It's the Human that Matters: Accurate User Orientation Estimation for Mobile Computing Applications

Ubiquity of Internet-connected and sensor-equipped portable devices sparked a new set of mobile computing applications that leverage the proliferating sensing capabilities of smart-phones. For many of these applications, accurate estimation of the user heading, as compared to the phone heading, is of paramount importance. This is of special importance for many crowd-sensing applications, where the phone can be carried in arbitrary positions and orientations relative to the user body. Current state-of-the-art focus mainly on estimating the phone orientation, require the phone to be placed in a particular position, require user intervention, and/or do not work accurately indoors; which limits their ubiquitous usability in different applications. In this paper we present Humaine, a novel system to reliably and accurately estimate the user orientation relative to the Earth coordinate system. Humaine requires no prior-configuration nor user intervention and works accurately indoors and outdoors for arbitrary cell phone positions and orientations relative to the user body. The system applies statistical analysis techniques to the inertial sensors widely available on today's cell phones to estimate both the phone and user orientation. Implementation of the system on different Android devices with 170 experiments performed at different indoor and outdoor testbeds shows that Humaine significantly outperforms the state-of-the-art in diverse scenarios, achieving a median accuracy of $15^\circ$ averaged over a wide variety of phone positions. This is $558\%$ better than the-state-of-the-art. The accuracy is bounded by the error in the inertial sensors readings and can be enhanced with more accurate sensors and sensor fusion.Comment: Accepted for publication in the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous 2014

Rural development and the problem of access: The case of the integrated rural development programme in Bangladesh

Rural development programmes are normally regarded as necessary for alleviating mass rural poverty in the Developing World, but to be successful they must reach small farmers and the landless. The available evidence suggests that major rural development programme instituted by the Bangladesh Government in the 1960s, the Integrated Rural Development Programme (IRDP), has failed to assist the poorer sections of the rural community to any great extent. Although recently re-designed to provide better access to its services for small farmers and the landless, it will be argued that the main reason for its continuing failure to meet their needs arises from their variable access to land and other private resources which together limit the advantages to be acquired from the goods and services provided under the IRDP. Understanding the process by which access is differentiated is, therefore, crucial to designing improvements to existing programmes and to developing appropriate institutions for those who lack access. This study is an attempt to understand this process. Data have been collected through interviews with officials responsible for the IRDP at all levels of its operation and from the Sherpur Upazila Central Cooperative Association (UCCA) in Bogra District of north-west Bangladesh. Farmers and landless people in two villages in that upazila (sub-district), one employing the IRDP and the other not, have been interviewed. The surveys show that in principle the IRDP can work effectively on behalf of the rural poor but its impact is greatly reduced in practice by a complex and poorly supervised administration at the local level and weak links with potential recipients. The ownership of material assets, especially land, and the individual's position in the local power structure, remain the determining factors in the receipt of benefits from the IRDP

Recruitment and Selection Process in Bangladesh Civil Service: A Critical Overview

An efficient civil service  is essential for effective implementation of public policy and delivery of public services.  To build an efficient civil service system, government must ensure that talented, competent and committed persons are recruited in the civil service. So the recruitment and selection process should be objective, uniform and of high quality. But it is very unfortunate that sound recruitment system for civil service does not exist in Bangladesh. Ensuring merit in public appointment is an important element of quality civil service. But merit has not given due importance in our recruitment policy. Reservation of posts, politicization of bureaucracy and faulty examination system are destroying the reputation of recruitment and selection process to be a fair and sound system .Against this backdrop this paper intends to assess and evaluate the existing recruitment and selection process of BCS and provide some suggestions to improve the present situation. Key words: Recruitment, Selection, Civil Service, Cadre Service, Merit, Equity

Globalization and Women in Bangladesh: A Review of Socio Socio-Economic and Cultural Impacts

We live in an ‘age of globalization’. The impact of globalization has brought about positive as well as negative effects on almost every societal aspect in the present day world. Globalization affects developed and developing nations differently. It also affects different groups of people in different ways. Women clearly stand out among the distinct groups of society upon whom globalization’s impact has been most significant. In this paper an attempt has been made to present an overview of the socio-economic and cultural consequences of globalization on women in Bangladesh from various angles. Keywords: Globalization, Women, Changing economy, Society, Culture

The effectiveness of collaborative reading in tertiary level EFL teaching in Iran

This research addressed four questions: 1. Does collaborative reading lead to greater comprehension of a text than private reading? If so: 2. Does this effect vary according to students’ competence in reading comprehension? 3. What strategies are used by the students during collaborative reading, and 4. In what ways might these strategies contribute to the higher level of comprehension? The study sample comprised two groups of students in two different universities. The major intervention consisted of four texts of equal length. Each class read two of the texts collaboratively in small groups and the other two privately. After reading the text the participants took a comprehension test. Collaborative reading resulted in consistently higher scores than private reading for all four texts. Group interactions during collaborative reading were tape recorded and transcribed. Analysis of the transcriptions revealed that collaborative readers were involved in five major processes of collaborative reading, namely: brainstorming, clarifying the language, paraphrasing, summarizing, and interaction management

Fusing Freight Analysis Framework and Transearch Data: An Econometric Data Fusion Approach

A major hurdle in freight demand modeling has always been the lack of adequate data on freight movements for different industry sectors for planning applications. Freight Analysis Framework (FAF), and Transearch (TS) databases contain annualized commodity flow data. The primary motivation for our study is the development of a fused database from FAF and TS to realize transportation network flows at a fine spatial resolution (county-level) while accommodating for production and consumption behavioral trends (provided by TS). Towards this end, we formulate and estimate a joint econometric model framework grounded in maximum likelihood approach to estimate county-level commodity flows. The algorithm is implemented for the commodity flow information from 2012 FAF and 2011 TS databases to generate transportation network flows for 67 counties in Florida. The data fusion process considers several exogenous variables including origin-destination indicator variables, socio-demographic and socio-economic indicators, and transportation infrastructure indicators. Subsequently, the algorithm is implemented to develop freight flows for the Florida region considering inflows and outflows across the US and neighboring countries. The base year models developed are employed to predict future year data for years 2015 through 2040 in 5-year increments at the same spatial level. Furthermore, we disaggregate the county level flows obtained from algorithm to a finer resolution `- statewide transportation analysis zone (SWTAZ) defined by the FDOT. The disaggregation process allocates truck-based commodity flows from a 79-zone system to an 8835-zone system. A two-stage factor multiplication method is proposed to disaggregate the county flow to SWTAZ flow. The factors are estimated both at the origin and destination level using a random utility factional split model approach. Eventually, we conducted a sensitivity analysis of the parameterization by evaluating the model structure for different numbers of intermediate stops in a route and/or the number of available routes for the origin-destinations

An immunoinformatic approach to design a novel vaccine against the human respiratory syncytial virus (hRSV) by targeting M2-1 protein

Background: Human respiratory syncytial virus (hRSV) is the leading cause of upper and lower respiratory infection in infants, adults and immunocompromised persons. The matrix protein, M2-1 of hRSV is a cofactor of viral RNA polymerase that plays a crucial role during replication. This programmed study was designed to scrutinize potential immunogens from the M2-1 protein characterized from four different continents.Methods: Sequence data obtained from NCBI databases were analysed by using a series of web and software based bioinformatics tools to find out the best epitope against hRSV.Results: The phylogenetic data revealed a homogenized clustering of M2-1 protein for the African, European, and Asian clades while proteins from North American collections found to have a significant evolutionary detachment compared to three other clusters. Using various web-based bioinformatics tools, the study identified four common B-cell epitopes present in all the M2-1 proteins from four different clusters with higher antigenicity and conservancy. Among the 17 M2-1 protein investigated for T-cell epitopes, “VLQNLDVGL” peptide from A2 super-type, and “QSACVAMSK” and “CLNGRRCHY” from A3 super-type showed the highest antigenicity at >0.80 conservancy cut-off value. After evaluation of all antigenic properties, only “CLNGRRCHY” peptide qualified as a potential vaccine candidate against hRSV. Molecular docking revealed strong and stable binding of the epitope to major histocompatibility complexes (MHC) molecules in terms of hydrogen bonding.Conclusion: The designed epitope could be used as a possible vaccine candidate against hRSV.Keywords: hRSV; M2-1 protein; phylogenetic cluster; BCL and CTL epitopes; molecular dockin

Prediction of Sudden Cardiac Death Using Ensemble Classifiers

Sudden Cardiac Death (SCD) is a medical problem that is responsible for over 300,000 deaths per year in the United States and millions worldwide. SCD is defined as death occurring from within one hour of the onset of acute symptoms, an unwitnessed death in the absence of pre-existing progressive circulatory failures or other causes of deaths, or death during attempted resuscitation. Sudden death due to cardiac reasons is a leading cause of death among Congestive Heart Failure (CHF) patients. The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised machine learning methods have been successfully used for medical diagnosis. Ensemble classifiers are known to achieve better prediction accuracy than its constituent base classifiers. In an effort to understand the factors contributing to SCD, data on 2,521 patients were collected for the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT). The data included 96 features that were gathered over a period of 5 years. The goal of this dissertation was to develop a model that could accurately predict SCD based on available features. The prediction model used the Cox proportional hazards model as a score and then used the ExtraTreesClassifier algorithm as a boosting mechanism to create the ensemble. We tested the system at prediction points of 180 days and 365 days. Our best results were at 180-days with accuracy of 0.9624, specificity of 0.9915, and F1 score of 0.9607

Expression of infectious bovine rhinotracheitis virus glycoprotein D in bacterial cell

Bovine Herpesvirus 1 (BHV-1) belongs to the genus of Varicellovirus and the family of Herpesviridae which contains three main gB, gC and gD genes. In order to cloning of the coding region of gD gene of IBR virus , PCR product of the open reading frame of the gene from IBR virus isolated in Iran was amplified by PCR. A 1047bp PCR product of the gD gene with EcoRI, HindIII restriction sites were subcloned of pTZ57R/T and digested by the mentioned endonucleases. Digested insert cloned in to pET-32a and transfered in E.coli cells. For the expression of gD protein, the pET-32a recombinant vector was transformed and then induced in BL21 (DE3) strain of E.coli competent cells using IPTG. The presence of gD expressed protein was shown in immunoblotting and SDS-PAGE system. With respect to the remarkable frequency of infection to IBR in Iran and the necessity of controlling it through vaccination with recombinant vaccines of thymidine kinase, manufacturing and applying the recombinant gD protein are vital goals in recognition and distinction between infection and responsescaused by vaccine