Development of a Model for International Traveler’s Check-In Process Using Arena Software Tool

The increasing demand for airline services amidst limited resources results in passenger dissatisfaction and dwindling revenue for airports and airlines. The dynamics of service demand and resource supply results in check-in issues for the stakeholders in the commercial aviation industry. This has the effect of impacting negatively on service performance, cost of operations, customer satisfaction, and overall throughput. Hence, this paper modelled the travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The work was carried out by determining the parameters of the queues at designated service points in the check-in process. The primary data required to develop the model were acquired by direct observation of passenger flow and oral interview. Thus, the average check-in time was determined. Thereafter, a model of the international check-in system of the MMIA was developed using Arena software in combination with Microsoft Office tools. The data collected were therefore inputted into the model and simulated;the real result was compared with the simulation result of 133 completions and there was no significant difference. The result showed that the model is a representation of the real system under study. Further work will be tailored towards simulation (i.e. the model will be subjected to experimentation in order to have different scenario).

Simulation of a Model for International Traveler’s Check-In Process Using Arena Software Tool

With the current situation of insecurity in Nigeria and the worsening condition of Nigerian roads, there is increasing demand for air travel. This increasing demand for airline services amidst limited resources results in passenger dissatisfaction and reduction of revenue for airports and airlines. The dynamics of service demand and resource supply result in check-in issues for all the stakeholders in the commercial aviation industry. Hence, this research simulated the developed model for travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The simulation of the developed model was carried out by varying five different configurations of the servers with respect to the baggage weighing machines and passenger profiling devices to obtain the minimum average check-in time (ACT) for the process, with each configuration undergoing 133 completions of simulation runs. The result of the experimentation revealed that the 3 × 3 × 4 configuration of servers produced the smallest ACT of 18.25 minutes. This translates to a difference of about 58 minutes from the 76.16 minutes ACT of the real system;representing about 76% improvement in the check-in time of passengers. This study contributed to knowledge by revealing that the main choke points in the MMIA check-in system occur at the baggage weighing and passenger profiling areas as against the check-in counter sub-section as advanced by previous works. Furthermore, the research added value to knowledge by creating a balance between customer satisfaction and cost of operations thereby accommodating the interests of the passenger and the operator who are the two main stakeholders in the commercial aviation industry.

Scheduling Check-in Staff with Hierarchical Skills and Weekly Rotation Shifts

The paper aims to schedule check-in staff with hierarchical skills as well as day and night shifts in weekly rotation.That shift ensures staff work at day in a week and at night for the next week.The existing approaches do not deal with the shift constraint.To address this,the proposed algorithm firstly guarantees the day and night shifts by designing a data copy tactic,and then introduces two algorithms to generate staff assignment in a polynomial time.The first algorithm is to yield an initial solution efficiently,whereas the second incrementally updates that solution to cut off working hours.The key idea of the two algorithms is to utilize a block Gibbs sampling with replacement to simultaneously exchange multiple staff assignment.Experimental results indicate that the proposed algorithm reduces at least 15.6 total working hours than the baselines.

Latent spatio-temporal activity structures: a new approach to inferring intra-urban functional regions via social media check-in data

This article introduces a novel low rank approximation (LRA)-based model to detect the functional regions with the data from about 15 million social media check-in records during a year-long period in Shanghai, China. We identified a series of latent structures, named latent spatio-temporal activity structures. While interpreting these structures, we can obtain a series of underlying associations between the spatial and temporal activity patterns. Moreover, we can not only reproduce the observed data with a lower dimensional representative, but also project spatio-temporal activity patterns in the same coordinate system. With the K-means clustering algorithm, five significant types of clusters that are directly annotated with a combination of temporal activities can be obtained, providing a clear picture of the correlation between the groups of regions and different activities at different times during a day. Besides the commercial and transportation dominant areas, we also detected two kinds of residential areas, the developed residential areas and the developing residential areas.We further interpret the spatial distribution of these clusters using urban form analytics. The results are highly consistent with the government planning in the same periods, indicating that our model is applicable to infer the functional regions from social media check-in data and can benefit a wide range of fields, such as urban planning, public services, and location-based recommender systems.

Joint model of user check-in activities for point-of-interest recommendation

With the rapid development of location-based networks, point-of-interest（POI） recommendation has become an important means to help people discover interesting and attractive locations, especially when users travel out of town. However, because users only check-in interaction is highly sparse, which creates a big challenge for POI recommendation. To tackle this challenge, we propose a joint probabilistic generative model called geographical temporal social content popularity（GTSCP） to imitate user check-in activities in a process of decision making, which effectively integrates the geographical influence, temporal effect, social correlation, content information and popularity impact factors to overcome the data sparsity, especially for out-of-town users. Our proposed the GTSCP supports two recommendation scenarios in a joint model, i.e., home-town recommendation and out-of-town recommendation. Experimental results show that GTSCP achieves significantly superior recommendation quality compared to other state-of-the-art POI recommendation techniques.

乘机别忘Check-in

随着生活水平的提高,出国旅行成为越来越多中国家庭假期的假日选择。出国旅行的主要交通工具就是飞机。小朋友们跟随父母亲在国外乘机,了解一些国外机场常用的英语表达是非常有帮助的。今天我们就来讲讲在国外机场乘机最重要的环节:check-in。在机场,这个词可以理解为'办理登机手续'。

基于位置签到数据的城市分层地标提取

为了及时准确地获取用于智慧位置服务的城市层次性空间知识,该文提出了一种依据签到属性显著度的差异从位置签到数据中提取城市分层地标的方法.首先,针对传统基于调查问卷的公众认知度计算方法存在的不足,该文从位置签到数据中的签到次数、签到用户数和用户影响因子3个方面入手讨论POI显著度的影响因素,进而提出了一种基于签到数据的POI显著度计算模型;然后,利用Voronoi图对POI空间作用范围进行分割并结合邻域分析与合并算法逐层迭代,形成了基于签到POI显著度与Voronoi图的分层地标提取算法;最后,以北京市的位置签到数据为例,进行了POI显著度计算与分时分层地标提取,通过与现有实体、网络地图资料的比对,验证了算法的有效性,并进一步分析了分层、分时地标反映的空间现象和规律,为个性化智慧位置服务提供城市层次性空间知识.

使用Dreamweaver4协同开发Web站点

Dreamweaver的最新版本 4 .0集网页的设计制作和站点的创建管理功能于一身 ,本文就解决协同工作的问题 ,给出利用”CheckIn”和”CheckOut”

Hotel Guest Service Technology

For any hotel guest reception technology is an important factor in the quality service process,financial-economic efficiency,and management of the hotel industry.The service process in the same type hotel is standard,meanwhile the service process technology undergoes certain alterations according to the hotel’s size,structure,category,and market segment orientation.Hotel customer service technology is characterized by cycling phases—consistent repeat of the service process before the departure of the guest from the hotel.The article discusses the four-phase cycle of guest reception,related to the hotel services and transactions.Each phase of the cycle consists of standard transactions/phases,which are carried out between hotel clients and the hotel itself.

基于兴趣点的城市阻抗计算模型

为实现城市阻抗的实时计算,提出一种基于社交网络兴趣点的城市阻抗计算模型.模型以城市路网划分地块为基本单位,综合考虑地块中心到兴趣点间的平均路网距离、转弯角度、转弯次数、交叉口以及人口等因素,计算城市地块在可达半径范围内的阻抗值.将提出的模型与效用模型、潜力模型以每2h作为时间段进行计算对比.结果表明:提出的阻抗模型与实际路况的相似度比效用模型、潜力模型分别高出80%与60%,有效提高了模型在城市阻抗计算上的适用性,反映出城市地块在不同时间段的阻抗变化.

基于虚拟仪器技术的自动控制系统综合检测系统的研制

介绍了针对某型飞机的自动控制系统综合检测系统的研究与设计,经过多次方案论证后该综合检测系统最终采用虚拟仪器技术研制开发,较好地结合了软硬件的特点,实现了某型飞机的检测设备国产化,为我国新型飞机的研制提供了新的思路和方法。主要介绍了虚拟仪器的开发平台,阐述了该系统的总体设计方案、体系结构、主要功能、模块划分及系统特点,讨论了软件实现中实时检测与多线程、A/D转换与数字滤波的关键问题及解决的技术方案。

钢领钢丝圈纺制高品质纱线的思考

为了用好钢领钢丝圈并纺制高品质纱线,提出管理+制度化的理念,从把好进厂关、纺纱使用关和客户关,以及优化自动络筒工序电清工艺、跟踪观察纱疵变化确定钢领钢丝圈使用周期和日常生产中钢丝圈的管理等方面,分析钢领钢丝圈选型配套和管理对高品质纱线质量和布面效果的影响。指出:应用钢领钢丝圈纺制高品质纱线,技术工艺是手段,管理才是保障;纺纱企业应加强制度化建设,确保钢领钢丝圈管理到位,并全面、系统进行精准布局、配套使用,以保证客户的满意度和实物质量。

Diversifying Top-κRoutes with Spatial Constraints

Trip recommendation has become increasingly popular with the rapid growth of check-in data in location-based social networks.Most existing studies focused only on the popularity of trips.In this paper,we consider further the usability of trip recommendation results through spatial diversification.We thereby formulate a new type of queries named spatial diversified top-κroutes(SDκR)query.This type of queries finds k trip routes with the highest popularity,each of which starts at a given starting point,consumes travel time within a given time budget,and passes through points of interest(POIs)of given categories.Any two trip routes returned are diversified to a certain degree defined by the spatial distance between the two routes.We show that the SDkR problem is NP-hard.We propose two precise algorithms to solve the problem.The first algorithm starts with identifying all candidate routes that satisfy the query constraints,and then searches for theκ-route combination with the highest popularity.The second algorithm identifies the candidate routes and builds up the optimalκ-route combination progressively at the same time.Further,we propose an approximate algorithm to obtain even higher query efficiency with precision bounds.We demonstrate the effectiveness and efficiency of the proposed algorithms on real datasets.Our experimental results show that our algorithms find popular routes with diversified POI locations.Our approximate algorithm saves up to 90%of query time compared with the baseline algorithms.

User Account Linkage Across Multiple Platforms with Location Data

Linking user accounts belonging to the same user across different platforms with location data has received significant attention,due to the popularization of GPS-enabled devices and the wide range of applications benefiting from user account linkage(e.g.,cross-platform user profiling and recommendation).Different from most existing studies which only focus on user account linkage across two platforms,we propose a novel model ULMP(i.e.,user account linkage across multiple platforms),with the goal of effectively and efficiently linking user accounts across multiple platforms with location data.Despite of the practical significance brought by successful user linkage across multiple platforms,this task is very challenging compared with the ones across two platforms.The major challenge lies in the fact that the number of user combinations shows an explosive growth with the increase of the number of platforms.To tackle the problem,a novel method GTkNN is first proposed to prune the search space by efficiently retrieving top-k candidate user accounts indexed with well-designed spatial and temporal index structures.Then,in the pruned space,a match score based on kernel density estimation combining both spatial and temporal information is designed to retrieve the linked user accounts.The extensive experiments conducted on four real-world datasets demonstrate the superiority of the proposed model ULMP in terms of both effectiveness and efficiency compared with the state-of-art methods.