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One of the challenges of living in today's cities is parking availability. Searching for available parking spots can be a time-consuming task that simultaneously increases traffic congestion and greenhouse gas pollution by a significant 40%. A solution that would increase drivers' ability to locate an empty parking spot would represent an important step towards more sustainable parking as it would have a direct impact on reducing greenhouse gas pollution in urban areas. This paper proposes how data science can help by evaluating the prediction performance of four machine learning models. Analysed machine learning models are based on different machine learning methods (i.e., CatBoost and Random Forest) and use different real-world data sets (i.e., parking sensor data only or contextually enriched parking sensor data). The dummy (baseline) model is considered as well, but with a R2 score of 61.29% is outperformed by more advanced data science approaches. Prediction performance in the case of using parking sensor data only gives R2 score of 84.31% and 88.16% for Random Forest and CatBoost, respectively. The best prediction performance is achieved using CatBoost and contextually enriched data, resulting in the high-performing machine learning model with the R2 value of 88.83%, thus outperforming the Random Forest model by 1.7%. In fact, for both machine learning methods, the contextually enriched data approach gives better results for predicting parking spot availability. This suggests that parking data should be enriched with contextual data when designing and building sustainable parking solutions for smart cities of the future.
Goran Jelen; Vedran Podobnik; Jurica Babic. Contextual prediction of parking spot availability: A step towards sustainable parking. Journal of Cleaner Production 2021, 312, 127684 .
AMA StyleGoran Jelen, Vedran Podobnik, Jurica Babic. Contextual prediction of parking spot availability: A step towards sustainable parking. Journal of Cleaner Production. 2021; 312 ():127684.
Chicago/Turabian StyleGoran Jelen; Vedran Podobnik; Jurica Babic. 2021. "Contextual prediction of parking spot availability: A step towards sustainable parking." Journal of Cleaner Production 312, no. : 127684.
This paper explores multidisciplinary application of emotions and human psychology within market behavior to analyse how emotional dimensions, extracted from Twitter messages and related to cryptocurrency market, are connected to future uncertainty and risk exposure. Although Twitter messages are often used to derive sentiment scores that are then linked to market performance, specific values of emotional components have not been utilised in the previous academic literature to analyze risk behavior. We connect VAD (valence, arousal and dominance) dimensions with the future hourly absolute value of returns, future 24-hour return standard deviation, future 24-hour downside deviation and future 24-hour maximal drawdown (all measuring market uncertainty and risk) on the cryptocurrency market. Results show that all target variables have various predictability from VAD dimensions, where lagged dominance variable (perceived level of control) is the key driver of predictability. Additionally, VAD dimensions have been grouped into distinct clusters by using the k-Means approach. A comparison of selected clusters on in-sample and out-of-sample data showed consistent predictability of identified clusters to all target variables. Results show that emotional components of human emotions, derived from cumulative Twitter messages, actually predict future uncertainty and risk with consistent clustering profile from lagged dominance VAD dimension where lower dominance values predict higher future risk and vice versa.
Demijan Grgic; Vedran Podobnik. Application of Data Science for Understanding Emotional Dimensional Behavior and Their Connection to Uncertainty and Risk Behavior. IEEE Access 2021, 9, 72624 -72636.
AMA StyleDemijan Grgic, Vedran Podobnik. Application of Data Science for Understanding Emotional Dimensional Behavior and Their Connection to Uncertainty and Risk Behavior. IEEE Access. 2021; 9 (99):72624-72636.
Chicago/Turabian StyleDemijan Grgic; Vedran Podobnik. 2021. "Application of Data Science for Understanding Emotional Dimensional Behavior and Their Connection to Uncertainty and Risk Behavior." IEEE Access 9, no. 99: 72624-72636.
Electric vehicle (EV) owners enjoy many positive aspects when driving their cars, including low running costs and zero tailpipe gas emissions, which makes EVs a clean technology provided that they are sourced through renewable sources, e.g., biomass, solar power, or wind energy. However, their driving behaviour is often negatively affected by the so-called range anxiety phenomenon, i.e., a concern that an EV might not have enough driving range to reach the desired destination due to its limited battery size. The perception of range anxiety may also affect potential buyers in their decisions on whether to purchase an internal combustion engine vehicle as opposed to an EV. This paper investigates some factors that influence range anxiety through a comparative analysis of two target groups: (i) existing EV owners, and (ii) non-EV owners (i.e., potential EV owners). The specially crafted survey was used to collect range anxiety data from more than 200 participants. In particular, participants provided their perceptions on (i) the potential relationship between existing gas station infrastructure and the desired EV charging station infrastructure, and (ii) the potential relationship between range anxiety and two influencing variables, namely the current state of charge and remaining range. Concerning the existing gas station infrastructure, evidence suggests that both target groups think that the distances between gas stations could be increased. Moreover, our analysis shows that the desired distances between charging stations correspond to the distances between the existing gas stations, which indicates that both EV owners and non-EV owners have a common view on the optimal gas station and charging station topology. Furthermore, we find that the type of settlement (urban vs rural) influences preferred distances, where both target groups living in cities desire shorter distances, and that non-EV owners, as opposed to EV owners, are more prone to be affected by the state of charge and remaining range. Quantitatively, we are able to define a measure for range anxiety, which is connected with the preferred distance between two neighbouring charging stations. Throughout our analyses, we find that the mean preferred distance between two neighbouring charging stations is 7 km, but this value significantly differs based on the settlement type of a (potential) EV owner.
Dario Pevec; Jurica Babic; Arthur Carvalho; Yashar Ghiassi-Farrokhfal; Wolfgang Ketter; Vedran Podobnik. A survey-based assessment of how existing and potential electric vehicle owners perceive range anxiety. Journal of Cleaner Production 2020, 276, 122779 .
AMA StyleDario Pevec, Jurica Babic, Arthur Carvalho, Yashar Ghiassi-Farrokhfal, Wolfgang Ketter, Vedran Podobnik. A survey-based assessment of how existing and potential electric vehicle owners perceive range anxiety. Journal of Cleaner Production. 2020; 276 ():122779.
Chicago/Turabian StyleDario Pevec; Jurica Babic; Arthur Carvalho; Yashar Ghiassi-Farrokhfal; Wolfgang Ketter; Vedran Podobnik. 2020. "A survey-based assessment of how existing and potential electric vehicle owners perceive range anxiety." Journal of Cleaner Production 276, no. : 122779.
In the last decade, electric vehicles (EVs) have emerged as a sustainable transportation alternative to traditional internal combustion engine (ICE) cars, with automotive software as the key driver behind the advancements. A well-defined information and communication technology (ICT) architecture, comprised of electronics and software, can increase an EV’s energy and cost efficiency, safety and comfort. With connected and autonomous electric vehicles (CAEVs) fast becoming a reality, the importance of software in vehicles increases tenfold. This paper serves as an introduction into the field of electromobility and automotive software. It provides an overview of the software and ICT architecture found in CAEVs and identifies future trends and challenges in automotive software development.
Hrvoje Vdovic; Jurica Babic; Vedran Podobnik. Automotive Software in Connected and Autonomous Electric Vehicles: A Review. IEEE Access 2019, 7, 166365 -166379.
AMA StyleHrvoje Vdovic, Jurica Babic, Vedran Podobnik. Automotive Software in Connected and Autonomous Electric Vehicles: A Review. IEEE Access. 2019; 7 (99):166365-166379.
Chicago/Turabian StyleHrvoje Vdovic; Jurica Babic; Vedran Podobnik. 2019. "Automotive Software in Connected and Autonomous Electric Vehicles: A Review." IEEE Access 7, no. 99: 166365-166379.
Current trends are showing that the popularity of electric vehicles (EVs) has significantly increased over the last few years, causing changes not only in the transportation industry but generally in business and society. This paper covers one possible angle to the (r)evolution instigated by EVs, i.e., it provides the data science perspective review of the interdisciplinary area at the intersection of green transportation, energy informatics, and economics. Namely, the review summarizes data-driven research in EVs by identifying two main research streams: (i) socio–economic, and (ii) socio–technical. The socio–economic stream includes research in: (i) acceptance of green transportation in countries and among different populations, (ii) current trends in the EV market, and (iii) forecasting future sales for the green transportation. The socio–technical stream includes research in: (i) electric vehicle battery price and capacity and (ii) charging station management. This kind of study is especially important now when the question is no longer whether the transition from internal-combustion engine vehicles to clean-fuel vehicles is going to happen but how fast it will happen and what are going to be implications for society, governmental policies, and industry. Based on the presented literature review, the paper also outlines the most significant open questions and challenges that are yet to be solved: (i) scarcity of trustworthy (open) data, and (ii) designing a generalized methodology for charging station deployment.
Dario Pevec; Jurica Babic; Vedran Podobnik. Electric Vehicles: A Data Science Perspective Review. Electronics 2019, 8, 1190 .
AMA StyleDario Pevec, Jurica Babic, Vedran Podobnik. Electric Vehicles: A Data Science Perspective Review. Electronics. 2019; 8 (10):1190.
Chicago/Turabian StyleDario Pevec; Jurica Babic; Vedran Podobnik. 2019. "Electric Vehicles: A Data Science Perspective Review." Electronics 8, no. 10: 1190.
Besides the smart grid, future sustainable energy systems will have to employ a smart market approach where consumers are able choose one of many different energy providers. The Power Trading Agent Competition (Power TAC) provides an open source, smart grid simulation platform where brokers compete in power brokerage. This paper presents CrocodileAgent, which competed in the Power TAC 2018 finals as a broker agent. The main focus in the design and development of CrocodileAgent 2018 was the creation of smart time-of-use tariffs to reduce peak-demand charges. CrocodileAgent 2018 was ranked third in Power TAC 2018 Finals, with a positive final profit and a positive result in each of three game types. In addition, CrocodileAgent 2018 had the highest percentage of ?profitable games? (91%) from among all competing agents, the second highest level of ?net profit per standard deviation? (0.48) and the third highest ?net profit per subscriber? (79 monetary units).
Demijan Grgic; Hrvoje Vdovic; Jurica Babic; Vedran Podobnik. CrocodileAgent 2018: Robust agent-based mechanisms for power trading in competitive environments. Computer Science and Information Systems 2019, 16, 105 -129.
AMA StyleDemijan Grgic, Hrvoje Vdovic, Jurica Babic, Vedran Podobnik. CrocodileAgent 2018: Robust agent-based mechanisms for power trading in competitive environments. Computer Science and Information Systems. 2019; 16 (1):105-129.
Chicago/Turabian StyleDemijan Grgic; Hrvoje Vdovic; Jurica Babic; Vedran Podobnik. 2019. "CrocodileAgent 2018: Robust agent-based mechanisms for power trading in competitive environments." Computer Science and Information Systems 16, no. 1: 105-129.
Electric vehicles (EVs) are currently the most promising technology with the potential to transform transportation and energy landscapes to make industry and society more sustainable. Although their adoption has been much faster than anticipated a few years ago, resulting in a significant increase from 400,000 EVs sold in 2013 to more than 3 million in 2017, the coming years will be crucial for determining whether EVs are to become a new transportation industry “standard”, the role of which has been held by internal combustion engine (ICE) vehicles over the last hundred years. Not only will innovation in EV batteries determine a “win” or “fail” for EVs, but a significant role in its acceptance will be successful development of a comprehensive EV eco-system, establishing an efficient network of EV chargers as well as attractive and affordable charging tariffs. Furthermore, having insight as to how much money EV users are willing to pay for the charging service (i.e., willingness to pay) in various circumstances is one of the essential factors in building a successful EV eco-system. That being said, this paper utilizes a gamified survey for exploring a person's willingness to pay for EV charging. The experimental setup includes both the classic (text-only) questionnaire, as well as the game-based questionnaire. Therefore, not only have interesting insights on the willingness to pay for EV charging been identified, but analysis of user experience analysis from the questionnaires suggests that use of gamification is a good approach to performing a survey as it exhibits superior hedonic quality in comparison to classic methods (i.e., text-only questionnaire).
Lara Dorcec; Dario Pevec; Hrvoje Vdovic; Jurica Babic; Vedran Podobnik. How do people value electric vehicle charging service? A gamified survey approach. Journal of Cleaner Production 2018, 210, 887 -897.
AMA StyleLara Dorcec, Dario Pevec, Hrvoje Vdovic, Jurica Babic, Vedran Podobnik. How do people value electric vehicle charging service? A gamified survey approach. Journal of Cleaner Production. 2018; 210 ():887-897.
Chicago/Turabian StyleLara Dorcec; Dario Pevec; Hrvoje Vdovic; Jurica Babic; Vedran Podobnik. 2018. "How do people value electric vehicle charging service? A gamified survey approach." Journal of Cleaner Production 210, no. : 887-897.
Online social networks are complex systems often involving millions or even billions of users. Understanding the dynamics of a social network requires analysing characteristics of the network (in its entirety) and the users (as individuals). This paper focuses on calculating user’s social influence, which depends on (i) the user’s positioning in the social network and (ii) interactions between the user and all other users in the social network. Given that data on all users in the social network is required to calculate social influence, something not applicable for today’s social networks, alternative approaches relying on a limited set of data on users are necessary. However, these approaches introduce uncertainty in calculating (i.e., predicting) the value of social influence. Hence, a methodology is proposed for evaluating algorithms that calculate social influence in complex social networks; this is done by identifying the most accurate and precise algorithm. The proposed methodology extends the traditional ground truth approach, often used in descriptive statistics and machine learning. Use of the proposed methodology is demonstrated using a case study incorporating four algorithms for calculating a user’s social influence.
Vanja Smailovic; Vedran Podobnik; Ignac Lovrek. A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks. Complexity 2018, 2018, 1 -20.
AMA StyleVanja Smailovic, Vedran Podobnik, Ignac Lovrek. A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks. Complexity. 2018; 2018 ():1-20.
Chicago/Turabian StyleVanja Smailovic; Vedran Podobnik; Ignac Lovrek. 2018. "A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks." Complexity 2018, no. : 1-20.
Current trends suggest that there is a substantial increase in the overall usage of electric vehicles (EVs). This, in turn, is causing drastic changes in the transportation industry and, more broadly, in business, policy making, and society. One concrete challenge brought by the increase in the number of EVs is a higher demand for charging stations. This paper presents a methodology to address the challenge of EV charging station deployment. The proposed methodology combines multiple sources of heterogeneous real-world data for the sake of deriving insights that can be of a great value to decision makers in the field, such as EV charging infrastructure providers and/or local governments. Our starting point is the business data, ie, data describing charging infrastructure, historical data about charging transactions, and information about competitors in the market. Another type of data used are geographical data, such as places of interest located around chargers (eg, hospitals, restaurants, and shops) and driving distances between available chargers. The merged data from different sources are used to predict charging station utilization when EV charging infrastructure and/or contextual data change, eg, when another charging station or a place of interest is created. On the basis of such predictions, we suggest where to deploy new charging stations. We foresee that the proposed methodology can be used by EV charging infrastructure providers and/or local governments as a decision support tool that prescribes an optimal area to place a new charging station while keeping a desired level of utilization of the charging stations. We showcase the proposed methodology with an illustrative example involving the Dutch EV charging infrastructure through the period from 2013 to 2016. Specifically, we prescribe the optimal location for new ELaadNL charging stations based on different objectives such as maximizing the overall charging network utilization and/or increasing the number of chargers in scarcely populated areas.
Dario Pevec; Jurica Babic; Martin A. Kayser; Arthur Carvalho; Yashar Ghiassi-Farrokhfal; Vedran Podobnik. A data-driven statistical approach for extending electric vehicle charging infrastructure. International Journal of Energy Research 2018, 42, 3102 -3120.
AMA StyleDario Pevec, Jurica Babic, Martin A. Kayser, Arthur Carvalho, Yashar Ghiassi-Farrokhfal, Vedran Podobnik. A data-driven statistical approach for extending electric vehicle charging infrastructure. International Journal of Energy Research. 2018; 42 (9):3102-3120.
Chicago/Turabian StyleDario Pevec; Jurica Babic; Martin A. Kayser; Arthur Carvalho; Yashar Ghiassi-Farrokhfal; Vedran Podobnik. 2018. "A data-driven statistical approach for extending electric vehicle charging infrastructure." International Journal of Energy Research 42, no. 9: 3102-3120.
This paper presents the SmartSocial Dataset which describes 1,826 Facebook users with lots of details, including their connections and their interactions (e.g., posts, likes, and comments). We first present a detailed analysis of descriptive and network characteristics of the SmartSocial Dataset to provide evidence for its representativeness. Afterward, we analyze the relationship between social and behavioral characteristics of SmartSocial Dataset users and Benford's Law as well as Dunbar's Number, to test whether Facebook has the power to change natural (Benford) and anthropological (Dunbar) laws. We find that Facebook's features are aligned with the Benford's Law but redefine the way how Dunbar's Number is calculated. Finally, we demonstrate how those findings could help researchers and business practitioners who collect Facebook data sets in a way to indicate whether there is serious sampling problem with the data set they collected.
Darko Striga; Vedran Podobnik. Benford’s Law and Dunbar’s Number: Does Facebook Have a Power to Change Natural and Anthropological Laws? IEEE Access 2018, 6, 14629 -14642.
AMA StyleDarko Striga, Vedran Podobnik. Benford’s Law and Dunbar’s Number: Does Facebook Have a Power to Change Natural and Anthropological Laws? IEEE Access. 2018; 6 ():14629-14642.
Chicago/Turabian StyleDarko Striga; Vedran Podobnik. 2018. "Benford’s Law and Dunbar’s Number: Does Facebook Have a Power to Change Natural and Anthropological Laws?" IEEE Access 6, no. : 14629-14642.
The recent advent of electric vehicles (EVs) marks the beginning of a new positive era in the transportation sector. Although the environmental benefits of EVs are well-known today, planning and managing EV charging infrastructure are activities that are still not well-understood. In this paper, we are investigating how the so-called EV-enabled parking lot (EVPL), a parking lot that is equipped with a certain number of chargers, can define an appropriate parking policy in such a way that satisfies two challenges: EV owners’ needs for recharging as well as the parking lot operator’s goal of profit maximization. Concretely, we present three parking policies that are able to simultaneously deal with both EVs and internal combustion engine vehicles. Detailed sensitivity analysis, based on realworld data and simulations, evaluates the proposed parking policies in a case study concerning parking lots in Melbourne, Australia. Our study produces results that are highly prescriptive in nature because they inform a decision maker under which circumstances a certain parking policy operates optimally. Most notably, we find that the dynamic parking policy, which takes the advantage of advanced information technology (IT) and charging infrastructure by dynamically changing the role of parking spots with chargers, often outperforms the other two parking policies because it maximizes the profit and minimizes the chance of cars being rejected by the parking lot. We also discuss how making a few parking spots EV-exclusive might be a good policy when the number of available chargers is small and/or the required IT infrastructure is not in place for using the dynamic policy. We conclude our work by proposing a technology roadmap for transforming parking lots into smart EV-enabled parking lots based on the three studied parking policies.
Jurica Babic; Arthur Carvalho; Wolfgang Ketter; Vedran Podobnik. Evaluating Policies for Parking Lots Handling Electric Vehicles. IEEE Access 2017, 6, 944 -961.
AMA StyleJurica Babic, Arthur Carvalho, Wolfgang Ketter, Vedran Podobnik. Evaluating Policies for Parking Lots Handling Electric Vehicles. IEEE Access. 2017; 6 (99):944-961.
Chicago/Turabian StyleJurica Babic; Arthur Carvalho; Wolfgang Ketter; Vedran Podobnik. 2017. "Evaluating Policies for Parking Lots Handling Electric Vehicles." IEEE Access 6, no. 99: 944-961.
Although quite recently our diversity and inclusion core values were challenged, we should not forget to recognize the importance and value of bringing together students from underrepresented minorities and their different perspectives into our various workplace processes one day. Unfortunately, most of the outreach efforts in Science, Technology, Engineering, Mathematics and Computer Science (STEM-C) fields are designed only to help students coming from economically disadvantaged backgrounds to catch up with other students. What if instead of only making up for the opportunities they had missed, we could provide at least some of them with the cutting-edge education? In this paper, we present how Student Research Development Center's of Ana G. Mendez University System (AGMUS) in San Juan, Puerto Rico will achieve that the 14 Panel Advanced Modular Incoherent Scatter Radar (AMISR) becomes a base for an educational program for undergraduate and graduate students from Puerto Rico. Having AMISR belong to a Spanish Minority Institution is the first step in the right direction of putting together a scientific team, within AGMUS that will offer competitive research opportunities in Atmospheric Sciences to STEM-C majors from Puerto Rico and Latin America.
Juan F. Arratia; Iva Bojic; Vedran Podobnik. Building a competitive STEM-C workforce in a Minority Spanish Institution. 2017 IEEE Frontiers in Education Conference (FIE) 2017, 1 -4.
AMA StyleJuan F. Arratia, Iva Bojic, Vedran Podobnik. Building a competitive STEM-C workforce in a Minority Spanish Institution. 2017 IEEE Frontiers in Education Conference (FIE). 2017; ():1-4.
Chicago/Turabian StyleJuan F. Arratia; Iva Bojic; Vedran Podobnik. 2017. "Building a competitive STEM-C workforce in a Minority Spanish Institution." 2017 IEEE Frontiers in Education Conference (FIE) , no. : 1-4.
Jurica Babic; Arthur Carvalho; Wolfgang Ketter; Vedran Podobnik. A Data-Driven Approach to Manage Charging Infrastructure for Electric Vehicles in Parking Lots. SSRN Electronic Journal 2017, 1 .
AMA StyleJurica Babic, Arthur Carvalho, Wolfgang Ketter, Vedran Podobnik. A Data-Driven Approach to Manage Charging Infrastructure for Electric Vehicles in Parking Lots. SSRN Electronic Journal. 2017; ():1.
Chicago/Turabian StyleJurica Babic; Arthur Carvalho; Wolfgang Ketter; Vedran Podobnik. 2017. "A Data-Driven Approach to Manage Charging Infrastructure for Electric Vehicles in Parking Lots." SSRN Electronic Journal , no. : 1.
Andrea Pirsa; Leon Rokic; Hrvoje Vdovic; Lara Vertlberg; Matea Zilak; Zeljka Car; Vedran Podobnik. Analysis of ICT-based assistive solutions for people with disabilities. 2017 14th International Conference on Telecommunications (ConTEL) 2017, 1 .
AMA StyleAndrea Pirsa, Leon Rokic, Hrvoje Vdovic, Lara Vertlberg, Matea Zilak, Zeljka Car, Vedran Podobnik. Analysis of ICT-based assistive solutions for people with disabilities. 2017 14th International Conference on Telecommunications (ConTEL). 2017; ():1.
Chicago/Turabian StyleAndrea Pirsa; Leon Rokic; Hrvoje Vdovic; Lara Vertlberg; Matea Zilak; Zeljka Car; Vedran Podobnik. 2017. "Analysis of ICT-based assistive solutions for people with disabilities." 2017 14th International Conference on Telecommunications (ConTEL) , no. : 1.
Even students who are provided with currently best available education in Science, Technology, Engineering, Mathematics and Computer Science (STEM-C) fields are having problems coping with living in the modern world where technological advancements happen on a daily basis, let alone students coming from economically disadvantaged backgrounds. In a world where institutions offering formal education have to collaborate with individuals and groups of people interested in providing informal education, it is of a vital importance to set up good examples and share them with communities that are less experienced. In this paper we present how Student Research Development Center's (SRDC) best practices of establishing a pre-college pipeline for young economically disadvantage minority students, who are interested in STEM-C fields, from Puerto Rico are being transferred to Universidad Catolica de Nicaragua (UNICA). The goal of the paper is to show how we developed a partnership between Puerto Rico and Nicaragua, and used lessons learned in Puerto Rico to involve undergraduate and pre-college students from Nicaragua in research program using project based learning in STEM-C fields.
Iva Bojic; Vedran Podobnik; Juan F. Arratia; Mislav Grgic. Supporting economically disadvantaged students from Nicaragua in STEM-C fields. 2016 IEEE Frontiers in Education Conference (FIE) 2016, 1 -4.
AMA StyleIva Bojic, Vedran Podobnik, Juan F. Arratia, Mislav Grgic. Supporting economically disadvantaged students from Nicaragua in STEM-C fields. 2016 IEEE Frontiers in Education Conference (FIE). 2016; ():1-4.
Chicago/Turabian StyleIva Bojic; Vedran Podobnik; Juan F. Arratia; Mislav Grgic. 2016. "Supporting economically disadvantaged students from Nicaragua in STEM-C fields." 2016 IEEE Frontiers in Education Conference (FIE) , no. : 1-4.
The number of people who decide to share their photographs publicly increases every day, consequently making available new almost real-time insights of human behavior while traveling. Rather than having this statistic once a month or yearly, urban planners and touristic workers now can make decisions almost simultaneously with the emergence of new events. Moreover, these datasets can be used not only to compare how popular different touristic places are, but also predict how popular they should be taking into an account their characteristics. In this paper we investigate how country attractiveness scales with its population and size using number of foreign users taking photographs, which is observed from Flickr dataset, as a proxy for attractiveness. The results showed two things: to a certain extent country attractiveness scales with population, but does not with its size; and unlike in case of Spanish cities, country attractiveness scales sublinearly with population, and not superlinearly.
Iva Bojic; Ivana Nizetic-Kosovic; Alexander Belyi; Vedran Podobnik; Stanislav Sobolevsky; Carlo Ratti. Sublinear scaling of country attractiveness observed from Flickr dataset. 2016, 1 .
AMA StyleIva Bojic, Ivana Nizetic-Kosovic, Alexander Belyi, Vedran Podobnik, Stanislav Sobolevsky, Carlo Ratti. Sublinear scaling of country attractiveness observed from Flickr dataset. . 2016; ():1.
Chicago/Turabian StyleIva Bojic; Ivana Nizetic-Kosovic; Alexander Belyi; Vedran Podobnik; Stanislav Sobolevsky; Carlo Ratti. 2016. "Sublinear scaling of country attractiveness observed from Flickr dataset." , no. : 1.
Communication is a prerequisite for any form of social activity, including social networking. Nowadays, communication is not reserved only for humans, but machines can also communicate. This paper reviews the state-of-the-art technology in the area of Machine-to-Machine (M2M) communication by comparing the M2M concept with other related research paradigms such as Wireless Sensor Networks, Cyber-Physical Systems, Internet of Things, and Human-Agent Collectives. Furthermore, the paper analyses trends in the interconnecting of machines and identifies an evolutionary path in which future (smart) machines will form mostly or completely autonomous communities bonded through social connections. Such communities—machine social networks—will be formed dynamically, just like human connections, and based on the needs of machines, their context, and state of their environment. Finally, the paper outlines the current evolutionary stage and identifies key research challenges of machine social networking.
Marina Pticek; Vedran Podobnik; Gordan Jezic. Beyond the Internet of Things: The Social Networking of Machines. International Journal of Distributed Sensor Networks 2016, 12, 1 .
AMA StyleMarina Pticek, Vedran Podobnik, Gordan Jezic. Beyond the Internet of Things: The Social Networking of Machines. International Journal of Distributed Sensor Networks. 2016; 12 (6):1.
Chicago/Turabian StyleMarina Pticek; Vedran Podobnik; Gordan Jezic. 2016. "Beyond the Internet of Things: The Social Networking of Machines." International Journal of Distributed Sensor Networks 12, no. 6: 1.
The number of people who decide to share their photographs publicly increases every day, consequently making available new almost real-time insights of human behavior while traveling. Rather than having this statistic once a month or yearly, urban planners and touristic workers now can make decisions almost simultaneously with the emergence of new events. Moreover, these datasets can be used not only to compare how popular different touristic places are, but also predict how popular they should be taking into an account their characteristics. In this paper we investigate how country attractiveness scales with its population and size using number of foreign users taking photographs, which is observed from Flickr dataset, as a proxy for attractiveness. The results showed two things: to a certain extent country attractiveness scales with population, but does not with its size; and unlike in case of Spanish cities, country attractiveness scales sublinearly with population, and not superlinearly.
Iva Bojic; Stanislav Sobolevsky; Ivana Nizetic-Kosovic; Vedran Podobnik; Alexander Belyi; Carlo Ratti. Sublinear scaling of country attractiveness observed from Flickr dataset. 2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) 2015, 305 -308.
AMA StyleIva Bojic, Stanislav Sobolevsky, Ivana Nizetic-Kosovic, Vedran Podobnik, Alexander Belyi, Carlo Ratti. Sublinear scaling of country attractiveness observed from Flickr dataset. 2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). 2015; ():305-308.
Chicago/Turabian StyleIva Bojic; Stanislav Sobolevsky; Ivana Nizetic-Kosovic; Vedran Podobnik; Alexander Belyi; Carlo Ratti. 2015. "Sublinear scaling of country attractiveness observed from Flickr dataset." 2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) , no. : 305-308.
The paper presents software development model for implementation of communication and education applications based on Augmentative and Alternative Communication (AAC). Target user group of these applications are people with disabilities, specifically people with complex communication needs. Development process of such applications should follow specific principles to successfully implement all functional and accessible features that applications should contain in order to be accessible and highly usable. Furthermore, development process should be enriched with specific methodologies and approaches in its particular phases in order to fully exploit a necessary synergy of multidisciplinary team consisting of experts from information and communication technology, rehabilitation and education, psychology and graphic design. The presented model was defined during extensive developmental activities over two years period and evaluated on the number of publicly available case-study web and mobile AAC applications.
Jurica Babic; Ivan Slivar; Željka Car; Vedran Podobnik; Babic Jurica. Prototype-driven software development process for augmentative and alternative communication applications. 2015 13th International Conference on Telecommunications (ConTEL) 2015, 1 -8.
AMA StyleJurica Babic, Ivan Slivar, Željka Car, Vedran Podobnik, Babic Jurica. Prototype-driven software development process for augmentative and alternative communication applications. 2015 13th International Conference on Telecommunications (ConTEL). 2015; ():1-8.
Chicago/Turabian StyleJurica Babic; Ivan Slivar; Željka Car; Vedran Podobnik; Babic Jurica. 2015. "Prototype-driven software development process for augmentative and alternative communication applications." 2015 13th International Conference on Telecommunications (ConTEL) , no. : 1-8.
Vedran Podobnik; Ignac Lovrek. Implicit Social Networking: Discovery of Hidden Relationships, Roles and Communities among Consumers. Procedia Computer Science 2015, 60, 583 -592.
AMA StyleVedran Podobnik, Ignac Lovrek. Implicit Social Networking: Discovery of Hidden Relationships, Roles and Communities among Consumers. Procedia Computer Science. 2015; 60 ():583-592.
Chicago/Turabian StyleVedran Podobnik; Ignac Lovrek. 2015. "Implicit Social Networking: Discovery of Hidden Relationships, Roles and Communities among Consumers." Procedia Computer Science 60, no. : 583-592.