Search results for: road user characteristics

Authors: Zuk Nechemia Turbovich

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This paper introduces DoD, a contextual spiral model that describes the lifecycle of products intended for manufacturing using Personal 3D Printers (P3DP). The study is based on a review of the desktop P3DPs market that shows that the combination of digital connectivity, coupled with the potential ownership of P3DP by home users, is radically changing the form of the product lifecycle, comparatively to familiar lifecycle paradigms. The paper presents the change in the design process, considering the characterization of product types in the P3DP market and the possibility of having a direct dialogue between end-user and product designers. The model, as an updated paradigm, provides a strategic perspective on product design and tools for success, understanding that design is subject to rapid and continuous improvement and that products are subject to repair, update, and customization. The paper will include a review of real cases.

Keywords: lifecycle, mass-customization, personal 3d-printing, user involvement

Procedia PDF Downloads 175

Authors: P. Intaracharoen, P. Chantraket, C. Detyothin, S. Kirtsaeng

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Radar reflectivity data from Phimai weather radar station of DRRAA (Department of Royal Rainmaking and Agricultural Aviation) were used to analyzed the rainstorm characteristics via Thunderstorm Identification Tracking Analysis and Nowcasting (TITAN) algorithm. The Phimai weather radar station was situated at Nakhon Ratchasima province, northeastern Thailand. The data from 277 days of rainstorm events occurring from May 2016 to May 2017 were used to investigate temporal distribution characteristics of convective individual rainclouds. The important storm properties, structures, and their behaviors were analyzed by 9 variables as storm number, storm duration, storm volume, storm area, storm top, storm base, storm speed, storm orientation, and maximum storm reflectivity. The rainstorm characteristics were also examined by separating the data into two periods as wet and dry season followed by an announcement of TMD (Thai Meteorological Department), under the influence of southwest monsoon (SWM) and northeast monsoon (NEM). According to the characteristics of rainstorm results, it can be seen that rainstorms during the SWM influence were found to be the most potential rainstorms over northeastern region of Thailand. The SWM rainstorms are larger number of the storm (404, 140 no./day), storm area (34.09, 26.79 km²) and storm volume (95.43, 66.97 km³) than NEM rainstorms, respectively. For the storm duration, the average individual storm duration during the SWM and NEM was found a minor difference in both periods (47.6, 48.38 min) and almost all storm duration in both periods were less than 3 hours. The storm velocity was not exceeding 15 km/hr (13.34 km/hr for SWM and 10.67 km/hr for NEM). For the rainstorm reflectivity, it was found a little difference between wet and dry season (43.08 dBz for SWM and 43.72 dBz for NEM). It assumed that rainstorms occurred in both seasons have same raindrop size.

Keywords: rainstorm characteristics, weather radar, TITAN, Northeastern Thailand

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Authors: Ruvaitha Banu, Amaladhithyan Krishnamoorthy

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IoT networks today solve various consumer problems, from home automation systems to aiding in driving autonomous vehicles with the exploration of multiple devices. For example, in an autonomous vehicle environment, multiple sensors are available on roads to monitor weather and road conditions and interact with each other to aid the vehicle in reaching its destination safely and timely. IoT systems are predominantly dependent on the cloud environment for data storage, and computing needs that result in latency problems. With the advent of Fog networks, some of this storage and computing is pushed to the edge/fog nodes, saving the network bandwidth and reducing the latency proportionally. Managing the data stored in these fog nodes becomes crucial as it might also store sensitive information required for a certain application. Data management in fog nodes is strenuous because Fog networks are dynamic in terms of their availability and hardware capability. It becomes more challenging when the nodes in the network also live a short span, detaching and joining frequently. When an end-user or Fog Node wants to access, read, or write data stored in another Fog Node, then a new protocol becomes necessary to access/manage the data stored in the fog devices as a conventional static way of managing the data doesn’t work in Fog Networks. The proposed solution discusses a protocol that acts by defining sensitivity levels for the data being written and read. Additionally, a distinct data distribution and replication model among the Fog nodes is established to decentralize the access mechanism. In this paper, the proposed model implements stewardship towards the data stored in the Fog node using the application of Reinforcement Learning so that access to the data is determined dynamically based on the requests.

Keywords: IoT, fog networks, data stewardship, dynamic access policy

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Authors: Inyoung Park, Youngjoo Woo, Euiseong Seo

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With the advent of WebGL, Web apps are now able to provide high quality graphics by utilizing the underlying graphic processing units (GPUs). Despite that the Web apps are becoming common and popular, the current power management schemes, which were devised for the conventional native applications, are suboptimal for Web apps because of the additional layer, the Web browser, between OS and application. The Web browser running on a CPU issues GL commands, which are for rendering images to be displayed by the Web app currently running, to the GPU and the GPU processes them. The size and number of issued GL commands determine the processing load of the GPU. While the GPU is processing the GL commands, CPU simultaneously executes the other compute intensive threads. The actual user experience will be determined by either CPU processing or GPU processing depending on which of the two is the more demanded resource. For example, when the GPU work queue is saturated by the outstanding commands, lowering the performance level of the CPU does not affect the user experience because it is already deteriorated by the retarded execution of GPU commands. Consequently, it would be desirable to lower CPU or GPU performance level to save energy when the other resource is saturated and becomes a bottleneck in the execution flow. Based on this observation, we propose a power management scheme that is specialized for the Web app runtime environment. This approach incurs two technical challenges; identification of the bottleneck resource and determination of the appropriate performance level for unsaturated resource. The proposed power management scheme uses the CPU utilization level of the Window Manager to tell which one is the bottleneck if exists. The Window Manager draws the final screen using the processed results delivered from the GPU. Thus, the Window Manager is on the critical path that determines the quality of user experience and purely executed by the CPU. The proposed scheme uses the weighted average of the Window Manager utilization to prevent excessive sensitivity and fluctuation. We classified Web apps into three categories using the analysis results that measure frame-per-second (FPS) changes under diverse CPU/GPU clock combinations. The results showed that the capability of the CPU decides user experience when the Window Manager utilization is above 90% and consequently, the proposed scheme decreases the performance level of CPU by one step. On the contrary, when its utilization is less than 60%, the bottleneck usually lies in the GPU and it is desirable to decrease the performance of GPU. Even the processing unit that is not on critical path, excessive performance drop can occur and that may adversely affect the user experience. Therefore, our scheme lowers the frequency gradually, until it finds an appropriate level by periodically checking the CPU utilization. The proposed scheme reduced the energy consumption by 10.34% on average in comparison to the conventional Linux kernel, and it worsened their FPS by 1.07% only on average.

Keywords: interactive applications, power management, QoS, Web apps, WebGL

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Authors: Ming-Kwei Lee, Chih-Feng Yen

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The electrical characteristics of liquid phase deposited silicon oxynitride film on ammonium sulfide treated p-type (100) gallium arsenide substrate were investigated. Hydrofluosilicic acid, ammonia and boric acid aqueous solutions were used as precursors. The electrical characteristics of silicon oxynitride film are much improved on gallium arsenide substrate with ammonium sulfide treatment. With post-metallization annealing, hydrogen ions can further passivate defects in SiON/GaAs film and interface. The leakage currents can reach 7.1 × 10-8 and 1.8 × 10-7 at ± 2 V. The dielectric constant and effective oxide charges are 5.6 and -5.3 × 1010 C/cm2, respectively. The hysteresis offset of hysteresis loop is merely 0.09 V.

Keywords: liquid phase deposition, SiON, GaAs, PMA, (NH4)2S

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Authors: Nazneen, Aditya Kumar Patra

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The aim of this study was to investigate the personal exposures of toll plaza workers on a busy national highway in India during the winter season to PM₂.₅, PM₁₀, BC (black carbon), and UFP (ultrafine particles). The results showed that toll workers inside the toll collection booths (ITC) were exposed to higher concentrations of air pollutants than those working outside the booths (OTC), except for UFP. Specifically, the concentrations of PM₂.₅ were 20₄.₇ µg m⁻³ (ITC) and 100.4 µg m⁻³ (OTC), while PM₁₀ concentrations were 326.1 µg m⁻³ (ITC) and 24₄.₇ µg m⁻³ (OTC), and BC concentrations were 30.7 µg m⁻³ (ITC) and 17.2 µg m⁻³ (OTC). In contrast, UFP concentrations were higher at OTC (11312.8 pt cm⁻³) than at IOC (7431.6 pt cm⁻³). The diurnal variation of pollutants showed higher concentrations in the evening due to increased traffic and less atmospheric dispersion. The respiratory deposition dose (RDD) of pollutants was higher inside the toll booths, especially during the evening. The study also revealed that PM particles consisted of soot, mineral and fly ash, which are proxies of fresh exhaust emissions, re-suspended road dust, and industrial emissions, respectively. The presence of Si, Al, Ca and Pb, as confirmed by EDX (Energy Dispersive X-ray analysis) analyses, indicated the sources of pollutants to be re-suspended road dust, brake/tire wear, and construction dust. The findings emphasize the need for policies to regulate air pollutant concentrations, particularly in workplaces situated near busy roads.

Keywords: air pollution, PM₂.₅, black carbon, traffic emissions

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Authors: Dung Nguyen, Yu Wei, Eric Henderson

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Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: Fouad. Inel, Lakhdar. Khochemane

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This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: The first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-Integrated Derivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: parallel cable-based robots, geometric modeling, dynamic modeling, graphical user interface, open loop, PID/PD controllers

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Authors: Tom D. Gedeon, Ujala Rampaul

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The evaluation of electronic consumer goods are most often done from the perspective of analysing the latest models, comparing their advantages and disadvantages with respect to price. This style of evaluation is often performed by one or a few product experts on a wide range of features that may not be applicable to each user. We instead used a scenario-based approach to evaluate a number of e-readers. The setting is similar to a user who is interested in a new product or technology and has allocated a limited budget. We evaluate the quality and usability of e-readers available within that budget range. This is based on the assumption of a rational market which prices older second hand devices the same as functionally equivalent new devices. We describe our evaluation and comparison of four branded eReaders, as the initial stage of a larger project. The scenario has a range of tasks approximating a busy person who does not bother to read the manual. We found that navigation within books to be the most significant differentiator between the eReaders in our scenario based evaluation process.

Keywords: eReader, scenario based, price comparison, Kindle, Kobo, Nook, Sony, technology adoption

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Authors: Pradeep Kumar, Shalinee Shukla

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Pavement plays a vital role in the socio-economic development of a country. Bituminous roads construction with conventional paving grade bitumen obtained from hot mix plant creates pollution and involves emission of greenhouse gases, also the construction of pavements at very high temperature is not feasible or desirable for high rainfall and snowfall areas. This problem of overheating can be eliminated by the construction of pavements with the usage of emulsified cold mixes which will eliminate emissions and help in the reduction of fuel requirement at mixing plant, which leads to energy conservation. Cold mix is a mixture of unheated aggregate and emulsion or cutback and filler. The primary objective of this research is to assess the volumetric mix design parameters of recycled aggregates with cold mixing technology and also to assess the impact of additives on volumetric mix characteristics. In this present study, bituminous pavement materials are reclaimed using cold mix technology, and Marshall specimens are prepared with the help of slow setting type 2 (SS-2) cationic bitumen emulsion as a binder for recycled aggregates. This technique of road construction is more environmentally friendly and can be done in adverse weather conditions.

Keywords: cold mixes, bitumen emulsion, recycled aggregates, volumetric properties

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Authors: M. Fikriansyah Wicaksono, Rafael Arief Budiman, M. Very Setiawan

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Currently, a wide range of innovative mobile library (M-Library) service is provided for the users in the library. The M-Library service is an innovation that aims to bring the collections of the library to users who currently use their smartphone so often. With M-Library services, it is expected that the users can fulfill their information needs more conveniently and practically. This study aims to find out how users use M-Library services provided by UGM library. This study applied a quantitative approach to investigate how to use the application M-Library. The Technology Acceptance Model (TAM) theory is applied to perform the analysis in terms of perceived usefulness, perceived ease of use, attitude towards behavior, behavioral intention and actual system usage. The results show that overall the users found that the M-Library application is useful to meet their information needs. Such as facilitate user to access e-resources, search UGM library collections, online booking collections, and reminder for returning book.

Keywords: m-library, mobile library services, technology acceptance, library of UGM

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Ignacio Sanchez Cohen, Aurelio Pedroza Sandoval, Ricardo Trejo Calzada

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Water harvesting systems (WHS) has become the unique alternative that farmers in dry areas accounts for surviving dry periods. Nevertheless, technicians, agronomists, and users, in general, have to cope with the difficulty of finding suitable technology for optimal design of WHS. In this paper, we describe a user-friendly computer program that uses readily available information for the design of multiple WHS depending upon the water final use (agriculture, household, conservation, etc). The application (APP) itself contains several links to help the user complete the input requirements. It is not a prerequisite to have any computer skills for the use of the APP. Outputs of the APP are the dimensions of the WHS named terraces, micro-catchments, cisterns, and small household cisterns for roof water catchment. The APP also provides guidance on crops for backyard agriculture. We believe that this tool may guide users to better optimize WHS for multiple purposes and to widen the possibility of copping with dry spells in arid lands.

Keywords: rainfall-catchment, models, computer aid, arid lands

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Authors: Xiaoxue Jin, Qiong Zhang

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The rapid influx and ongoing flow of young migrants in large cities, alongside the emergence and evolution of new social media, have led to increased interpersonal alienation and weakened place attachment. In the interplay between individuals and space, urban public spaces play a pivotal role in meeting the multifaceted needs of individuals and fostering a sense of attachment. This article aims to investigate the relationship between the place characteristics of public spaces and individuals' needs and perceptions, with an aim to identify the factors influencing place attachment among the youth. This study is conducted in the Shekou community of Shenzhen, focusing on the youth residents to evaluate their place attachment levels and to analyze their perceptions of the place characteristics of selected public spaces. The influencing factors of public spaces on place attachment were sorted out through detailed data analysis. Research has found that rapid urbanization has led to spatial homogenization and spatial segregation caused by uneven resource distribution, which in turn diminishes the utilization of public spaces. The social characteristics of public spaces, such as the quality of social activities and spatial openness, are critical in forming place attachment. In this research, place characteristics impacting place attachment are categorized, aiming to reconstruct the characteristics of public space places and use them as a medium to explore the place attachment of young people, promote their independent creation and participation in public life, and enhance the dynamism between individuals and spaces.

Keywords: place attachment, place characteristics, public spaces, spatial perception

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Authors: Tanhao Gao, Hongtao Zhou

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With the COVID-19 pandemic spreading worldwide, people are facing more significant mental pressure. The government and social groups are sparing no effort to find ways to heal people's emotions and return to normal life. Therefore, research on emotional healing has urgency and practical significance. From the perspective of urban planning, street furniture has the potential to become "emotional healing touchpoints." This study first analyzed the suitable places for adding emotional healing street furniture in the background of urban micro-renewal and combined the fifteen-minute living circle, the leftover space, and urban acupuncture theories, then used the 5W analysis method to show the main characteristics of emotionally healing street furniture. Finally, the research discovers four design strategies, which can be summarized as: A. Exploring the renewal potential of the leftover space; B. Integrating with local culture and the surrounding environment; C. Discovering quick and straightforward ways of interaction; D. Finding a delicate balance between artistry and functionality. Then, the author takes one emotional healing street furniture located on Chifeng Road as an example to show the design strategies vividly.

Keywords: emotional healing, street furniture, urban micro-renewal, urban acupuncture

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Andrew Laghos

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The Internet is a big part of our everyday lives. People can now access the internet from a variety of places including home, college, and work. Many airports, hotels, restaurants and cafeterias, provide free wireless internet to their visitors. Using technologies like computers, tablets, and mobile phones, we spend a lot of our time online getting entertained, getting informed, and communicating with each other. This study deals with the latter part, namely, human communication through the Internet. People can communicate with each other using social media, social network sites (SNS), e-mail, messengers, chatrooms, and so on. By connecting with each other they form virtual communities. Regarding SNS, types of connections that can be studied include friendships and cliques. Analyzing these connections is important to help us understand online user behavior. The method of Social Network Analysis (SNA) was used on a case study, and results revealed the existence of some useful patterns of interactivity between the participants. The study ends with implications of the results and ideas for future research.

Keywords: human communication, internet communities, online user behavior, psychology

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Authors: Lai Wenfang

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Tthis study will describe how to use artificial intelligence (AI) technology to build the user-oriented platform for integrated archival service. The platform will be launched in 2020 by the National Archives Administration (NAA) in Taiwan. With the progression of information communication technology (ICT) the NAA has built many systems to provide archival service. In order to cope with new challenges, such as new ICT, artificial intelligence or blockchain etc. the NAA will try to use the natural language processing (NLP) and machine learning (ML) skill to build a training model and propose suggestions based on the data sent to the platform. NAA expects the platform not only can automatically inform the sending agencies’ staffs which records catalogues are against the transfer or destroy rules, but also can use the model to find the details hidden in the catalogues and suggest NAA’s staff whether the records should be or not to be, to shorten the auditing time. The platform keeps all the users’ browse trails; so that the platform can predict what kinds of archives user could be interested and recommend the search terms by visualization, moreover, inform them the new coming archives. In addition, according to the Archives Act, the NAA’s staff must spend a lot of time to mark or remove the personal data, classified data, etc. before archives provided. To upgrade the archives access service process, the platform will use some text recognition pattern to black out automatically, the staff only need to adjust the error and upload the correct one, when the platform has learned the accuracy will be getting higher. In short, the purpose of the platform is to deduct the government digital transformation and implement the vision of a service-oriented smart government.

Keywords: artificial intelligence, natural language processing, machine learning, visualization

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Authors: Mingwei Yi, Liujie Guo, Zongjun Pan, Xiang Lin, Xiaoming Yi

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With the rapid expansion of road construction mileage in China, the scale of road maintenance needs has concurrently escalated. As the service life of roads extends, the design of pavement repair and maintenance emerges as a crucial component in preserving the excellent performance of the pavement. The remaining service life of asphalt pavement structure is a vital parameter in the lifecycle maintenance design of asphalt pavements. Based on an analysis of pavement structural integrity, this study introduces a characterization and assessment of the remaining life of existing asphalt pavement structures. It proposes indicators such as the transverse crack spacing and the length of longitudinal cracks. The transverse crack spacing decreases with an increase in maintenance intervals and with the extended use of semi-rigid base layer structures, although this trend becomes less pronounced after maintenance intervals exceed 4 years. The length of longitudinal cracks increases with longer maintenance intervals, but this trend weakens after five years. This system can support the enhancement of standardization and scientific design in highway maintenance decision-making processes.

Keywords: structural integrity, highways, pavement evaluation, asphalt concrete pavement

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Authors: Suraj Gururaj, Sumantha Udupa U.

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Browsing the Web has emerged as the de facto activity performed on the Internet. Although browsing gets tracked, the manageability aspect of Web browsing history is very poor. In this paper, we have a workable solution implemented by using machine learning and natural language processing techniques for efficient manageability of user’s browsing history. The significance of adding such a capability to a Web browser is that it ensures efficient and quick information retrieval from browsing history, which currently is very challenging. Our solution guarantees that any important websites visited in the past can be easily accessible because of the intelligent and automatic classification. In a nutshell, our solution-based paper provides an implementation as a browser extension by intelligently classifying the browsing history into most relevant category automatically without any user’s intervention. This guarantees no information is lost and increases productivity by saving time spent revisiting websites that were of much importance.

Keywords: adhoc retrieval, Chrome extension, supervised learning, tile, Web personalization

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Authors: Julio Aguirre, Yohnny Campana, Elmer Guerrero, Daniel De La Torre Ugarte

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A well-developed transportation network is a necessary condition for a country to derive full benefits from good trade and macroeconomic policies. Road infrastructure plays a key role in the economic development of rural areas of developing countries; where agriculture is the main economic activity. The ability to move agricultural production from the place of production to the market, and then to the place of consumption, greatly influence the economic value of farming activities, and of the resources involved in the production process, i.e., labor and land. Consequently, investment in transportation networks contributes to enhance or overcome the natural advantages or disadvantages that topography and location have imposed over the agricultural sector. This is of particular importance when dealing with countries, like Peru, with a great topographic diversity. The objective of this research is to estimate the impacts of road infrastructure on the performance of the agricultural sector. Specific variables of interest are changes in travel time, shifts of production for self-consumption to production for the market, changes in farmers income, and impacts on the diversification of the agricultural sector. In the study, a cross-section model with instrumental variables is the central methodological instrument. The data is obtained from agricultural and transport geo-referenced databases, and the instrumental variable specification utilized is based on the Kruskal algorithm. The results show that the expansion of road connectivity reduced farmers' travel time by an average of 3.1 hours and the proportion of output sold in the market increases by up to 40 percentage points. The increase in connectivity has an unexpected increase in the districts index of diversification of agricultural production. The results are robust to the inclusion of year and region fixed-effects, and to control for geography (i.e., slope and altitude), population variables, and mining activity. Other results are also very eloquent. For example, a clear positive impact can be seen in access to local markets, but this does not necessarily correlate with an increase in the production of the sector. This can be explained by the fact that agricultural development not only requires provision of roads but additional complementary infrastructure and investments intended to provide the necessary conditions so that producers can offer quality products (improved management practices, timely maintenance of irrigation infrastructure, transparent management of water rights, among other factors). Therefore, complementary public goods are needed to enhance the effects of roads on the welfare of the population, beyond enabling them to increase their access to markets.

Keywords: agriculture devolepment, market access, road connectivity, regional development

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Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: Jayesh M. Patel, Bharat P. Modi

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The availability of on mobile devices that can invoke the demonstrated that the total data demand from users is far higher than previously articulated by measurements based solely on a cellular-centric view of smart-phone usage. The ratio of Wi-Fi to cellular traffic varies significantly between countries, This paper is shown the compression between the cellular data usage and Wi-Fi data usage by the user. This strategy helps operators to understand the growing importance and application of yield management strategies designed to squeeze maximum returns from their investments into the networks and devices that enable the mobile data ecosystem. The transition from unlimited data plans towards tiered pricing and, in the future, towards more value-centric pricing offers significant revenue upside potential for mobile operators, but, without a complete insight into all aspects of smartphone customer behavior, operators will unlikely be able to capture the maximum return from this billion-dollar market opportunity.

Keywords: cellular, Wi-Fi, mobile, smart phone

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Authors: Victor Radich, Tania Basso, Regina Moraes

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Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis or opinion mining can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results obtained so far have shown that it is possible to extract data from social networks and combine the techniques for a more complete classification.

Keywords: lead qualification, sentiment analysis, opinion mining, machine learning, CRM, lead scoring

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Authors: Youssouf Benmeriem

Abstract:

Shear strength of sandy soils has been considered as the important parameter to study the stability of different civil engineering structures when subjected to monotonic, cyclic and earthquake loading conditions. The proposed research investigated the effect of grading characteristics on the shear strength and mechanical behavior of granular classes of sands mixed with silt in loose and dense states (Dr = 15% and 90%). The laboratory investigation aimed at understanding the extent or degree at which shear strength of sand-silt mixture soil is affected by its gradation under static loading conditions. For the purpose of clarifying and evaluating the shear strength characteristics of sandy soils, a series of Casagrande shear box tests were carried out on different reconstituted samples of sand-silt mixtures with various gradations. The soil samples were tested under different normal stresses (100, 200 and 300 kPa). The results from this laboratory investigation were used to develop insight into the shear strength response of sand and sand-silt mixtures under monotonic loading conditions. The analysis of the obtained data revealed that the grading characteristics (D10, D50, Cu, ESR, and MGSR) have significant influence on the shear strength response. It was found that shear strength can be correlated to the grading characteristics for the sand-silt mixture. The effective size ratio (ESR) and mean grain size ratio (MGSR) appear as pertinent parameters to predict the shear strength response of the sand-silt mixtures for soil gradation under study.

Keywords: grading characteristics, granular classes of sands, mechanical behavior, sand-silt, shear strength

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Authors: Do Jaesoo, Kim Kyoung Seok

Abstract:

Under the recent difficult economic conditions, a number of people are increasingly expecting fostering ventures as the breakthrough in economic recovery and thus more attention is socially paid to an entrepreneur spirit. However, even though the role of managers is very important for the success of a venture company, programs to cultivate their qualities and skills are quite insufficient. In recent years, programs to foster entrepreneurs and business men have proliferated, which are led mainly by national agencies, research institutions, and large corporations. However, these programs still remain at a tottering stage, since there is no accumulated knowledge in many aspects, including systemic know-how and education. Therefore, this study attempted to introduce the definition of the entrepreneur (founder’s) spirit and furthermore identify the characteristics required for entrepreneurs as the subject of management. It thus tried to examine how those characteristics have an influence on entrepreneurs as their successful conditions, and presented foreign cases after analyzing the entrepreneur spirit through case studies. The entrepreneur spirit and the venture management emerge as a new field in business administration and scholars have reported various theories. Further research activities and efforts for active exchanges are also needed thereof.

Keywords: venture, entrepreneur, entrepreneur (founder’s) spirit, characteristics of entrepreneur spirit

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Authors: Ajeni Ari, Chiara Maria Leva, Lorraine D’Arcy, Mary Kinahan

Abstract:

In addressing gender and transport, considerations of mobility disparities amongst users are important. Public transport (PT) policy and design do not efficiently account for the varied mobility practices between men and women, with literature only recently showing a movement towards gender inclusion in transport. Arrantly, transport policy and designs remain gender-blind to the variation of mobility needs. The global movement towards sustainability highlights the need for expeditious strategies that could mitigate biases within the existing system. At the forefront of such a plan of action, in part, may be mandated inclusive infrastructural designs that stimulate user engagement with the transport system. Fundamentally access requires a means or an opportunity for the entity, which for PT is an establishment of its physical environment and/or infrastructural design. Its practicality may be utilised with knowledge of shortcomings in tangible or intangible aspects of the service offerings allowing access to opportunities. To inform on existing biases in PT planning and design, this study analyses qualitative data to examine the opinions and lived experiences among transport users in Ireland. Findings show that infrastructural design plays a significant role in users’ engagement with the service. Paramount to accessibility are service provisions that cater to both user interactions and those of their dependents. Apprehension to use the service is more so evident in women in comparison to men, particularly while carrying out household duties and caring responsibilities at peak times or dark hours. Furthermore, limitations are apparent with infrastructural service offerings that do not accommodate the physical (dis)ability of users, especially universal design. There are intersecting factors that impinge on accessibility, e.g., safety and security, yet essentially; the infrastructural design is an important influencing parameter to user perceptual conditioning. Additionally, data discloses the need for user intricacies to be factored in transport planning geared towards gender inclusivity, including mobility practices, travel purpose, transit time or location, and system integration.

Keywords: infrastructure design, public transport, accessibility, women, gender

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Authors: Sofia Figueroa, Efrain Bernal, Silvia Del Pilar Forero, Humberto Ramirez

Abstract:

This work shows a detailed review of the scope of global research on the road infrastructure using materials from Construction and Demolition Waste (C&DW), also called RCD. In the first phase of this research, a segment of road was designed using recycled materials such as Reclaimed Asphalt Pavement (RAP) on the top, the natural coarse base including 30% of RAP and recycled concrete blocks. The second part of this segment was designed using regular materials for each layer of the pavement. Both structures were built next to each other in order to analyze and measure the material properties as well as performance and environmental factors in the pavement under real traffic and weather conditions. Different monitoring devices were installed among the structure, based on the literature revision, such as soil cells, linear potentiometer, moisture sensors, and strain gauges that help us to know the C&DW as a part of the pavement structure. This research includes not only the physical characterization but also the measured parameters in a field such as an asphalt mixture (RAP) strain (ετ), vertical strain (εᵥ) and moisture control in coarse layers (%w), and the applied loads and strain in the subgrade (εᵥ). The results will show us what is happening with these materials in order to obtain not only a sustainable solution but also to know its behavior and lifecycle.

Keywords: sustainable pavements, construction & demolition waste-C&DW, recycled rigid concrete, reclaimed asphalt pavement-rap

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Authors: Humeyra Bolakar Tosun

Abstract:

The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

Procedia PDF Downloads 138