scholarly journals Impact Evaluation of Bike-Sharing on Bicycling Accessibility

2020 ◽  
Vol 12 (15) ◽  
pp. 6124 ◽  
Author(s):  
Mingzhu Song ◽  
Kaiping Wang ◽  
Yi Zhang ◽  
Meng Li ◽  
He Qi ◽  
...  
Keyword(s):  
Significant Influence ◽  
Real World ◽  
Transportation Planning ◽  
Impact Evaluation ◽  
Critical Aspect ◽  
Location Data ◽  
Bike Sharing ◽  
The Impact ◽  
Better Than

The presence of bike-sharing has a significant influence on the ease of trips by bike, which is one critical aspect of bicycling accessibility (BAcc). The existing measurements of BAcc rarely consider the factor of ownership of bikes, which means that no distinction is made between private-bikes and shared bikes. To measure BAcc more fully, this paper proposes a method to evaluate the influences of bike-sharing on BAcc and to perform the method on a real-world case study in Beijing. It is found that bike-sharing has a boosting effect on BAcc, and the increased rate of BAcc is significantly affected by bicycling frequency and shared-bike availability. A case study in Beijing utilizing geo-location data collected from two major bike-sharing companies (OFO and Mo-bike) illustrates the significance of the impact of bike-sharing on BAcc and the necessity to include bike-sharing in the measurement of BAcc. Besides, the case study shows BAcc around the transit station is better than that over the whole area. Given that bicycling feeds transit, this research lays the foundation for analyzing the combination of bike-sharing and transit from the perspective of accessibility and can further support transportation planning.

scholarly journals Results from a Psychology OER pilot program: faculty and student perceptions, cost savings, and academic outcomes

Open Praxis ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 83
Author(s):  
Juliana Magro ◽  
Sara V Tabaei
Keyword(s):  
Student Perceptions ◽  
Academic Outcomes ◽  
Cost Savings ◽  
Open Educational Resources ◽  
Pilot Program ◽  
Open Textbooks ◽  
The Impact ◽  
Pedagogical Changes ◽  
Better Than

This case study describes the library’s experience of collaborating with an undergraduate Psychology Department at Touro College to integrate open textbooks into their program. We discuss the pedagogical changes as well as explore the impact of Open Educational Resources (OER) on students’ savings, their academic outcomes and perceptions of OER. Furthermore, we highlight the successes and shortcomings in having the library as a central OER partner. To measure the results, we surveyed students and conducted a faculty survey and a focus group, in addition to analyzing the students’ final grades. This pilot program delivered strong results. The students’ perception was very positive, and faculty’s opinions on the textbooks used were mixed. Some professors felt that the textbook lacked important content, but because of its openness, they added their own content to the book. Students enrolled in OER courses performed better than those enrolled in the same courses using a commercial textbook.

A Procedure for Collecting and Labeling Man-in-the-Middle Attack Traffic

2017 ◽  
Vol 24 (01) ◽  
pp. 1750002 ◽  
Author(s):  
Chad Calvert ◽  
Taghi M. Khoshgoftaar ◽  
Maryam M. Najafabadi ◽  
Clifford Kemp
Keyword(s):  
Real World ◽  
Production Environment ◽  
Representative Data ◽  
Man In The Middle ◽  
Scale Network ◽  
The Impact ◽  
Traffic Behavior ◽  
Gain Access ◽  
Mitm Attack

In this work, we outline a procedure for collecting and labeling Man-in-the-Middle (MITM) attack traffic. Our capture procedure allows for the collection of real-world representative data using a full-scale network environment. MITM attacks are typically performed with the purpose of intercepting information amongst two networked machines. This enables the attacker to gain access to otherwise confidential communications and potentially alter said communications maliciously. MITM attacks are still a very common attack that can be implemented with relative ease across a variety of network environments. Our work establishes experimental procedures for enacting three prevalent MITM attack variants through penetration testing. The process for data collection is defined, along with our approach on gathering real-world, representative data. We also present a novel labeling procedure based on the inherent behaviors of each MITM attack variant. Our work aims to address the challenges associated with collecting such data within a live production environment, as well as identify the impact MITM attacks have on traffic behavior. We also present a case study to provide some quantitative analysis regarding the data collected.

scholarly journals Comparing Impact Evaluation Evidence of EU and Local Development Policies with New Urban Agenda Themes: The Agri Valley Case in Basilicata (Italy)

2021 ◽  
Vol 13 (16) ◽  
pp. 9376
Author(s):  
Piergiuseppe Pontrandolfi ◽  
Priscilla Sofia Dastoli
Keyword(s):  
Impact Evaluation ◽  
Local Development ◽  
Methodological Approach ◽  
National Level ◽  
Open Data ◽  
Use Of Resources ◽  
Italian Regions ◽  
The Impact ◽  
New Urban Agenda

The European Union’s Cohesion Policy is the most important structural policy in terms of financial commitment, geographical size and time frame, aimed at redistributing wealth between regions and countries, to stimulate growth in areas whose development is lagging behind. The reach of the investments prompted the EU Commission to promote an impact evaluation of the European Structural Funds (SF); however, the impact evaluation of EU programs is almost neglected in the Italian regions. This paper is based on the results developed within the RI.P.R.O.VA.RE project and is aimed at defining an impact evaluation of EU SF and other regional funds, based on evidence derived from the analysis of a specific case study in the Agri Valley area (Basilicata, Italy). To develop the impact evaluation process, the euro amounts of all the individual policies organized according to the themes of the New Urban Agenda (NUA), the impact indicators and the trend for the municipalities are considered together, in order to obtain an overall trend for the entire case study area. An important result is achieved above all in the methodological approach to impact evaluation: the municipal territorial scale is taken into account; the maps illustrate the use of resources; regardless of the type of funding source since there is a comparison between the priority axes of the funds with the NUA issues; and indicators are developed with open data available at a national level. This experiment makes it possible to detect that, even in the face of significant investments, some substantial aspects that are part of the policy objectives remain unchanged or even worsen.

scholarly journals Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study

2021 ◽  
Author(s):  
Sheng Liu ◽  
Zuo-Jun Max Shen ◽  
Xiang Ji
Keyword(s):  
Real World ◽  
Smart City ◽  
Utility Functions ◽  
Mixed Integer ◽  
Planning Problem ◽  
Planning Model ◽  
Trajectory Data ◽  
Bike Sharing ◽  
Route Choices

Problem definition: We study an urban bike lane planning problem based on the fine-grained bike trajectory data, which are made available by smart city infrastructure, such as bike-sharing systems. The key decision is where to build bike lanes in the existing road network. Academic/practical relevance: As bike-sharing systems become widespread in the metropolitan areas over the world, bike lanes are being planned and constructed by many municipal governments to promote cycling and protect cyclists. Traditional bike lane planning approaches often rely on surveys and heuristics. We develop a general and novel optimization framework to guide the bike lane planning from bike trajectories. Methodology: We formalize the bike lane planning problem in view of the cyclists’ utility functions and derive an integer optimization model to maximize the utility. To capture cyclists’ route choices, we develop a bilevel program based on the Multinomial Logit model. Results: We derive structural properties about the base model and prove that the Lagrangian dual of the bike lane planning model is polynomial-time solvable. Furthermore, we reformulate the route-choice-based planning model as a mixed-integer linear program using a linear approximation scheme. We develop tractable formulations and efficient algorithms to solve the large-scale optimization problem. Managerial implications: Via a real-world case study with a city government, we demonstrate the efficiency of the proposed algorithms and quantify the trade-off between the coverage of bike trips and continuity of bike lanes. We show how the network topology evolves according to the utility functions and highlight the importance of understanding cyclists’ route choices. The proposed framework drives the data-driven urban-planning scheme in smart city operations management.

scholarly journals Economic Empowerment of Pesantren Through Agribusiness (Study On Al-Mawaddah Entrepreneurial Pesantren)

2020 ◽  
Vol 3 (1) ◽  
pp. 15-31
Author(s):  
Muhammad Baqi Mustaghfiri
Keyword(s):  
Agricultural Sector ◽  
Field Research ◽  
Strategy Research ◽  
Analysis Technique ◽  
Dragon Fruit ◽  
Qualitative Descriptive ◽  
Three Stages ◽  
The Impact ◽  
Better Than

This paper aims for several research objectives. It aims to find out the agribusiness sectors developed by Al-Mawaddah Entrepreneurial Pesantren. It also aims to find out the empowerment of agribusiness developed by this pesantren. Last, it also aims to determine the impact of empowering agribusiness developed on improving the economy Al-Mawaddah Entrepreneurial Pesantren’s alumni. This research is a field research. The approach used by researcher is a qualitative descriptive approach with a case study strategy. Research location is at Pesantren Entrepreneur Al-Mawaddah Honggosoco Kudus RT. 06/ RW. 01, Jekulo District, Kudus Regency. Data collection techniques used are observation, interviews, and documentation. The data analysis technique used is descriptive qualitative. The results show that: (1) the agribusiness sector that was developed at Al-Mawaddah Entrepreneurial Pesantren touched only agriculture and educational sectors. It yet touches other agribusiness sectors, such as fisheries or livestock. The agricultural sector developed includes: agricultural food crops, such as: rice, corn, soybeans, vegetables, and cassava, fruit crops, such as: longan, and dragon fruit. They even plant within the premise sugar cane plantation; (2) Agribusiness Empowerment developed by Al-Mawaddah Entrepreneurial Pesantren consists of three stages, namely: input, process, and output; (3) Agribusiness entrepreneurship is better than working under other people (companies) because apart from freedom, the income generated is also higher.

scholarly journals Impacts of sedimentation on rainwater quality: case study at Ikorodu of Lagos, Nigeria

2021 ◽  
Author(s):  
Chukwuemeka Kingsley John ◽  
Jaan H. Pu ◽  
Manish Pandey ◽  
Rodrigo Moruzzi
Keyword(s):  
Suspended Solids ◽  
Storage System ◽  
Total Suspended Solids ◽  
Phase Zone ◽  
E Coli ◽  
Different Depths ◽  
Rain Events ◽  
The Impact ◽  
Better Than

Abstract This study investigated the impact of sedimentation on rainwater storage system using a case study at the Ikorodu area of Lagos state, a rural area in Nigeria. In this investigation, the proportions of Escherichia coli (E. coli) that were settleable (due to sedimentation) and those that were at the free phase have been studied. Water samples were collected from different depths in the inspected rainwater storage tank at two different periods (i.e. rainy and dry periods) for 20 days. The samples collected from these periods have been analysed for physical and microbial measures before passing it through the serial filters with pore sizes of 500 μm, 100 μm, 10 μm and 1.5 μm to measure the retained particle mass. From the results, it was observed that: (1) the water quality at the free-phase zone was better than that at the tank's bottom; (2) the settleable bacteria rapidly sinked to bottom; (3) the correlation of turbidity, E. coli and total suspended solids (TSS) for all the rain events showed a relatively high Pearson's coefficient of 0.9 to one another; and (4) over 70% of settling TSS occurred within first 36 hours. Finally, it has been found that the physical sedimentation process can significantly reduce the microbial measures.

scholarly journals Getting the Perpetrator Incorporated and Prioritized in Homicide Investigations: The Development and Evaluation of a Case-Specific Element Library (C-SEL)

2020 ◽  
Vol 17 (17) ◽  
pp. 6430
Author(s):  
August Daniel Sutmuller ◽  
Marielle den Hengst ◽  
Ana Isabel Barros ◽  
Pieter van Gelder
Keyword(s):  
Real World ◽  
Criminal Investigation ◽  
Specific Element ◽  
Digital Era ◽  
Initial Score ◽  
Better Than

Homicide investigators in the digital era have access to an increasing amount of data and the processing of all persons of interest and pieces of evidence has become nearly impossible. This paper describes the development and evaluation of a case-specific element library (C-SEL) that can be used to incorporate and prioritize persons of interest in homicide investigations. In a survey, 107 experts in the field of criminal investigation assigned an initial score to the elements. Each element was extended with underlying factors that can be used to adjust the initial score based on the relevance and credibility of the source. A case study was conducted using three Dutch real-world cases to evaluate the methodology. The results look promising and are better than four methodologies currently used in practice.

scholarly journals Prediction of Real-World Drug Effectiveness Prelaunch: Case Study in Rheumatoid Arthritis

2018 ◽  
Vol 38 (6) ◽  
pp. 719-729 ◽  
Author(s):  
Eva-Maria Didden ◽  
Yann Ruffieux ◽  
Noemi Hummel ◽  
Orestis Efthimiou ◽  
Stephan Reichenbach ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Real World ◽  
Linear Models ◽  
Target Population ◽  
New Drugs ◽  
Simulated Patients ◽  
Drug Effectiveness ◽  
Conventional Dmards ◽  
The Impact

Background. Decision makers often need to assess the real-world effectiveness of new drugs prelaunch, when phase II/III randomized controlled trials (RCTs) but no other data are available. Objective. To develop a method to predict drug effectiveness prelaunch and to apply it in a case study in rheumatoid arthritis (RA). Methods. The approach 1) identifies a market-approved treatment ( S) currently used in a target population similar to that of the new drug ( N); 2) quantifies the impact of treatment, prognostic factors, and effect modifiers on clinical outcome; 3) determines the characteristics of patients likely to receive N in routine care; and 4) predicts treatment outcome in simulated patients with these characteristics. Sources of evidence include expert opinion, RCTs, and observational studies. The framework relies on generalized linear models. Results. The case study assessed the effectiveness of tocilizumab (TCZ), a biologic disease-modifying antirheumatic drug (DMARD), combined with conventional DMARDs, compared to conventional DMARDs alone. Rituximab (RTX) combined with conventional DMARDs was identified as treatment S. Individual participant data from 2 RCTs and 2 national registries were analyzed. The model predicted the 6-month changes in the Disease Activity Score 28 (DAS28) accurately: the mean change was -2.101 (standard deviation [SD] = 1.494) in the simulated patients receiving TCZ and conventional DMARDs compared to -1.873 (SD = 1.220) in retrospectively assessed observational data. It was -0.792 (SD = 1.499) in registry patients treated with conventional DMARDs. Conclusion. The approach performed well in the RA case study, but further work is required to better define its strengths and limitations.

scholarly journals Real-World Performance of Longitudinal Barriers Struck by Large Trucks

2012 ◽  
Vol 2309 (1) ◽  
pp. 127-134 ◽  
Author(s):  
Douglas J. Gabauer
Keyword(s):  
Real World ◽  
Reporting System ◽  
Penetration Rate ◽  
Heavy Vehicles ◽  
The Real ◽  
Impact Performance ◽  
Passenger Vehicles ◽  
Road Users ◽  
The Impact ◽  
Better Than

Very little is known about the real-world performance of traffic barriers when subjected to impacts by large trucks. This study investigated real-world impacts of large trucks into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of barriers specifically designed for large trucks. Data sources included the Fatality Analysis Reporting System (2000 to 2009), the General Estimates System (2000 to 2009), and the Large Truck Crash Causation Study (155 in-depth crashes of large trucks into barriers). Impacts of large trucks into longitudinal barriers constituted 3% of all police-reported impacts into longitudinal barriers and roughly the same proportion of barrier fatalities. A logistic regression model predicting barrier penetration showed that the risk of a large truck penetrating a barrier increased by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although barriers specifically designed for impacts by large trucks performed better than barriers not specifically designed for impacts by heavy vehicles, the penetration rate of the former was 17%. This penetration rate is of concern, because barriers used for higher test levels are designed to protect other road users, not the occupants of large trucks. Barriers not specifically designed for impacts by large trucks prevented penetration by a large truck approximately half the time. This finding suggests that adding costlier barriers that meet higher test levels may not always be warranted, especially on roadways with lower truck volumes.

scholarly journals An Input-aware Factorization Machine for Sparse Prediction

2019 ◽  
Author(s):  
Yantao Yu ◽  
Zhen Wang ◽  
Bo Yuan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real World ◽  
State Of The Art ◽  
Overall Performance ◽  
Factorization Machine ◽  
The Impact ◽  
Novel Model ◽  
Individual Input ◽  
Better Than

Factorization machines (FMs) are a class of general predictors working effectively with sparse data, which represents features using factorized parameters and weights. However, the accuracy of FMs can be adversely affected by the fixed representation trained for each feature, as the same feature is usually not equally predictive and useful in different instances. In fact, the inaccurate representation of features may even introduce noise and degrade the overall performance. In this work, we improve FMs by explicitly considering the impact of individual input upon the representation of features. We propose a novel model named \textit{Input-aware Factorization Machine} (IFM), which learns a unique input-aware factor for the same feature in different instances via a neural network. Comprehensive experiments on three real-world recommendation datasets are used to demonstrate the effectiveness and mechanism of IFM. Empirical results indicate that IFM is significantly better than the standard FM model and consistently outperforms four state-of-the-art deep learning based methods.

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