Predictors of client retention in alternative -to -prison substance abuse programs

Increased treatment retention among substance abusing individuals has been associated with reduced drug use, fewer arrests, and decreased unemployment, as well as a reduction in health risk behaviors. This longitudinal study examined the predictors of client retention for alternative to prison substance abuse treatment programs through assessing the roles of motivational factors and the client-worker relationship. The sample was comprised of 141 male felony offenders who were legally mandated to community based long-term residential drug treatment programs. ^ The primary measures used in the study were the consecutive days a participant remained in treatment, Stages of Change Readiness Model and Treatment Eagerness Scale (SOCRATES), the Working Alliance Inventory (WAI), and The Readiness Ruler. Hierarchical multiple regression analysis was conducted for four hypotheses (a) participants who are more motivated to change at the time of entry will remain in treatment longer, (b) participants who have a strong therapeutic alliance will remain in treatment a greater number of consecutive days than participants who have weaker therapeutic alliance, (c) motivation to change, as measured at treatment entry, will be positively related to therapeutic alliance, (d) during the course of treatment variation in motivation to change will be predicted by the therapeutic alliance. ^ Results support the following conclusions: Among clients in alternative-to prison programs the number of days in treatment is positively related to their motivation to change. The therapeutic alliance is not a predictor of the number of days in treatment. Motivation to change, particularly recognition of a drug problem, is positively related to the therapeutic alliance. Changes in motivation to change in response to treatment are positively related to the therapeutic alliance among clients in an alternative to prison substance abuse treatment programs. These results carry forward prior research and have implications for social work practice, research, and social welfare policy. ^

Development of a new client -server architecture for context aware mobile computing

This dissertation studies the context-aware application with its proposed algorithms at client side. The required context-aware infrastructure is discussed in depth to illustrate that such an infrastructure collects the mobile user’s context information, registers service providers, derives mobile user’s current context, distributes user context among context-aware applications, and provides tailored services. The approach proposed tries to strike a balance between the context server and mobile devices. The context acquisition is centralized at the server to ensure the reusability of context information among mobile devices, while context reasoning remains at the application level. Hence, a centralized context acquisition and distributed context reasoning are viewed as a better solution overall. The context-aware search application is designed and implemented at the server side. A new algorithm is proposed to take into consideration the user context profiles. By promoting feedback on the dynamics of the system, any prior user selection is now saved for further analysis such that it may contribute to help the results of a subsequent search. On the basis of these developments at the server side, various solutions are consequently provided at the client side. A proxy software-based component is set up for the purpose of data collection. This research endorses the belief that the proxy at the client side should contain the context reasoning component. Implementation of such a component provides credence to this belief in that the context applications are able to derive the user context profiles. Furthermore, a context cache scheme is implemented to manage the cache on the client device in order to minimize processing requirements and other resources (bandwidth, CPU cycle, power). Java and MySQL platforms are used to implement the proposed architecture and to test scenarios derived from user’s daily activities. To meet the practical demands required of a testing environment without the impositions of a heavy cost for establishing such a comprehensive infrastructure, a software simulation using a free Yahoo search API is provided as a means to evaluate the effectiveness of the design approach in a most realistic way. The integration of Yahoo search engine into the context-aware architecture design proves how context aware application can meet user demands for tailored services and products in and around the user’s environment. The test results show that the overall design is highly effective, providing new features and enriching the mobile user’s experience through a broad scope of potential applications.

Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Proton Form Factor Puzzle and the CEBAF Large Acceptance Spectrometer (CLAS) two-photon exchange experiment

The electromagnetic form factors are the most fundamental observables that encode information about the internal structure of the nucleon. The electric (GE) and the magnetic ( GM) form factors contain information about the spatial distribution of the charge and magnetization inside the nucleon. A significant discrepancy exists between the Rosenbluth and the polarization transfer measurements of the electromagnetic form factors of the proton. One possible explanation for the discrepancy is the contributions of two-photon exchange (TPE) effects. Theoretical calculations estimating the magnitude of the TPE effect are highly model dependent, and limited experimental evidence for such effects exists. Experimentally, the TPE effect can be measured by comparing the ratio of positron-proton elastic scattering cross section to that of the electron-proton [R = σ(e +p)/σ(e+p)]. The ratio R was measured over a wide range of kinematics, utilizing a 5.6 GeV primary electron beam produced by the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. This dissertation explored dependence of R on kinematic variables such as squared four-momentum transfer (Q2) and the virtual photon polarization parameter (&epsis;). A mixed electron-positron beam was produced from the primary electron beam in experimental Hall B. The mixed beam was scattered from a liquid hydrogen (LH2) target. Both the scattered lepton and the recoil proton were detected by the CEBAF Large Acceptance Spectrometer (CLAS). The elastic events were then identified by using elastic scattering kinematics. This work extracted the Q2 dependence of R at high &epsis;(&epsis; > 0.8) and the $&epsis; dependence of R at ⟨Q 2⟩ approx 0.85 GeV2. In these kinematics, our data confirm the validity of the hadronic calculations of the TPE effect by Blunden, Melnitchouk, and Tjon. This hadronic TPE effect, with additional corrections contributed by higher excitations of the intermediate state nucleon, largely reconciles the Rosenbluth and the polarization transfer measurements of the electromagnetic form factors.

Users Acceptance of Online Enrollment Processes in a Higher Education Institution

Little is known about students’ perceptions of online enrollment processes. Student satisfaction is part of the assessment required for accreditation, but evidence suggests that college administrators are oriented to retention and graduation rates rather than to consumer perception. The purpose of this descriptive quantitative study was to develop and validate a model that enables the measurement of online enrollment processes by the analysis of the students’ perceptions. The theoretical framework used to support this study was the process virtualization theory while the conceptual framework was based on Technology Acceptance Model (TAM). TAM is the most valid framework for studying user acceptance of technology and virtual processes. The model was modified, adding a new variable to fit this study. Research questions were used to determine if an institution knows how its students perceive online enrollment processes and how they can become more efficient and effective, improving usage and satisfaction. Descriptive data were collected and analyzed in phases: the pilot study phase, data collection phase, and analysis phases. Inferential statistics were used to draw information from sampled observations of the population; a Cronbach Alpha was conducted to determine the reliability and validity of the model. The study demonstrated that the modified TAM is valid, reliable, and fit to assess the perceptions of the users of online enrollment processes. This study will effect positive social change by providing enrollment managers and administrators information on how to analyze the acceptance their online enrollment processes from the perspective of their students as customers of an institution of higher learning.

Are Consumers Ready for Mobile Payment? An Examination of Consumer Acceptance of Mobile Payment Technology in Restaurant Industry

As an emerging payment method, mobile payment technology is perceived to be a secure and effective substitute of traditional debit/credit card payment. Although several reports and scholars claimed that mobile payment technology would become a major future payment method, consumers rather caught on this trend slowly, and little is known about key determinants of consumers’ acceptance of mobile payment. To close that gap, the current study extended the classic Technology Acceptance Model by adding four additional predictors that are relevant to hospitality industry. The study results suggested that compatibility with lifestyle was the strongest predictor of consumers’ intention to adopt mobile payment technology in restaurants, followed by perceived usefulness, subjective norm, security, and previous experience with mobile payment. Important theoretical and practical implications were provided based on our findings.

Predictors of client retention in alternative to prison substance abuse programs

Increased treatment retention among substance abusing individuals has been associated with reduced drug use, fewer arrests, and decreased unemployment, as well as a reduction in health risk behaviors. This longitudinal study examined the predictors of client retention for alternative to prison substance abuse treatment programs through assessing the roles of motivational factors and the client-worker relationship. The sample was comprised of 141 male felony offenders who were legally mandated to community based long-term residential drug treatment programs. The primary measures used in the study were the consecutive days a participant remained in treatment, Stages of Change Readiness Model and Treatment Eagerness Scale (SOCRATES), the Working Alliance Inventory (WAI), and The Readiness Ruler. Hierarchical multiple regression analysis was conducted for four hypotheses (a) participants who are more motivated to change at the time of entry will remain in treatment longer, (b) participants who have a strong therapeutic alliance will remain in treatment a greater number of consecutive days than participants who have weaker therapeutic alliance, (c) motivation to change, as measured at treatment entry, will be positively related to therapeutic alliance, (d) during the course of treatment variation in motivation to change will be predicted by the therapeutic alliance. Results support the following conclusions: Among clients in alternative-to prison programs the number of days in treatment is positively related to their motivation to change. The therapeutic alliance is not a predictor of the number of days in treatment. Motivation to change, particularly recognition of a drug problem, is positively related to the therapeutic alliance. Changes in motivation to change in response to treatment are positively related to the therapeutic alliance among clients in an alternative to prison substance abuse treatment programs. These results carry forward prior research and have implications for social work practice, research, and social welfare policy.

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

The relationship between student characteristics, computer literacy,technology acceptance, and distance education student satisfaction

The purpose of this study is to identify the relationship between the characteristics of distance education students, their computer literacy and technology acceptance and distance education course satisfaction. The theoretical framework for this study will apply Rogers and Havelock's Innovation, Diffusion & Utilization theories to distance education. It is hypothesized that technology acceptance and computer competency will influence the student course satisfaction and explain the decision to adopt or reject distance education curriculum and technology. Distance education delivery, Institutional Support, Convenience, Interactivity and five distance education technologies were studied. The data were collected by a survey questionnaire sent to four Florida universities. Three hundred and nineteen and students returned the questionnaire. A factor and regression analysis on three measure of satisfaction revealed significant difference between the three main factors related to the overall satisfaction of distance education students and their adoption of distance education technology as medium of learning. Computer literacy is significantly related to greater overall student satisfaction. However, when competing with other factors such as delivery, support, interactivity, and convenience, computer literacy is not significant. Results indicate that age and status are the only two student characteristics to be significant. Distance education technology acceptance is positively related to higher overall satisfaction. Innovativeness is also positively related to student overall satisfaction. Finally, the technology used relates positively to greater satisfaction levels within the educational experience. Additional research questions were investigated and provided insights into the innovation decision process.

Development of a New Client-Server Architecture for Context Aware Mobile Computing

This dissertation studies the context-aware application with its proposed algorithms at client side. The required context-aware infrastructure is discussed in depth to illustrate that such an infrastructure collects the mobile user’s context information, registers service providers, derives mobile user’s current context, distributes user context among context-aware applications, and provides tailored services. The approach proposed tries to strike a balance between the context server and mobile devices. The context acquisition is centralized at the server to ensure the usability of context information among mobile devices, while context reasoning remains at the application level. Hence, a centralized context acquisition and distributed context reasoning are viewed as a better solution overall. The context-aware search application is designed and implemented at the server side. A new algorithm is proposed to take into consideration the user context profiles. By promoting feedback on the dynamics of the system, any prior user selection is now saved for further analysis such that it may contribute to help the results of a subsequent search. On the basis of these developments at the server side, various solutions are consequently provided at the client side. A proxy software-based component is set up for the purpose of data collection. This research endorses the belief that the proxy at the client side should contain the context reasoning component. Implementation of such a component provides credence to this belief in that the context applications are able to derive the user context profiles. Furthermore, a context cache scheme is implemented to manage the cache on the client device in order to minimize processing requirements and other resources (bandwidth, CPU cycle, power). Java and MySQL platforms are used to implement the proposed architecture and to test scenarios derived from user’s daily activities. To meet the practical demands required of a testing environment without the impositions of a heavy cost for establishing such a comprehensive infrastructure, a software simulation using a free Yahoo search API is provided as a means to evaluate the effectiveness of the design approach in a most realistic way. The integration of Yahoo search engine into the context-aware architecture design proves how context aware application can meet user demands for tailored services and products in and around the user’s environment. The test results show that the overall design is highly effective,providing new features and enriching the mobile user’s experience through a broad scope of potential applications.

Proton Form Factor Puzzle and the CEBAF Large Acceptance Spectrometer(CLAS) Two-Photon Exchange Experiment

The electromagnetic form factors are the most fundamental observables that encode information about the internal structure of the nucleon. The electric ($G_{E}$) and the magnetic ($G_{M}$) form factors contain information about the spatial distribution of the charge and magnetization inside the nucleon. A significant discrepancy exists between the Rosenbluth and the polarization transfer measurements of the electromagnetic form factors of the proton. One possible explanation for the discrepancy is the contributions of two-photon exchange (TPE) effects. Theoretical calculations estimating the magnitude of the TPE effect are highly model dependent, and limited experimental evidence for such effects exists. Experimentally, the TPE effect can be measured by comparing the ratio of positron-proton elastic scattering cross section to that of the electron-proton $\large(R = \frac{\sigma (e^{+}p)}{\sigma (e^{-}p)}\large)$. The ratio $R$ was measured over a wide range of kinematics, utilizing a 5.6 GeV primary electron beam produced by the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. This dissertation explored dependence of $R$ on kinematic variables such as squared four-momentum transfer ($Q^{2}$) and the virtual photon polarization parameter ($\varepsilon$). A mixed electron-positron beam was produced from the primary electron beam in experimental Hall B. The mixed beam was scattered from a liquid hydrogen (LH$_{2}$) target. Both the scattered lepton and the recoil proton were detected by the CEBAF Large Acceptance Spectrometer (CLAS). The elastic events were then identified by using elastic scattering kinematics. This work extracted the $Q^{2}$ dependence of $R$ at high $\varepsilon$ ($\varepsilon > $ 0.8) and the $\varepsilon$ dependence of $R$ at $\langle Q^{2} \rangle \approx 0.85$ GeV$^{2}$. In these kinematics, our data confirm the validity of the hadronic calculations of the TPE effect by Blunden, Melnitchouk, and Tjon. This hadronic TPE effect, with additional corrections contributed by higher excitations of the intermediate state nucleon, largely reconciles the Rosenbluth and the polarization transfer measurements of the electromagnetic form factors.