Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Statistically correlated multi-task learning for autonomous driving

Neural Computing and Applications - Autonomous driving research is an emerging area in the machine learning domain. Most existing methods perform single-task learning, while multi-task learning...     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

Soil–conduit interaction: an artificial intelligence application for reinforced concrete and corrugated steel conduits

Neural Computing and Applications - Marston’s load theory is commonly used for understanding the soil–conduit interaction. However, there are no practical methods available which can...     

Continuous reverse k nearest neighbors queries in Euclidean space and in spatial networks

In this paper, we study the problem of continuous monitoring of reverse k nearest neighbors queries in Euclidean space as well as in spatial networks. Existing techniques are sensitive toward objects and queries movement. For example, the results of a query are to be recomputed whenever the query changes its location. We present a framework for continuous reverse k nearest neighbor (RkNN) queries by assigning each object and query with a safe region such that the expensive recomputation is not required as long as the query and objects remain in their respective safe regions. This significantly improves the computation cost. As a byproduct, our framework also reduces the communication cost in client–server architectures because an object does not report its location to the server unless it leaves its safe region or the server sends a location update request. We also conduct a rigid cost analysis for our Euclidean space RkNN algorithm. We show that our techniques can also be applied to answer bichromatic RkNN queries in Euclidean space as well as in spatial networks. Furthermore, we show that our techniques can be extended for the spatial networks that are represented by directed graphs. The extensive experiments demonstrate that our techniques outperform the existing techniques by an order of magnitude in terms of computation cost and communication cost.     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.     

Transference and retrieval of voice message over low signal strength in satellite communication

This paper presents a method of transferring voice using short messaging service in satellite communication system. The method is especially applicable in a situation where signal strength is low and voice call is not possible. In a tunnel, basement or environment with bad climate conditions, signal strength usually gets weak which make voice call difficult but SMS works in such situation. An application has been developed using J2ME language in order to test the proposed method. For experimentation, Thuraya SG-2520 satellite phone has been used.     

Cytological Observations and Bulked-Segregant Analysis Coupled Global Genome Sequencing Reveal Two Genes Associated with Pollen Fertility in Tetraploid Rice

Neo-tetraploid rice with high fertility is a useful germplasm for polyploid rice breeding, which was developed from the crossing of different autotetraploid rice lines. However, little information is available on the molecular mechanism underlying the fertility of neo-tetraploid rice. Here, two contrasting populations of tetraploid rice, including one with high fertility (hereafter referred to as JG) and another with low fertility (hereafter referred to as JD), were generated by crossing Huaduo 3 (H3), a high fertility neo-tetraploid rice that was developed by crossing Jackson-4x with 96025-4x, and Huajingxian74-4x (T452), a low fertility autotetraploid rice parent. Cytological, global genome sequencing-based bulked-segregant (BSA-seq) and CRISPR/Cas9 technology were employed to study the genes associated with pollen fertility in neo-tetraploid rice. The embryo sacs of JG and JD lines were normal; however, pollen fertility was low in JD, which led to scarce fertilization and low seed setting. Cytological observations displayed low pollen fertility (25.1%) and approximately 31.3 and 27.2% chromosome lagging at metaphase I and II, and 28.8 and 24.8% chromosome straggling at anaphase I and II in JD, respectively. BSA-seq of F_2–3 generations and RNA-seq of F₄ generation detected a common fragment, i.e., 18,915,234–19,500,000, at chromosome 7, which was comprised of 78 genes associated with fertility. Among 78 genes, 9 genes had been known to be involved in meiosis and pollen development. Two mutants ny1 (LOC_Os07g32406) and ny2 (LOC_Os07g32040) were generated by CRISPR/Cas9 knockout in neo-tetraploid rice, and which exhibited low pollen fertility and abnormal chromosome behavior. Our study revealed that two unknown genes, LOC_Os07g32406 (NY1) and LOC_Os07g32040 (NY2) play an important role in pollen development of neo-tetraploid rice and provides a new perspective about the genetic mechanisms of fertility in polyploid rice.     

Sulfamic acid functionalized slag for effective removal of organic dye and toxic metal from the aqueous samples

Surface functionalization of blast furnace slag with sulfamic acid(a zwitterion) was performed for the removal of Cr~(3+) and methylene blue dye(MB) from water samples. The slag functionalization process was optimized using Response Surface Methodology Design. Statistical analysis of the parameters that include the sulfamic acid amount(A), reaction time(B), and temperature(C) revealed that(A) increase had a negative effect on the adsorption of both pollutants by the zwitterion slag, whereas(B) and(C)increase presented a positive impact. At the optimum condition of 2 g sulfamic acid amount, 50 min reaction time and 37 °C temperature, the prepared slag showed a removal efficiency of more than 90% for both Cr~(3+) and MB. Surface characterization by SEM/EDS, FTIR, XPS and surface area analyser, showed an improvement in surface properties and the incorporation of zwitterionic NH_2~+ and S@O groups of sulfamic acid. Adsorption isotherm and kinetic studies conducted with the zwitterion slag showed the adsorption process was suited to Freundlich isotherm model and pseudo-second-order kinetic model.The thermodynamic study conducted revealed the spontaneity of the process based on the calculated negative DG(Gibb's free energy) values. The prepared zwitterion slag offered easy regeneration with dilute HCl solution and showed a considerable removal(Cr3+: 65% and MB: 80%) for both pollutants even after 3 cycles of usage.