A statistical study of the luminosity gap in galaxy groups

The luminosity gap between the two brightest members of galaxy groups and clusters is thought to offer a strong test for the models of galaxy formation and evolution. This study focuses on the statistics of the luminosity gap in galaxy groups, in particular fossil groups, e.g. large luminosity gap, in an analogy with the same in a cosmological simulation. We use spectroscopic legacy data of seventh data release (DR7) of SDSS, to extract a volume limited sample of galaxy groups utilizing modified friends-of-friends (mFoF) algorithm. Attention is paid to galaxy groups with the brightest group galaxy (BGG) more luminous than \Mr = -22. An initial sample of 620 groups in which 109 optical fossil groups, where the luminosity gap exceeds 2 magnitude, were identified. We compare the statistics of the luminosity gap in galaxy groups at low mass range from the SDSS with the same in the Millennium simulations where galaxies are modeled semi-analytically. We show that the BGGs residing in galaxy groups with large luminosity gap, i.e. fossil groups, are on average brighter and live in lower mass halos with respect to their counter parts in non-fossil systems. Although low mass galaxy groups are thought to have recently formed, we show that in galaxy groups with 15 galaxies brighter than $M_r\ge -19.5$, evolutionary process are most likely to be responsible for the large luminosity gap. We also examine a new probe of finding fossil group. In addition we extend the recently introduced observational probe based on the luminosity gap, the butterfly diagram, to galaxy groups and study the probe as a function of halo mass. This probe can, in conjunction with the luminosity function, help to fine tune the semi-analytic models of galaxies employed in the cosmological simulations.Comment: 11 pages, 11 figures, accepted to PASP journa

Omission of quality software development practices : a systematic literature review

Software deficiencies are minimized by utilizing recommended software development and quality assurance practices. However, these recommended practices (i.e., quality practices) become ineffective if software professionals purposefully ignore them. Conducting a systematic literature review (n = 4,838), we discovered that only a small number of previous studies, within software engineering and information systems literature, have investigated the omission of quality practices. These studies explain the omission of quality practices mainly as a result of organizational decisions and trade-offs made under resource constraints or market pressure. However, our study indicates that different aspects of this phenomenon deserve further research. In particular, future research must investigate the conditions triggering the omission of quality practices and the processes through which this phenomenon occurs. Especially, since software development is a human-centric phenomenon, the psychological and behavioral aspects of this process deserve in-depth empirical investigation. In addition, futures research must clarify the social, organizational, and economical consequences of ignoring quality practices. Gaining in-depth theoretically sound and empirically grounded understandings about different aspects of this phenomenon enables research and practice to suggest interventions to overcome this issue.fi=vertaisarvioitu|en=peerReviewed

Building Climate Resilience in Smart Cities Using Open Data Services

Climate change and its consequences are among modern societies' most critical challenges. To that end, cities have focused on using information technology in their climate mitigation efforts in smart cities. Considering the magnitude of the problem and its impact on our societies, the need for building climate-resilient smart cities is crucial. In this study, we aim to understand how smart cities can achieve climate resilience. Conducting an exploratory field study and using the urban climate resilience framework as a theoretical lens, we suggest that smart cities can leverage the potential of open data and citizen engagement to reach climate resilience. In particular, our results show that building climate-resilient cities requires structural changes in citizen engagement processes and climate considerations. To that end, open data services and tools can be used to improve citizen engagement processes and develop more sustainable smart city solutions

DATA MONETIZATION CHALLENGES IN ESTABLISHED ORGANIZATIONS: A SYSTEMATIC LITERATURE REVIEW

Over the last decades, researchers and practitioners have looked at data as a valuable asset for improving business processes in organizations. However, nowadays, they see data more as a tradable asset that can be monetized. Data monetization here refers to generating revenue from selling data and data-based products and services. Despite providing opportunities for generating new revenue streams, data monetization is not without challenges, especially in established organizations. Previous research shows that an organization’s data monetization capability is constrained by its existing business model, infrastructure, and organizational culture. Although Information Systems (IS) research and practice have shown an increasing interest in data monetization, we lack a thorough understanding of its challenges. As a first step in addressing this gap, we set out to identify challenges that established organizations face in monetizing their data. To that end, we conducted a systematic literature review and identified 21 challenges reported in the extant literature. Based on their nature, we divided these challenges into five categories, including business model, legal & regulatory, security & privacy, organizational, and data management challenges. Our study has several implications for IS research and practice

Team performance and large scale agile software development

Software development is a team work and largely dependent on open social interaction and continuous learning of individuals. Drawing on well established theoretical concepts proposed by social psychology and organizational science disciplines, we develop a theoretical framework proposing that team climate has a significant influence on team learning and ultimately affects team performance. Our study consists of two goals. First to understand the preconditions of team learning and second to investigate the relationship between team learning, psychological safety, and team performance in large scale agile software development projects. We plan to conduct a survey with software professionals in Sweden from three companies partners in pur large-scale agile research project.Comment: 6 pages, 1 figure, conference, ESEM, Register Repor

Fast and Efficient Lenslet Image Compression

Light field imaging is characterized by capturing brightness, color, and directional information of light rays in a scene. This leads to image representations with huge amount of data that require efficient coding schemes. In this paper, lenslet images are rendered into sub-aperture images. These images are organized as a pseudo-sequence input for the HEVC video codec. To better exploit redundancy among the neighboring sub-aperture images and consequently decrease the distances between a sub-aperture image and its references used for prediction, sub-aperture images are divided into four smaller groups that are scanned in a serpentine order. The most central sub-aperture image, which has the highest similarity to all the other images, is used as the initial reference image for each of the four regions. Furthermore, a structure is defined that selects spatially adjacent sub-aperture images as prediction references with the highest similarity to the current image. In this way, encoding efficiency increases, and furthermore it leads to a higher similarity among the co-located Coding Three Units (CTUs). The similarities among the co-located CTUs are exploited to predict Coding Unit depths.Moreover, independent encoding of each group division enables parallel processing, that along with the proposed coding unit depth prediction decrease the encoding execution time by almost 80% on average. Simulation results show that Rate-Distortion performance of the proposed method has higher compression gain than the other state-of-the-art lenslet compression methods with lower computational complexity

Kinematic Analysis of the Triangle-Star Robot with Telescopic Arm and Three Kinematics Chains as T-S Robot (3-PRP)

In this chapter, the limitations and weaknesses of the motion geometry and the workspace of Triangle-Star Robot {T-S (3-PRP)} are diagnosed after research and consideration of the issues at hand. In addition, they are offered in index form. To remove the problems with the abovementioned cases, at first, a robot with telescopic arms and a similar kinematics chain is rendered to give a kinematics analysis approach like Hartenberg-Denavit. Furthermore, in order to increase the workspace, Reuleaux Triangle-Star Robot {RT-S (3-PRP)} with kinematics chains 3-PRP and Circle-Star Robot{C-S (3-PRP)} with kinematics chains 3-PRP and a new improved structure are introduced

Postural and Musculoskeletal Disorders in Women with Urinary Incontinence: A Research Report

Introduction: To investigate and compare the prevalence of some postural and musculoskeletal disorders in women with and without Urinary Incontinence (UI). Urinary Incontinence (UI) is one of the most important social and health problems in women. Limited studies have shown that UI prevalence is around 35%-55% in Iran. Nevertheless, to the best of our knowledge, there is no exact and reliable data reported in the literature on the prevalence of musculoskeletal, postural, or other related disorders in UI patients in Iran. Methods and Materials: The current study was conducted based on the data obtained from 166 incontinent and 90 continent women attending Vali-e-Asr University Hospital between 2010 and 2012. After collecting participants’ demographic information, postural status was assessed. In addition, we measured values for pelvic inclination and lumbar lordosis angles. Finally, vaginal tone and pelvic floor muscle strength and endurance were evaluated. Kolmogorov-Smirnov (K-S) goodness-of-fit, Independent t, X2, and Pearson correlation tests were used for the purposes of data analysis. Results: The prevalence of low back pain, chronic pelvic pain, and pelvic asymmetry were significantly higher in incontinent women compared with that in continent women (p<0.05). It was found that lumbar lordosis was significantly different between the two groups (P=0.021); however, no significant difference was observed regarding pelvic inclination (P=0.20). Conclusion: The present study confirms the hypothesis that incontinent women have higher prevalence of low back and pelvic pain and pelvic asymmetry. It is recommented that further epidemiologic and comprehensive etiologic investigations be conducted on these findings.Keywords: Urinary Incontinence, Posture, Musculoskeletal Disorders, Wome

Motion estimation with chessboard pattern prediction strategy

Due to high correlations among the adjacent blocks, several algorithms utilize movement information of spatially and temporally correlated neighboring blocks to adapt their search patterns to that information. In this paper, this information is used to define a dynamic search pattern. Each frame is divided into two sets, black and white blocks, like a chessboard pattern and a different search pattern, is defined for each set. The advantage of this definition is that the number of spatially neighboring blocks is increased for each current block and it leads to a better prediction for each block. Simulation results show that the proposed algorithm is closer to the Full-Search algorithm in terms of quality metrics such as PSNR than the other state-of-the-art algorithms while at the same time the average number of search points is less.info:eu-repo/semantics/publishedVersio