Mining Social Groups with Weighted Similarity in Campus Wireless Network

With the popularity of wireless networks and the prevalence of personal mobile computing devices, understanding the characteristic of wireless network users is of great significance to the network performance. In this study, system logs from two universities, Dartmouth College and Shanghai Jiao Tong University(SJTU), were mined and analyzed. Every user's log was represented by a user profile. A novel weighted social similarity was proposed to quantify the resemblance of users considering influence of location visits. Based on the similarity, an unsupervised learning method was applied to cluster users. Though environment parameters are different, two universities both form many social groups with Pareto distribution of similarity and exponential distribution of group sizes. These findings are very important to the research of wireless network and social network .

Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids,carbohydrates,and lipids,as well as protein synthesis from the consumed food,the liver has many diverse responsibilities and functions that are to be performed.Liver disease may impact the hormonal and nutritional balance in the human body.The earlier diagnosis of such critical conditions may help to treat the patient effectively.A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver.The proposed approach can recognize the abnormalities with better accuracy without training,unlike in supervisory procedures requiring considerable computational efforts for training.In the earlier stages,the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation.Then,the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted—Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information,which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts.It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%.The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.

The Social Group Distinction of Nationalists and Globalists amid COVID-19 Pandemic

The primary discussion in this article is the classification of the typical reactions of social groups in various nations as nationalist and globalist.Subject to the new coronavirus pandemic,nationalists have adopted extreme national security policies,namely,“the nation’s interests prevails;”globalists have adopted moderate policies by complying with the faith of society in the recommendations of the scientific community.The disparate contrasts in values and actions between the two groups are extensively manifested in domestic disease control,attitude toward the World Health Organization,identification of the disease’s source,vaccine research,international cooperation,and social reaction.This research indicates that nationalists largely consist of conservative country leaders,“social elites,”populists,and individuals in the middle-lower class,many of whom uphold racism and extreme nationalism,and that globalists largely consist of international organizations and regional leaders,medical practitioners,intellectuals andphilanthropic entrepreneurs,the middleupper class population.This social group distinction is clarified in accordance with converse ethical value perspectives,ideologies,social group-economic interests,and even national competition positions.Regarding cultural and institutional basics,nationalists uphold neoliberalism,social Darwinism,the law of jungle,and individualism,whereas globalists advocate for social democracy and collectivistic ethnic codes.The two parties have been competing for the high moral ground during and the pandemic,thereby profoundly affecting the relationships of nations worldwide.

大城市中低社会群体的居住边缘化趋势及其规划对策——以成都为例

As low and lower-middle social groups account for a great proportion of the total population in China and their status in society is special,it is of great social and practical significance to study their housing conditions and characteristics.Based on research at home and abroad,this paper defines the basic characteristics of low and lower-middle social groups in China,and elaborates the definition and connotation of housing marginalization,thereby proposing that these residents in the Chinese city are facing a problem of housing marginalization.According to data from the fifth and sixth population census and statistical yearbooks of Chengdu,it reveals changes in housing location,housing tenure structure,and housing quality of the study group between 2000 to 2010 by means of spatial and statistical analysis,which indicates that the low and lower-middle social groups are facing the three trends of"living in outskirts,""predicament in tenure selectivity of housing,"and"impoverishment of housing quality."In response to these trends,three planning suggestions are proposed:①to establish"housing policy areas"suitable for the group of residents to reside and work;②to innovate policy measures to support the low and lower-middle social groups to rent and purchase houses within these areas;③to guide the residents to integrate into the community life circle in these areas so as to avoid poverty concentration.

How New Individuals Behave in a Heterogeneous Community: A Computational Approach to Norm Assimilation Using Agent-Based Systems

Heterogeneous community entails a number of social groups that adopt similar/different social norms.In such community,new individuals who join a new social group should be able to decide with which group they could assimilate based on their capabilities/values/manners.Otherwise,they would be penalized by other members in the group for violating some norms which they cannot comply.Using this approach,software agents would have better reasoning in simulating human society.In this paper,the authors propose a norms assimilation theory,in which a new agent attempts to assimilate with a social group’s norms.This theory builds an approach to norm assimilation,analyzes the cases for an agent to decide to assimilate with a social group and develops a mathematical model to measure the assimilation cost and the agent’s ability.The approach is developed based on the agent’s internal belief about its ability and desire,and its external belief about the cost of assimilating with a number of social groups.The significance of this research is two-fold.Firstly,the study paves the way to future design of intelligent systems,i.e.,software agents or robots,to closely mimic human social interactions.Secondly,the norm assimilation using agent-based system could be potentially utilized to simulate some social issues such as immigrants,new students,expatriate etc.The experiments that have been conducted demonstrate that an agent in the domain is able to calculate the assimilation cost and decide which social group to join.

Morphology of quarters in traditional Arab Islamic city:A case of the traditional city of Damascus

Studies on the quarters of traditional Arab Islamic cities have stressed the idea of an urban structure that corresponds to social groupings and to a collection of local regions or even of,,inchoateM neighborhood units.This spatial model has often provided the rationale for the intervention in these cities and in the design of new housing layouts.This study aims to examine this issue through syntactic measures and observations to describe and analyze the structure and morphology of quarters through connectivity and visibility analysis of pedestrian move ment through space syntax.Whether the structure of these cities presents a global whole in contrast to the assumptions of physical subareas of social groupings is discussed.The city of Damascus is used as a model of analysis in which the urban morphology of quarters is described and characterized.This study reports several findings that are potentially relevant to the understanding of traditional laws that relate the physical layout of quarters to the social structure and their local subareas to the global whole that dominate and unify the parts.On this basis,the design approach in these cities may be better understood.

Travel behavior resilience:Theory,method,and empirical studies

Resilience studies have long been a focal point in the fields of geography,social science,urban studies,and psychology.Recently,resilience studies from multiple disciplines have scrutinized resilience at an individual scale.As one important behavior in the daily life of human beings,travel behavior is characterized by spatial dependence,spatiotemporal dynamics,and group heterogeneity.Moreover,how to understand the interaction between travel behavior(or demand)and transportation supply and their dynamics is a fundamental question in transportation studies when transportation systems encounter unexpected disturbances.This paper refines the definition of travel behavior resilience based on fundamental theories from multiple disciplines,including ecology,transportation engineering,and psychology.Additionally,this paper proposes a conceptual theoretical framework of travel behavior resilience based on the dynamic equilibrium characteristics of transportation supply and demand.In general,travel behavior has three stages of variation,namely,dramatic reduction,rapid growth,and fluctuation recovery,which have helped capture the travel behavior resilience triangle.Then,we construct a corresponding evaluation methodology that is suitable for multiscale and multidimensional perspectives.We emphasize that the evaluation of travel behavior resilience should be process-oriented with temporal continuity or capture the inflection points of travel behavior.Using multisource big data such as mobile phone signaling data and smart card data,this paper reviews empirical studies on travel behavior resilience,exploring its spatial heterogeneity and group differences.With location-based analysis,we confirm that people show greater travel behavior resilience in places where people engage in various socioeconomic activities.The group-based analysis shows that age and socioeconomic attributes of mobility groups significantly affect travel behavior resilience.Travel behavior resilience can be one pillar,offering geographic perspectives in resilience studies.In the future,the study of travel behavior resilience at multiple scales and from multiple perspectives can explore the spatial heterogeneity of transportation re-equilibrium and travel modal differences,contributing to urban spatial structure studies.Studying travel behavior resilience can provide scientific and technological support for urban management and resilient city construction.