Delay Factor Analysis for Indian HAM Highway Construction Projects

Government has approved the hybrid annuity model (HAM) for building National Highways (NH) to speed up the construction of roads in the country by renewing interest of private developers in highway projects. 40% the Project Cost is to be provided by the Government as Construction Support during the construction period and the balance 60% as annuity payments over the operations period along with interest thereon to the concessionaire. Execution of hybrid annuity model (HAM) projects, which is the preferred mode of awarding by the National Highways Authority of India (NHAI), is largely on schedule with about 60% of projects, covering 3,200 km of roads, completed on time. The rest of the projects, however, are delayed largely due to various reasons. In order to identify and analysis of delay causes in highway projects of HAM model, this study provides a questionnaire survey-based study. Land acquisition delay is found as the most severe delay cause of highway projects of HAM model. Waste of time in controlling the traffic is found as the least severe delay cause of highway projects of HAM model. The study is supposed as useful to HAM construction managers for delay analysis of highway projects. Keywords: Hybrid annuity model, Highway projects, Delay analysis, Questionnaire survey.

Synchronized Information Acquisition Method for Virtual Geographic Scene Image Synthesis in Cities Based on Wireless Network Technology

At present, in the process of image synthesis information acquisition of urban virtual geographic scene, there is information complexity. The existing acquisition technology is easy to disturb in the process of information positioning and transmission, resulting in large acquisition delay and affecting the final synthesis quality of the image. In response to the above problems, the method of synchronous information acquisition for urban virtual geographic scene image synthesis based on wireless network technology is studied. Based on the construction of an urban virtual geographic environment, the spatial localization of the sign target of geographic scene image synthesis is carried out, and the optical flow method is used to register the urban geographic scene images. Based on the greedy algorithm of the beacon to design the synchronous wireless network route for urban virtual scene image synthesis, and after the grid division of the wireless network in the synthesis information acquisition area, the packets of each acquisition node are acquired and transmitted according to the designed wireless network route to realize the synchronous acquisition of image synthesis information. The comparison experimental data show that the acquisition delay of the studied information synchronization acquisition method is less than 0.5 s, the acquisition synchronization rate is significantly improved, and the quality of the synthesized images is better by applying the information acquired by the method, and the practical use is better.

DMAS Beamforming with Complementary Subset Transmit for Ultrasound Coherence-Based Power Doppler Detection in Multi-Angle Plane-Wave Imaging

Conventional ultrasonic coherent plane-wave (PW) compounding corresponds to Delay-and-Sum (DAS) beamforming of low-resolution images from distinct PW transmit angles. Nonetheless, the trade-off between the level of clutter artifacts and the number of PW transmit angle may compromise the image quality in ultrafast acquisition. Delay-Multiply-and-Sum (DMAS) beamforming in the dimension of PW transmit angle is capable of suppressing clutter interference and is readily compatible with the conventional method. In DMAS, a tunable p value is used to modulate the signal coherence estimated from the low-resolution images to produce the final high-resolution output and does not require huge memory allocation to record all the received channel data in multi-angle PW imaging. In this study, DMAS beamforming is used to construct a novel coherence-based power Doppler detection together with the complementary subset transmit (CST) technique to further reduce the noise level. For p = 2.0 as an example, simulation results indicate that the DMAS beamforming alone can improve the Doppler SNR by 8.2 dB compared to DAS counterpart. Another 6-dB increase in Doppler SNR can be further obtained when the CST technique is combined with DMAS beamforming with sufficient ensemble averaging. The CST technique can also be performed with DAS beamforming, though the improvement in Doppler SNR and CNR is relatively minor. Experimental results also agree with the simulations. Nonetheless, since the DMAS beamforming involves multiplicative operation, clutter filtering in the ensemble direction has to be performed on the low-resolution images before DMAS to remove the stationary tissue without coupling from the flow signal.

Scientific Workflow Makespan Minimization In Edge Multiple Service Providers Environment

The edge computing model offers an ultimate platform to support scientific and real-time workflow-based applications over the edge of the network. However, scientific workflow scheduling and execution still facing challenges such as response time management and latency time. This leads to deal with the acquisition delay of servers, deployed at the edge of a network and reduces the overall completion time of workflow. Previous studies show that existing scheduling methods consider the static performance of the server and ignore the impact of resource acquisition delay when scheduling workflow tasks. Our proposed method presented a meta-heuristic algorithm to schedule the scientific workflow and minimize the overall completion time by properly managing the acquisition and transmission delays. We carry out extensive experiments and evaluations based on commercial clouds and various scientific workflow templates. The proposed method has approximately 7.7% better performance than the baseline algorithms, particularly in overall deadline constraint that gives a success rate.

Educazione linguistica e disturbi della comunicazione in bambini di origine bangladese Uno studio di caso e alcune implicazioni glottodidattiche

In this paper I present a case study conducted between October 2018 and October 2019 involving Bengali children aged 4 to 6 with migration background who live in Venice. These children may have special educational needs, communication disorders or language acquisition delay because they neither speak Italian L2 fluently at school nor Bengali, their L1, at home. On the basis of neuropsychiatrists’ hypotheses, I investigate the quality and type of language input they receive at home and in different social contexts, as well as the external factors that can impact acquisition of both the L1 and L2.

Failure of Operational PPP Projects in India Leading to Private Developer’s Apathy to Participate in Future Projects: A Case Study Based Analysis

The goal of this study is to examine the failure of operational public-private partnership (PPP) infrastructure projects in India. The case study based analysis is done of eleven operational PPP projects from infrastructure subsectors like roads, metro rail, seaports, and power projects to investigate various risks faced during the life cycle of projects. The construction risks like land acquisition delay, change in scope, delay in financial closure resulting in time and cost overrun, revenue risk of not getting adequate revenue during operation phase and legal disputes between the authority and the concessionaire are prominent risks observed in these projects. Mitigating these risks through efficient life cycle contract management and appropriate allocation of risk creates adequate risk-adjusted financial returns to the private developers and value for money for the government. The study concludes that failure in contract and risk management in case of the majority of operational projects resulting in disappointing financial returns is the major reason for the private developer's apathy towards participation in a once successful PPP program in India.

Digimesh-Based Design of a Wireless Monitoring Network for Environmental Factors Affecting Granary System

The monitoring of granaries were earlier implemented with wired networks in most Asia countries with obvious challenges that include high installation and maintenance costs, data acquisition delay, and high energy consumption. Most other works being implemented with wireless approaches presented inherent drawbacks that include inefficient coverage of the grain storage bins and high rate of node failure. This paper presents the design and tremendous advantages of deploying distributed wireless sensor network based on Digimesh network protocol, to monitor the environmental temperature, humidity and illumination of a granary system. The monitoring system has only one node type, and consists of a homogenous network in which all nodes route data and they are interchangeable. A node consists of Xbee transceiver modules, Arduino microcontroller and DHT22 Temperature/Humidity sensor, and it is being configured as low battery powered devices. The results were logged real-time on a personal computer for analysis, display and record. The results indicate a system which provides a better sleeping scheme and eliminate the single point of failure associated with Zigbee and some other network protocols.

An IoT-based task scheduling optimization scheme considering the deadline and cost-aware scientific workflow for cloud computing

Large-scale applications of Internet of things (IoT), which require considerable computing tasks and storage resources, are increasingly deployed in cloud environments. Compared with the traditional computing model, characteristics of the cloud such as pay-as-you-go, unlimited expansion, and dynamic acquisition represent different conveniences for these applications using the IoT architecture. One of the major challenges is to satisfy the quality of service requirements while assigning resources to tasks. In this paper, we propose a deadline and cost-aware scheduling algorithm that minimizes the execution cost of a workflow under deadline constraints in the infrastructure as a service (IaaS) model. Considering the virtual machine (VM) performance variation and acquisition delay, we first divide tasks into different levels according to the topological structure so that no dependency exists between tasks at the same level. Three strings are used to code the genes in the proposed algorithm to better reflect the heterogeneous and resilient characteristics of cloud environments. Then, HEFT is used to generate individuals with the minimum completion time and cost. Novel schemes are developed for crossover and mutation to increase the diversity of the solutions. Based on this process, a task scheduling method that considers cost and deadlines is proposed. Experiments on workflows that simulate the structured tasks of the IoT demonstrate that our algorithm achieves a high success rate and performs well compared to state-of-the-art algorithms.