New Releases by Dan Wang

My dissertation explores how skilled return migrants adapt the expertise they gained working abroad to workplaces in their home countries with data from an original survey of 4,183 skilled returnees from 81 countries, who had worked abroad in the U.S. First, I find that whether returnees are successful at transferring knowledge depends less on their individual ability and more on features of the professional environments in their home countries. Also, returnees who are effective brokers of knowledge bring back ideas about management practices more than they do technical knowledge. Third, returnees are more likely to become entrepreneurs if they have strong local ties to their home countries, the effect of which is stronger in countries with already high rates of self-employment. Finally, the very returnees who are most successful as knowledge brokers are also most likely to venture abroad again. These findings challenge the conventional notion of return migrants as agents of economic transformation, suggesting that many institutional challenges stand in the way of their ability to broker resources across borders.

Obesity is a major health problem for both adults and children. It is particularly important for college students to focus on weight management due to weight persistence from adolescent to adult. This study analyzes the influence of peer effects and menu labeling on calorie intake at a university dining hall with posted nutrition facts. Data were collected at the Citrus Dining Hall on Polytechnic Campus of Arizona State University by means of a questionnaire. Groups of four members each were interviewed for a total of 112 individual observations. The results show that individuals who are dining in a group with at least one obese member consume more calories. Also food-related interactions in a group influence the amount of calorie consumption regarding pizza and interactions in a group influence the amount of calorie consumption regarding pizza and pasta. Looking at nutrition facts when ordering the food decreases the amount of calories but the effects of menu labeling on calorie intake are not amplified through peer effects. The strength of ties indicated by closeness does not significantly influence calorie intake. There is a need for future research in which more approaches related to social networks need to be tested regarding healthy diets.

"The contexts of family and peer group play critical roles in shaping children''s lives over their development. Biological theory suggests that these two contexts are interlinked to impact children''s daily lives and should be examined in integrated models. The present study examined relationship quality with peers as a potential mediator that links maternal parenting style to children''s school adjustment. Two dimensions of parenting style--maternal responsiveness and behavioral control, and three aspects of school adjustment--academic grades, problem behaviors in the school setting, and school related experiences of stress, were investigated. The mediation models were tested concurrently and longitudinally in a sample of 347 children during their 4th to 5th grades. Biological theory also suggests personal characteristics as one of the defining factors that influence developmental outcomes. Thus, child gender and child ethnicity were included as moderators in the proposed models. /DISS_para DISS_paraUsing multiple regressions, results of the study indicated both dimensions of maternal parenting style and peer relationship quality were linked to children''s well-being at school concurrently. Surprisingly, peer relationship quality was unassociated with behavioral problems. Short-term longitudinal associations were found between behavioral control and GPA and between responsiveness and school related stress. In terms of mediation, only maternal responsiveness had indirect effects on one of children''s outcome variables via its influence on peer relationships concurrently. Also, moderation effects were not found in the proposed mediation models."--Abstract from author supplied metadata.

This paper investigates the impact of early relationships on entrepreneurial firm innovation. Prior research has largely focused on the benefits of network ties, documenting the many advantages that accrue to firms embedded in a rich network of inter-organizational relationships. In contrast, we build on competitive interaction research to consider potential drawbacks and emphasize how competitive exposure, enabled by powerful intermediaries, can inhibit innovation. We develop a conceptualization of information leakage that occurs when firms are indirectly tied to their competitors through these shared intermediary organizations. To test our theory, we examine every relationship between entrepreneurial firms and their venture capital investors in the minimally invasive surgical segment of the medical device industry over a 22 year period. The theory and evidence provide novel insights for entrepreneurship research while contributing to the literatures on innovation and competition through networks.

Leverage effect has become an extensively studied phenomenon which describes the negative relation between the stock return and its volatility. Although this characteristic of stock returns is well acknowledged, most studies about it are based on cross-sectional calibration with parametric models. Other than that, most previous work are over daily or longer return horizons and usually do not specify the quantitative measure of it. This paper provides nonparametric estimation of a class of stochastic measures of leverage effect for both cases with and without microstructure noise, and studies the statistical properties of the estimators when the log price process is a quite general continuous semimartingale, in the stochastic volatility context and for high frequency data. The consistency and limit distribution of the estimators are derived, and simulation results present the properties accordingly. This estimator also provides the opportunity to study the empirical relation between skewness and leverage effect, which further leads to the prediction of skewness. Furthermore, adopting similar ideas to these in this paper, it is easy to extend the study to other important aspects of the stock returns, e.g. volatility of volatility.

The educational system in China is marked by its dramatic inequality between rural and urban schools. The challenges facing rural schools are usually understood as disadvantages in funding, facilities, and staffing, which consequently result in undesirable student performance in general. This book, however, penetrates these phenomena on the surface and brings forth a much deeper moral crisis in rural education, a crisis that is entrenched in the complicated interlocking of formal and informal institutions within and beyond the school. The Demoralization of Teachers describes the work and workplace in a rural school from the perspective of teachers who were working there. It faithfully depicts the lamentable state of teachers’ work morale in the school and, little by little as if a detective story, reveals the reasons for the teachers’ demoralization by vivid narratives. The book demonstrates the profound impact on the meanings of teaching exerted by the state curriculum reform, the formal and informal norms and regulations in the school, and the erosion of moral integrity in the state bureaucracy and the society at large. The crisis in the rural school stops to be a “rural” or educational problem in nature, but mirrors the societal-wide transformation in political economy as well as in ideology in the current reform China. The sheer complexity of the moral crisis in this ethnography calls for renewed efforts to identify and investigate the educational problems in rural China from fresh theoretical perspectives that situate rural education in broader historical and social contexts and processes.

My dissertation explores how skilled return migrants adapt the expertise they gained working abroad to workplaces in their home countries. To study this, I conducted a survey of 4,183 skilled returnees from 81 countries, who had worked abroad in the U.S., as well as 161 interviews with skilled returnees from 25 countries. The respondent pool came from U.S.''s largest organizational sponsor of J1 Visas for professionals. As the largest survey of skilled return migrants ever compiled, the dataset includes information on the respondents'' career histories, attitudes, and work activity. My data analysis generated three main findings. One, less than half of the respondents report implementing some aspect of their professional knowledge gained overseas in the workplaces of their home countries. Whether returnees are successful channels of cross-border knowledge depends less on their ability to demonstrate or articulate novel ideas and more on the normative conditions of the professional environments in their home countries. Two, returnees who are effective brokers of knowledge bring back ideas about organizational and management practices, such as new methods of training, more than they do technical knowledge. Three, returnees are more likely to venture into self-employment if they have strong local ties to their home countries; moreover, the effect of these local ties on entrepreneurial transitions is stronger for returnees in home countries with high rates of self-employment. Finally, I show that the very returnees who are most successful as knowledge brokers are also most likely to venture abroad again. Thus, the returnees who could benefit their home countries the most are also the least like to stay. These findings challenge the conventional notion of return migrants as agents of economic transformation, suggesting that many institutional and cultural challenges stand in the way of their ability to broker knowledge and resources across country borders. This work also ties contributes to theoretical perspectives on international migration, organizational learning, social networks, and the sociology of knowledge.

ABSTRACT Smartphones appear to perfectly match travelers'' needs due to their portability and easy access to the Internet. The current literature in management information systems (MIS), communication, marketing, and tourism provides a basic foundation with which to understand the adoption and use of information communication technology (ICT) such as smartphones. However, a critical review of this literature indicates that there is a need to develop a much richer theoretical framework that describes the use of smartphones for travel. In particular, our understanding of the use of smartphones for travel is largely established from a quantitative perspective method, and as such, it is argued that this perspective cannot provide an in-depth understanding of the mechanisms that affect the use of smartphones in travel which, in turn, shapes the travel experience. That is, it appears that there is a lack of integration of the various models describing the nature of the use of ICT in travel. Additionally, it is argued that the processes shaping the use of technology which were developed in the organizational settings have been inappropriately applied at the individual level, and therefore should be critically examined within the travel context. The overall goal of this dissertation is to develop a theoretical framework describing the mechanisms shaping the use of smartphones for travel, and can be addressed by answering the following questions: (1) What are the uses of smartphones in the context of travel? (2) What are the factors influencing the use of smartphones in the context of travel? And, (3) What are the mechanisms shaping the use of smartphones for travel (i.e. How are the factors working to shape the use of smartphones in travel context?). A phenomenological approach was used to answer these questions as quantitative methods are believed to be inadequate in describing the processes underlying the use of smartphones for travel. Twenty-four Americans who own one kind of smartphones and traveled at least once for leisure purpose in the most recent three months were interviewed extensively to gain an in-depth understanding of their uses of smartphones and resulting travel experience. Qualitative content analysis was used to analyze the interview transcripts, and data triangulation based upon a series of follow-up interviews and member check was used to ensure the trustworthiness of the interpretation. This study identified four categories of uses of smartphones for travel (including 25 unique activities) including the uses of smartphones for communication, entertainment, facilitation, and information search. Five sets of factors that are associated with the use of smartphones for travel were identified from both contexts of travel and everyday experience. Three sets of factors that directly lead travelers to use smartphones for travel are travelers'' motivations to use smartphones as a tool to achieve some purposes, their cognitive beliefs toward the use of smartphones, and other situational facilitators (e.g. no computer access) that lead the informants to use smartphones rather than any other alternative ways. Besides the three sets of direct factors, the informants indicated that their use of smartphones changed their travel experience. More important, the everyday use of smartphones and the changes brought to people''s lives appear to be indirect factors influencing the use of smartphones for travel. These results describing smartphone''s uses, outcomes and the mechanisms shaping this behavior were used as the primary basis in proposing a theoretical framework describing the use of smartphones for travel including its antecedents, process, and outcomes. The theoretical framework suggests four propositions. First, the underlying processes shaping the use of smartphones for travel is a process of appropriation in which a person "makes it his/her own" whereby the smartphone user learns, adjusts, and internalizes the `essence'' of the smartphone based on their uses in everyday context as well as previous travel experiences (Proposition 1). Second, the use of smartphones in everyday context lead to the changes of communication, information consumption, and the uses of other digital devices, and these changes influenced the use of smartphones for travel through transformation effect and spillover effect (Proposition 2). Third, the changes in everyday experience influence the use of smartphones for travel by influencing traveler''s motivations in the context of travel (Proposition 3). Finally, this study indicates that the appropriation process leads to changes in the travel experience. In particular, people change their travel activities including pre-trip planning, en-route arrangements, after-trips activities as well as their interpretations toward trips and sensations (Proposition 4). This study clearly delineates the relationships between use of smartphones and the impact of this use on travel behavior, and suggests several new perspectives with which to study the impact of technology on travel. First, this study indicates that a systems view should be adopted in tourism studies. Travelers are not isolated from their daily lifestyles, personalities, social connections, and other individual background (e.g. knowledge, preferences, etc.). As such, the behavior of travelers cannot be understood without consideration of the influence of other settings. Therefore in tourism studies, a systems perspective is important so as to reflect the intimate relationships (and influences) of the various `subsystems. Second, this study suggests a dynamic view for studies of technology and travel. The results of this study indicate that the uses of smartphones in travel are shaped by the interactions of a variety of factors. Therefore, in the studies of technology and travel it is important to understand the dynamic processes which shape the use of technology for travel. Third, this study suggests a development view for the study of technology and travel. This perspective includes not only the recognition that adoption of new technology may influence travelers and travel experience, but also the evolving use of the new ICT tools (e.g. smartphones) along with the development of these tools may substantially change travelers'' behavior and travel experience. Additionally, this study suggests a new perspective is needed regarding the concept of travel experience in that the use of smartphones reconfigures the current relationships between travelers, space, and time and as such, implies that the conceptualization of travel experience should go beyond the argument of the dichotomy of everyday life and travel and evolve with the development of information technology. This study also offers several managerial implications in the areas of mobile marketing, destination marketing and management, and the design of travel information services on the smartphones platform.

Recent breakthroughs in deep learning have made possible the learning of deep layered hierarchical representations of sensory input. Stacked restricted Boltzmann machines (RBMs), also called deep belief networks (DBNs), and stacked autoencoders are two representative deep learning methods. The key idea is greedy layer-wise unsupervised pre-training followed by supervised fine-tuning, which can be done efficiently and overcomes the difficulty of local minima when training all layers of a deep neural network at once. Deep learning has been shown to achieve outstanding performance in a number of challenging real-world applications. Existing deep learning methods involve a large number of meta-parameters, such as the number of hidden layers, the number of hidden nodes, the sparsity target, the initial values of weights, the type of units, the learning rate, etc. Existing applications usually do not explain why the decisions were made and how changes would affect performance. Thus, it is difficult for a novice user to make good decisions for a new application in order to achieve good performance. In addition, most of the existing works are done on simple and clean datasets and assume a fixed set of labeled data, which is not necessarily true for real-world applications. The main objectives of this dissertation are to investigate the optimal meta-parameters of deep learning networks as well as the effects of various data pre-processing techniques, propose a new active labeling framework for cost-effective selection of labeled data, and apply deep learning to a real-world application--emotion prediction via physiological sensor data, based on real-world, complex, noisy, and heterogeneous sensor data. For meta-parameters and data pre-processing techniques, this study uses the benchmark MNIST digit recognition image dataset and a sleep-stage-recognition sensor dataset and empirically compares the deep network''s performance with a number of different meta-parameters and decisions, including raw data vs. pre-processed data by Principal Component Analysis (PCA) with or without whitening, various structures in terms of the number of layers and the number of nodes in each layer, stacked RBMs vs. stacked autoencoders. For active labeling, a new framework for both stacked RBMs and stacked autoencoders is proposed based on three metrics: least confidence, margin sampling, and entropy. On the MINIST dataset, the methods outperform random labeling consistently by a significant margin. On the other hand, the proposed active labeling methods perform similarly to random labeling on the sleep-stage-recognition dataset due to the noisiness and inconsistency in the data. For the application of deep learning to emotion prediction via physiological sensor data, a software pipeline has been developed. The system first extracts features from the raw data of four channels in an unsupervised fashion and then builds three classifiers to classify the levels of arousal, valence, and liking based on the learned features. The classification accuracy is 0.609, 0.512, and 0.684, respectively, which is comparable with existing methods based on expert designed features.

The functional effects of mutations associated with cardiomyopathies generally suggest that the Ca2 responsiveness of the myofilament was affected. This functional change appears to be independent of which protein contains the mutation and therefore indicates that the altered Ca2 sensitivity could be a critical or causative component of disease expression and progression. However, the correlation underlying this functional change with the disease phenotype is still unclear. Thus, in this work a series of single amino acid-substituted cardiac troponin C (cTnC) variants with altered Ca2+ binding affinities were studied to determine how they influence the Ca2+ activation pathway in myofilament contraction and whether this change in Ca2+ binding will result in adaptive changes in intact cardiomyocytes. These variants have not been identified as associated with any cardiomyopathies and therefore may eventually provide clues as to whether altered Ca2+ signaling of myofilament contraction is causal or an adaptive response in diseased hearts. Firstly, we sought structural and mechanistic explanations for the increased/decreased Ca2+ sensitivity of contraction for the cTnC variants using an array of biophysical techniques. The properties of these cTnC variants were characterized by determining their effects on Ca2+ binding ability, cTnC-cTnI interaction and their modulation by PKA phosphorylation in solution, and their structural alterations using molecular dynamic simulations. We found that cTnC variants have different effects on both binding of Ca2+ and cTnI to cTnC, and they also respond differently upon PKA phosphorylation. MD simulations show, for the first time, that cTnC variants could disrupt crucial hydrophobic interactions so that the closed form of cTnC or the Ca2+ binding loop is destabilized. The findings emphasize the importance of the regulatory domain of cTnC''s conformation in the regulation of contraction and suggest that mutations in cTnC that alter myofilament Ca2+ sensitivity can do so by modulating Ca2+ and cTnI binding. Secondly, the functional capacity of the Ca2+ desensitizing variants was characterized by expressing them in cardiomyocytes using adenovirus. Additionally, we demonstrate that engineered cTnC variants can correct the disease-induced abnormal Ca2+ binding sensitivity. Our study provides insights for the development of novel therapeutic strategies for the treatment of cardiomyopathies.

Minimally invasive technique (MIS) revolutionized the field of surgery for its shorter hospitalization time, lower complication rates, and ultimately reduced morbidity and mortality. However, one of the critical challenges that prevent it from reaching the full potentials is the restricted visualization from the traditional monocular camera systems at the presence of tissue deformations. This dissertation aims to design a new approach which can provide the surgeons with real time 3D visualization of complete organ deformations during the MIS operation. This new approach even allows the surgeon to see through the wall of an organ rather than just looking at its surface. The proposed design consists of two stages. The first training stage identified the deformation subspaces from a training data set in the transformed spherical harmonic domain, such that each surface can be sparsely represented in the structured dictionary with low dimensionality. This novel idea is based on our experimental discovery that the spherical harmonic coefficients of any organ surface lie in specific low dimensional subspaces. The second reconstruction stage reconstructs the complete deformations in real-time using surface samples obtained with an optical device from a limited field of view while applying the structured dictionary. The sparse surface representation algorithm is also applied to ultrasound image enhancement and efficient surgical simulation. The former is achieved by fusing ultrasound samples 5 with optical data under proper weighting strategies. The high speed of surgical simulation is obtained by decreasing the computational cost based on the high compactness of the surface representation algorithm. In order to verify the proposed approaches, we first use the computer models to demonstrate that the proposed approach matches the accuracy of complex mathematical modeling techniques. Then ex-vivo experiments are conducted on freshly excised porcine kidneys utilizing a 3D MRI machine, a 3D optical device and an ultrasound machine to further test the feasibility under practical settings.

With the emergence of multinational enterprises (MNEs) from the People''s Republic of China, Chinese expatriates are increasingly being posted overseas to manage international assignments. It has been reported that expatriates often face significant challenges in understanding the host culture, which negatively impact on their performance overseas. Thus the importance of cross-cultural competence (CCC) has been emphasized as it may assist expatriates to successfully manage the local workforce. The theoretical underpinnings of CCC are socio-analytic theory and social learning theory. Socio-analytic theory explains the role personality plays in leading to discrepant performance on international assignments, whilst social learning theory emphasizes the role of learning in developing cross-cultural skills. However, both theories are developed from a developed country context, and the transferability of those theories to emerging markets has not been examined. In order to address the theoretical deficiencies of CCC, this study explores expatriates from a large and significant emerging economy, namely, China. The broad research problem addressed is "how to develop CCC of Chinese expatriate managers in Chinese MNEs'' overseas operations".In particular, this study investigates antecedents of CCC including personal attributes (Research question 1a) and personal skills (Research question 2a), as well as how these antecedents contribute to CCC (Research question 1b, 2b). A qualitative research design was adopted due to the exploratory nature of the study, and 50 in-depth interviews were conducted to gather information. The sample comprised 25 Chinese expatriate managers, 15 foreign colleagues, and 10 expatriate supervisors or cross-cultural consultants. The respondents selected were based on criteria for each group. For instance, the criteria for expatriate managers include working experience (i.e., working on overseas assignments for at least six months) and location (i.e., working in both developed and developing countries). The snowballing techniques were used to recruit appropriate respondents.The findings of this study lead to the development of a theoretical model of CCC, which highlights the cultural-embedded factors as important antecedents. In addition to confirming CCC antecedents of Chinese expatriates that are similar to those for Western expatriates (i.e., openness, communication skills, interpersonal skills, perceptual skills), two new cultural-embedded factors were also identified, including endurance and coordination skills. More importantly, the findings demonstrate that cross-cultural contexts play an important role in how certain antecedents function in different situations. A range of institutional factors have been identified which are able to influence perceptions of expatriates and local employees on CCC antecedents, including ambiguous or sophisticated regulation systems, relationship-based or rule-based corporate governance, supervisor-subordinate relationships and work-life relationships. This study advances the theoretical development of CCC by integrating institutional theory with socio-analytic theory and social learning theory, which leads to a more comprehensive explanation of CCC. It also highlights significant methodological and practical implications for future expatriate studies and international human resource management in Chinese MNEs.

Fecal pollution is a primary concern for recreational water bodies in US. The current water quality criteria are based on the cultivability of fecal indicator bacteria like E. coli and enterococci. These indicators are ubiquitous in the digestive tract of warm-blooded animals but are also known to persist and even multiply in the environment given favorable conditions. Hence their presence does not provide information on the sources of fecal contamination. In the past decade microbial source tracking (MST), the research area that uses host-specific microbes to identify the sources of fecal pollution, has undergone rapid development. A brief historical overview is provided in Chapter 1 and state-of-the art methods are presented and analyzed in Chapter 2. Quantitative PCR (qPCR)-based MST methods have been widely used for two reasons: they can detect both cultivable and uncultivable microbes and their process time is shorter comparing to other MST methods. The results from qPCR reactions need to be further processed to achieve quantitative MST because of analytical complications caused by the environmental water matrix. Two of the most important aspects will be addressed in Chapters 3 and 4. Chapter 3 attempts to solve the imperfect specificity and sensitivity of the qPCR assays with a statistical procedure that evaluates the impact of false positive/negative information. Chapter 4 addresses the inaccuracy in qPCR data analysis caused by the high noise signal and inconsistent amplification efficiency frequently seen in environmental water samples. Corrective measures are proposed to improve the accuracy of estimated DNA concentrations.

Finally we discuss the convergency of the discretisation schemes of the stochastic processes encountered in the Monte Carlo simulations. Under some regularity conditions, we give a partial strong convergency result for the stochastic volatility process. Moreover, we give a strong convergency result for the mean-reverting CEV process.

China is booming, not only in its rapidly growing economy, but also through innovation in decorative and fine arts, interior design and architecture. This is the first major survey of the new directions in style and design taken by the architects, designers and homeowners of China''s leading urban centres. China Contemporary showcases 35 examples of the new wave of Chinese design through the stunning photography of Michael Freeman and the perceptive commentary and interviews of Chinese journalist Xiao Dan Wang.

Poly(dimethylsiloxane) (PDMS) and similar polymers have proved to be of widespread interest for use in microfluidic and similar microanalytical devices. Surface modification of PDMS is required to extend the range of applications for devices made of this polymer, however. Here we report on the grafting of perfluorooctyltriethoxysilane via hydrolysis onto an oxidized PDMS substrate in order to form a fluorinated microchannel. Such a fluorinated device could be used for separating fluorous tagged proteins or peptides, similar to that which has been recently demonstrated in a capillary electrophoresis system, or in an open tubular capillary column. The modified polymer is characterized using chemical force titrations, contact angle measurements and X-ray photoelectron spectroscopy (XPS). We also report on a novel means of performing electroosmotic measurements on this material to determine the surface zeta potential. As might be expected, contact angle and chemical force titration measurements indicate the fluorinated surface to be highly hydrophobic. XPS indicates that fluorocarbon groups segregate to the surface of the polymer over a period of days following the initial surface modification, presumably driven by a lower surface free energy. One of the most interesting results is the zeta potential measurements, which show that significant surface charge can be maintained across a wide range of pH on this modified polymer, sufficient to promote electroosmotic flow in a microfluidic chip. Matrix-assisted time of flight mass spectrometry (MALDI-TOF MS) measurements show that a fluorous-tagged peptide will selectively adsorb on the fluorinated PDMS in aqueous solution, demonstrating that the fluorinated polymer could be used in devices designed forenrichment or enhanced detection of fluorous-labeled proteins and peptides. However, the non-specific adsorption of other proteins may interfere with the test results. The adsorption of four different proteins (cytochrome-C, carbonic anhydrase, insulin and ubiquitin) onto the unmodified, oxidized and fluorinated PDMS surfaces respectively was studied here with MALDI-TOF MS measurements. The results showed us that when rinsed in water/methanol solutions of high methanol concentration, cytochrome-C strongly adheres to the fluorinated surface. Carbonic anhydrase shows the opposite trend. Retention of ubiquitin on the surface shows relatively little sensitivity to either the nature of the substrate or the solution composition. Finally, the results using insulin demonstrated that this protein adheres relatively strongly to the oxidized PDMS surface as compared to the fluorinated or unmodified PDMS and showed a relative independence on the composition of the washing solution. The influence of the hydrophilicity of the protein, the surface and solvents, stability and size of proteins are discussed in the context of these observations.

This dissertation addresses the issues around the technology and cost structure in commercial banking industries in both industrialized economy (US) and transitional economy (China). In addition, internal and external factors that affect bank performance, in terms of technical change, technical efficiency and total factor productivity, are examined to provide policy and business implications to regulatory authorities and banking managers.

Recently, it has come to be generally believed by academia and industry alike that the sensor network will have a key role to extend the reachability of the next generation Internet. A key characteristic of this network is that there is no single node in the network that is powerful enough to perform the assigned tasks. An application should be served via the cooperation of several nodes or even the entire network. The network serves as an information base, and is data driven, as opposed to a provider for the point-to-point connection. The main challenge of this network is huge information organization, including information storage, searching and retrieval, especially in a continuous way. There are many specific and interrelated problems. We list a few examples. First, data accuracy: the correctness of the sensor network to represent the properties of the sensor field. Second, data search and retrieval delay; while low delay is always preferred, various applications have different delay constraints. Third, overhead; low transmission overhead is often the main consideration in system design, as it is directly related to the usage of energy, the most severely limited resource for sensors. In this thesis, we first discuss load balanced sensor coverage, which provides a lower layer support for long run sensor data collection. We then concentrate on how to balance the parameters in data collection of the sensor networks, so that the user queries and applications can be satisfied with reasonable delay and low overhead. Based on different application specifics, we try to use a smaller number of sensors, less number of transmissions by exploring historical and topological information, coding techniques and data distribution information. Our analysis and experimental results show that our architecture and algorithms provide both theoretical and practical insights for sensor network design and deployment.