. However, the range of performance boost remains limited by the deployment density and the maximum supported degree of multiconnectivity. In its turn, guard capacity allows to further decrease the ongoing session drop probability at the expense of the new session drop probability and the system resource utilization. When implemented jointly with multiconnectivity, guard capacity does not produce noticeable negative effects on the system resource utilization as compared to its standalone use. Hence, one may prefer a joint implementation of these mechanisms for preserving the session continuity of users without compromising the resource utilization.

Performance Analysis of Multi-Band Microwave and Millimeter-Wave Operation in 5G NR Systems

Blockage of millimeter-wave (mmWave) radio propagation paths in dense mobile scenarios requires advanced techniques to preserve session continuity in 5G New Radio (NR) systems. In this work, we employ the tools of stochastic geometry and queuing theory as well as rely on 3GPP cluster-based propagation modeling to formulate a mathematical framework, which captures session-level service dynamics of user equipment (UE) that supports multi-band operation. Accordingly, the sub-6 GHz NR base station (BS) is used to temporarily serve the sessions with strict throughput requirements that experience an outage at the mmWave NR BSs. We derive user- and system-centric key performance indicators, including new and ongoing session drop probabilities as well as radio resource utilization. Our numerical results confirm that the use of microwave BSs to serve mmWave sessions is only feasible in light traffic conditions. Particularly, the presence of throughput-hungry mmWave traffic increases the session drop probability at the sub-6 GHz band as well as decreases its utilization. Further, the support of sub-6 GHz radio may not improve the mmWave BS resource utilization, as many mmWave sessions are dropped during their service as a consequence of frequent blockage-induced outage situations.

Traffic Flow Characteristics and Lane Use Strategies for Connected and Automated Vehicles in Mixed Traffic Conditions

Managed lanes, such as a dedicated lane for connected and automated vehicles (CAVs), can provide not only technological accommodation but also desired market incentives for road users to adopt CAVs in the near future. In this paper, we investigate traffic flow characteristics with two configurations of the managed lane across different market penetration rates and quantify the benefits from the perspectives of lane-level headway distribution, fuel consumption, communication density, and overall network performance. The results highlight the benefits of implementing managed lane strategies for CAVs: (1) A dedicated CAV lane significantly extends the stable region of the speed-flow diagram and yields a greater road capacity. As the result shows, the highest flow rate is 3400 vehicles per hour per lane at 90% market penetration rate with one CAV lane. (2) The concentration of CAVs in one lane results in a narrower headway distribution (with smaller standard deviation) even with partial market penetration. (3) A dedicated CAV lane is also able to eliminate duel-bell-shape distribution that is caused by the heterogeneous traffic flow. (4) A dedicated CAV lane creates a more consistent CAV density, which facilitates communication activity and decreases the probability of packet dropping.

Optimal intervention strategies of staged progression HIV infections through an age-structured model with probabilities of ART drop out

In this paper, we construct a model to describe the transmission of HIV in a homogeneous host population. By considering the specific mechanism of HIV, we derive a model structured in three successive stages: (i) primary infection, (ii) long phase of latency without symptoms, and (iii) AIDS. Each HIV stage is stratified by the duration for which individuals have been in the stage, leading to a continuous age-structure model. In the first part of the paper, we provide a global analysis of the model depending upon the basic reproduction number ℜ0. When ℜ0 ≤ 1, then the disease-free equilibrium is globally asymptotically stable and the infection is cleared in the host population. On the contrary, if ℜ0 > 1, we prove the epidemic’s persistence with the asymptotic stability of the endemic equilibrium. By performing the sensitivity analysis, we then determine the impact of control-related parameters on the outbreak severity. For the second part, the initial model is extended with intervention methods. By taking into account antiretroviral therapy (ART) interventions and the probability of treatment drop out, we discuss optimal intervention methods which minimize the number of AIDS cases.

Two Different Exits: Prediction and Performance of Stocks that are About to Stop Trading

Mergers and drops are two of the most common reasons for firms to stop trading in the market. Both tend to be younger than the average and more likely to be growth stocks. Their past returns are very different -- firms that are about to drop have negative and volatile returns, while firms that merge have had high returns of lower-than-average volatility. Using a standard logit hazard model, we predict drops and mergers at short horizons and calculate predicted probabilities of these events. Portfolios of firms that are about to merge have positive Fama and French 3-factor and 5-factor alphas, though this is partly driven by positive momentum. Firms that have a high probability of dropping have negative alphas that are close to -2\% to -3\% per month. Results are robust to predicting returns using Fama and MacBeth regressions.

A Self-Tuning Congestion Tracking Control for TCP/AQM Network for Single and Multiple Bottleneck Topology

In this work a self-tuning rate and queue based proportional and integral controller called SRQ-PI is proposed to efficiently control the queue length with small overshoot and faster settling time. SRQ-PI proposes a new control tracking function that maps level of congestion to the packet drop probability dynamically. In SRQ-PI, the incoming traffic rate is estimated and used with the proportional and integral controller. The SRQ-PI tunes itself and stabilizes the system with internal feedback without requiring any external feedback. Furthermore, the stability of the SRQ-PI is analyzed using control theory and presents systematic guidelines to select the control gain parameters. NS2 is used to carry out the simulation work. The simulation result demonstrates that SRQ-PI is stable and gets faster transient response due to lower average delay jitter and robust against dynamic network parameters. The SRQ-PI outperforms proportional integral (PI), Intelligent adaptive PI (IAPI) and Random exponential marking (REM) algorithm.

A Flexible Handoff Prioritization Scheme for Improved Quality of Service in Mobile Networks

Efficient handoff prioritization schemes make mobile networks to perform better. However, most existing schemes have the common characteristics of reducing the call drop probability and increasing the call block probability; this decreases the general network performance. The reservation of channels for the use of handoff calls alone has not proved to be an efficient approach to optimally utilize the network limited channel resources. These approaches are such that even when the reserved channels are not in use, new calls could still get blocked if there are no channels among the shared channels to allocate to the new calls. In trying to maintain an improved QoS for handoff calls while ensuring an acceptable QoS for new calls, different methods have been suggested for new calls to access and use the reserved channels while priority is still given to handoff calls since it is more frustrating to have an on-going call dropped than blocking a new call. Network parameters such as call drop probability and traffic intensity had been used separately to determine when new calls could be granted access to use the reserved channels or otherwise. Handoff queuing and other call admission control approaches have also been used. This paper proposes the use of traffic intensity and call drop probability to decide whether the new calls could use the reserved channels or not. Also proposed is the need to keep the number of reserved channels fixed rather than calculating the numbers to reserve per time therefore reducing the computational complexity of the scheme. The simulation results showed an improved QoS for the handoff calls while producing a commensurate improvement for the new calls through a reduced Call drop Probability and call block probability. Keywords: Call block probability, Call drop probability, traffic intensity, handoff prioritization, mobile network DOI: 10.7176/JIEA/11-1-03 Publication date: January 31 st 2021

An Analytical Model for a Sectored Cellular Network with Embedded Small Cells

In order to handle the huge amounts of data transmitted through hot spots and to increase cell coverage in buildings, this paper proposes a sectored cellular network with small cells (SCNSC) embedded in each sector. Two region types, sectors and variable-radius small cells are classified in an SCNSC macro cell. Because the system capacity is enhanced by using fractional frequency reuse (FFR), the overall channel bandwidth is divided into two or three frequency bands depending on whether the number of sectors in a macro cell is even or odd. For the purpose of topological evaluation on the proposed SCNSC, we build an analytical model using Markov chain theory. The performance measures include new-call blocking and handoff-call dropping probabilities, average waiting times, and normalized throughputs in each sector and its embedded small cell by varying mobile stations’ moving speeds, the number of sectors, and the radius size of an embedded small cell. From the evaluation results, it is demonstrated that adjusting either the number of sectors or the coverage of an embedded cell can satisfy different service demands.

Stochastic Optimization of URLLC-eMBB Joint Scheduling With Queuing Mechanism

This letter proposes a dynamic joint scheduling for the ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) traffic at a sub-frame level with a queuing mechanism, which monitors and controls the latency of each URLLC packet in real time to ensure its strict requirements. We analytically derive the outage probability (i.e., the probability of any URLLC packet drop over all transmission channels) and URLLC expected throughput in addition to the expected value of served URLLC packets. Then, a stochastic optimization problem is formulated to maximize the total throughput for the eMBB services, constraining the URLLC outage probability. Numerical results confirm effectiveness of our queuing policy to significantly reduce the URLLC loss rate while ensuring that the total eMBB throughput is not affected.

Performance Analysis of Multimedia Communications Hard Handoff over Fading Channel (Dept.E)

Handoff is an essential element of cellular communication systems. Efficient handoff algorithms can be considered as a cost-effective way of enhancing the capacity and the quality of service (QoS) of cellular systems. In this paper, the performance of no priority schemes and first- in- first -out (FIFO) handoff queuing schemes are considered. The performance of signal power multimedia communications (SPMC) is studied for multimedia communications queuing over a shadow and ricean fading channel. Computer simulations are performed to calculate the probability of new call blocking (Pb) and probability of handoff dropping (Pd) using different types of handoff strategies. Results indicate that the developed scheme reduce the probability of multimedia handoff call dropping as compared to no priority schemes with 18% in case of no fading, while it provides about 8% - 18% improvement in case of shadow fading channel, and it provides about 4% -14% improvement in case of ricean fading channel.

A novel solution for real time video and path quality, and latency minimization: tele-training in surgical education

Surgical Tele-training has not been effectively implemented in telemedicine because of strict requirements for throughput and delay minimization during real-time high-quality video transmission. Therefore, the aim of this paper is to propose a new solution for surgical Tele-training with improved quality of real-time surgical video’s transmission, through put and minimized end-to-end delay required during the training session. The proposed system consists of an Enhanced Path Quality, Video Quality, and Latency Minimization (EPQVQaLM) algorithm to reduce network latency and improve the quality of real-time video transmission by including predicted data delivery time and packet drop probability in path quality calculation. The system also consists of cloud-based online video transcoding for economic transcoding of large-volume videos while guarantying the QoS parameter in case of additional resource requirement. The result shows that EPQVQaLM achieves improvements in PSNR by an average of 5db over the state of art solution. Furthermore, the proposed solution can reduce the processing time and end-to-end delay by an average of 32.6 ms and 33.93 ms over the state of art solution respectively. The proposed system concentrates on reducing end-to-end transmission delay and improves quality of surgical video transmission by using an EPQVQaLM technique. Meanwhile, it provides the mechanism for dropping the packets and re-routing packets to the different path before congestion becomes critical. Thus, this study provides an efficient mechanism to intelligently distribute data chunks over multiple paths.

Connectivity Performance Evaluation for Grant-Free Narrowband IoT With Widely Linear Receivers

Future wireless cellular communication networks are expected to provide connectivity for massive machine-type communication (mMTC) devices. The main challenge of supporting mMTC traffic for a cellular network lies in the high density of these devices, which individually have relatively little data to transmit. This suggests the use of low overhead, grant-free access scheme for uplink data transmission, which, however, suffers from packet collisions when devices attempt to access the channel. In this article, we suggest the use of real-valued transmission together with widely linear (WL) reception for improving resource access and thus data throughput in the uplink of mMTC traffic scenarios. We show that not surprisingly, the WL scheme can virtually double the number of receive antennas at the base station (BS). We analyze the effect of this on the supported user density and data throughput for grant-free uplink transmission. As a specific example, we consider the narrowband Internet-of-Things (NB-IoT) cellular communication system, which already includes real-valued modulation modes. Our numerical results show that the supported user density and data throughput of grant-free NB-IoT systems can be significantly improved due to the use of WL receivers. For example, considering an NB-IoT system with 1% packet drop probability, we obtain a tenfold (for single-antenna BS) and a sixfold (for dual-antenna BS) increase in the supported user density by using WL receivers instead of their conventional linear counterparts.

Explaining Student Retention: The Case of the University of Aberdeen

Student retention has risen high on the political agenda in the UK as part of the government's priorities to widen participation in higher education, in particular among groups traditionally under-represented in the sector. These concerns have been reflected in policies of the funding bodies in the UK. In turn Universities across the UK have become increasingly active in developing processes and procedures to meet the challenges of improving student retention while simultaneously widening access and participation in the context of rising student numbers overall. This has led to the desire for accurate data and reliable statistical analysis on which to inform policy the University of Aberdeen. The purpose of this report is to answer the question: what extent can the probability of drop out of a student be explained by student characteristics? Are mature students more likely to drop out? Is there an empirical distinction between younger and older mature students? Are male students more prone to dropping out? To what extent can the level of entry qualifications explain dropouts? Are there any differences in the impact of below core entry qualifications between male and female students? Do students who performed unsatisfactorily in their first year and who were allowed to repeat this first year drop out less or more often than other students? Have there been any significant trends over time? It is clear that any associations of these characteristics with drop out rates may have important policy implications for the University as it may allow the identification of those potentially at risk before they join the University and hence facilitate the targeting of support once students start their studies.

Attention fluctuations impact ongoing maintenance of information in working memory.

Working memory maintains information in a readily accessible state and has been shown to degrade as the length of the retention interval increases. Previous research has suggested that this decline is attributable to changes in precision as well as sudden loss of item representations. Here, by measuring trial-to-trial variations in performance, we examined an orthogonal distinction between the maximum number of items that an individual can store, and the probability of achieving that maximum. Across two experiments, we replicated the finding that performance declines after long (10 s) retention intervals, as well as past observations that forgetting was due to probabilistic dropping of individual items rather than all-or-none losses of the stored memories. Critically, longer retention intervals did not reduce the maximum amount of information that could be stored in working memory. Instead, lower attentional control accounted for a decreased probability of maintaining the maximum number of items in working memory. Thus, longer retention intervals impact working memory storage via fluctuations in attentional control that lower the probability of achieving a stable maximum storage capacity.