Generalized Interference Alignment --- Part I: Theoretical Framework

Interference alignment (IA) has attracted enormous research interest as it achieves optimal capacity scaling with respect to signal to noise ratio on interference networks. IA has also recently emerged as an effective tool in engineering interference for secrecy protection on wireless wiretap networks. However, despite the numerous works dedicated to IA, two of its fundamental issues, i.e., feasibility conditions and transceiver design, are not completely addressed in the literature. In this two part paper, a generalised interference alignment (GIA) technique is proposed to enhance the IA's capability in secrecy protection. A theoretical framework is established to analyze the two fundamental issues of GIA in Part I and then the performance of GIA in large-scale stochastic networks is characterized to illustrate how GIA benefits secrecy protection in Part II. The theoretical framework for GIA adopts methodologies from algebraic geometry, determines the necessary and sufficient feasibility conditions of GIA, and generates a set of algorithms that can solve the GIA problem. This framework sets up a foundation for the development and implementation of GIA.Comment: Minor Revision at IEEE Transactions on Signal Processin

The Evaluation Of Independent Norm Text And Impartial Judge On The Constitutional Court Of Indonesia

In this paper, the Judge of the Constitutional Court is the authority of judicial power to enforce law and justice as a guardian and interpreter of the constitution. The method used in this research is legal research. The result of this research is that the evaluation of the independent and impartial texts of Indonesian constitutional court judges can be measured from procedural independent, legal fomal-empirical independent, and empirically independent either according to national legal instruments or international instruments. Meanwhile, the supervision of the Constitutional Court judges is devided into two supervisory models. These are that it is supervised by the Ethics Council of the Constitutional Court and by the Honorary Council of Constitutional Justices. For the external supervision, the court is supervised by the Constitutional Court with the Judicial Commission philosophically forming the Ethics Council to perform the (control function) to the judges of the Constitutional Court in order to avoid deviation of legal norms by the judges of the Constitutional Court Indonesia

Breast cancer data analysis for survivability studies and prediction

© 2017 Elsevier B.V. Background Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. Objective The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties. Methods Unsupervised data mining methods viz. the self-organising map (SOM) and density-based spatial clustering of applications with noise (DBSCAN) is used to create patient cohort clusters. These clusters, with associated patterns, were used to train multilayer perceptron (MLP) model for improved patient survivability analysis. A large dataset available from SEER program is used in this study to identify patterns associated with the survivability of breast cancer patients. Information gain was computed for the purpose of variable selection. All of these methods are data-driven and require little (if any) input from users or experts. Results SOM consolidated patients into cohorts of patients with similar properties. From this, DBSCAN identified and extracted nine cohorts (clusters). It is found that patients in each of the nine clusters have different survivability time. The separation of patients into clusters improved the overall survival prediction accuracy based on MLP and revealed intricate conditions that affect the accuracy of a prediction. Conclusions A new, entirely data driven approach based on unsupervised learning methods improves understanding and helps identify patterns associated with the survivability of patient. The results of the analysis can be used to segment the historical patient data into clusters or subsets, which share common variable values and survivability. The survivability prediction accuracy of a MLP is improved by using identified patient cohorts as opposed to using raw historical data. Analysis of variable values in each cohort provide better insights into survivability of a particular subgroup of breast cancer patients

Pengaruh Nilai Pelanggan Terhadap Retensi Pelanggan Melalui Kepuasan

This study aimed to determine the effect of customer value on customer retention through customer satisfaction who use Smartfren data services on student majoring in Business Administration, University of Diponegoro class of 2009 to 2012. This type of research is explanatory research, by using a survey method of data collection tools such as questionnaires. The number of respondents were 63 persons obtained by sensus. Tests using the research instrument validity and reliability test, whereas data analysis techniques used simple linear regression, t-test, and path analysis with SPSS 16.0 tools. These results indicate that the effect given by the variable customer value (X1) and satisfaction variables (Y1) to variable customer retention (Y2) respectively - amounted to 26.2 % and 23.6 %. Results of simple linear regression between variables showed a positive regression coefficient, this means the higher the customer value and satisfaction, it will also result in higher customer retention. Advice can be given that the company needs to maintain customer satisfaction through increased customer value with continuous improvement efforts on the quality of data service connectivity, expansion of network coverage, improved service standards either directly or indirectly (via SMS, call center, or the official site). This effort is done so that consumers feel satisfied, and proud of the product, especially Smartfren data services, so that consumers do not switch to another data service provider, and is willing to give a positive recommendation

Generalized Interference Alignment—Part II: Application to Wireless Secrecy

In contrast to its wired counterpart, wireless communication is highly susceptible to eavesdropping due to the broadcast nature of the wireless propagation medium. Recent works have proposed the use of interference to reduce eavesdropping capabilities in wireless wiretap networks. However, the concurrent effect of interference on both eavesdropping receivers (ERs) and legitimate receivers has not been thoroughly investigated, and careful engineering of the network interference is required to harness the full potential of interference for wireless secrecy. This two-part article addresses this issue by proposing a generalized interference alignment (GIA) technique, which jointly designs the transceivers at the legitimate partners to impede the ERs without interfering with LRs. In Part I, we have established a theoretical framework for the GIA technique. In Part II, we will first propose an efficient GIA algorithm that is applicable to large-scale networks and then evaluate the performance of this algorithm in stochastic wireless wiretap network via both analysis and simulation. These results reveal insights into when and how GIA contributes to wireless secrecy

Bayesian Detection in Bounded Height Tree Networks

We study the detection performance of large scale sensor networks, configured as trees with bounded height, in which information is progressively compressed as it moves towards the root of the tree. We show that, under a Bayesian formulation, the error probability decays exponentially fast, and we provide bounds for the error exponent. We then focus on the case where the tree has certain symmetry properties. We derive the form of the optimal exponent within a restricted class of easily implementable strategies, as well as optimal strategies within that class. We also find conditions under which (suitably defined) majority rules are optimal. Finally, we provide evidence that in designing a network it is preferable to keep the branching factor small for nodes other than the neighbors of the leaves

Understanding urban inequalities in children's linear growth outcomes: a trend and decomposition analysis of 39,049 children in Bangladesh (2000-2018)

BACKGROUND: Despite significant progress in reducing child undernutrition, Bangladesh remains among the top six countries globally with the largest burden of child stunting and has disproportionately high stunting prevalence among the urban poor. We use population representative data to identify key predictors of child stunting in Bangladesh and assess their contributions to linear growth differences observed between urban poor and non-poor children. METHODS: We combined six rounds of Demographic and Health Survey data spanning 2000-2018 and used official poverty rates to classify the urban population into poor and non-poor households. We identified key stunting determinants using stepwise selection method. Regression-decomposition was used to quantify contributions of these key determinants to poverty-based intra-urban differences in child linear growth status. RESULTS: Key stunting determinants identified in our study predicted 84% of the linear growth difference between urban poor and non-poor children. Child's place of birth (27%), household wealth (22%), maternal education (18%), and maternal body mass index (11%) were the largest contributors to the intra-urban child linear growth gap. Difference in average height-for-age z score between urban poor and non-poor children declined by 0.31 standard deviations between 2000 and 2018. About one quarter of this observed decrease was explained by reduced differentials between urban poor and non-poor in levels of maternal education and maternal underweight status. CONCLUSIONS: Although the intra-urban disparity in child linear growth status declined over the 2000-2018 period, socioeconomic gaps remain significant. Increased nutrition-sensitive programs and investments targeting the urban poor to improve girls' education, household food security, and maternal and child health services could aid in further narrowing the remaining linear growth gap

Change in nutritional status of urban slum children before and after the first COVID-19 wave in Bangladesh: a repeated cross-sectional assessment

The onset of COVID-19 severely disrupted economies and increased acute household food insecurity in developing countries. Consequently, a global rise in childhood undernutrition was predicted, especially among vulnerable populations, but primary evidence on actual changes in nutritional status remained scarce. In this paper, we assessed shifts in nutritional status of urban slum children in Bangladesh pre- and post- the country's first wave of COVID-19 and nationwide lockdown. We used two rounds of cross-sectional data collected before and after the pandemic's first year in two large slum settlements (Korail and Tongi) of Dhaka and Gazipur, Bangladesh (n = 1119). Regression models estimated pre-post changes in: 1) predictors of childhood undernutrition (household income, jobs, food security, dietary diversity, healthcare utilization, and hand hygiene); and 2) under-five children's nutritional status (average height-for-age z-score (HAZ) and weight-for-height z-score (WHZ), stunting, and wasting). Subgroup analysis was done by household migration status and slum area. Over the sample period, average monthly household income dropped 23% from BDT 20,740 to BDT 15,960 (beta = -4.77; 95% CI:-6.40, -3.15), and currently employed fathers slightly declined from 99% to 95% (beta = -0.04; 95% CI:-0.05, -0.02). Average HAZ among the slum children improved 0.13 SD (95% CI: 0.003, 0.26). Among non-migrant children in Tongi, the odds of stunting increased (OR = 2.01, 95% CI: 1.16, 3.48) and average WHZ reduced -0.40 SD (95% CI: -0.74, -0.06). Despite great economic hardship, and differential patterns of representativeness by household geography and migration status, slum children in Bangladesh generally demonstrated resilience to nutritional decline over the first year of the pandemic. While underlying threats to nutritional deterioration persisted, considerable job and income recovery in the post-lockdown period appeared to have cushioned the overall decline. However, as the pandemic continues, monitoring and appropriate actions are needed to avert lasting setbacks to Bangladesh nutritional progress

Socio-Technical Perspective on Managing Type II Diabetes

Social attributes such as education level, family history or place of residence all place a strong role in the probability of a person developing type II diabetes later in life. The aim of this paper is to develop a knowledge system based to use social attributes to estimate the prevalence of type II diabetes in a given area in Australia to support public health policymaking. The focus of this paper is towards answering the research question How can social determinants associated with type II diabetes, be used to incrementally develop a supporting knowledge-based system (KBS)? The contribution of this paper is two folds: 1. The problem domain is analysed and a suitable KBS development framework is chosen 2. A prototype is developed and presented. Initial results with preliminary data confirm the validity of the approach