Collaborative detection and mitigation of DDoS in software-defined networks

The Journal of Supercomputing - This research presents the detection and mitigation of distributed denial of service (DDoS) in software defined networks (SDN). The proposed method consists of three...     

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...     

Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

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.     

A panoramic view of Li7P3S11 solid electrolytes synthesis,structural aspects and practical challenges for all-solid-state lithium batteries

The development of an inorganic electrochemical stable solid-state electrolyte is essentially responsible for future state-of-the-art all-solid-state lithium batteries (ASSLBs). Because of their advantages in safety, working temperature, high energy density, and packaging, ASSLBs can develop an ideal energy storage system for modern electric vehicles (EVs). A solid electrolyte (SE) model must have an economical synthesis approach, exhibit electrochemical and chemical stability, high ionic conductivity, and low interfacial resistance. Owing to its highest conductivity of 17 mS·cm^-1, and deformability, the sulfide-based Li₇P₃S₁₁ solid electrolyte is a promising contender for the high-performance bulk type of ASSLBs. Herein, we present a current glimpse of the progress of synthetic procedures, structural aspects, and ionic conductivity improvement strategies. Structural elucidation and mechanistic approaches have been extensively discussed by using various characterization techniques. The chemical stability of Li₇P₃S₁₁ could be enhanced via oxide doping, and hard and soft acid/base (HSAB) concepts are also discussed. The issues to be undertaken for designing the ideal solid electrolytes, interfacial challenges, and high energy density have been discoursed. This review aims to provide a bird's eye view of the recent development of Li₇P₃S₁₁-based solid-state electrolyte applications and explore the strategies for designing new solid electrolytes with a target-oriented approach to enhance the efficiency of high energy density all-solid-state lithium batteries.     

Gurum Seeds: A Potential Source of Edible Oil

Cucurbitaceae family seeds are mostly discarded as agro-industrial wastes. Gurum (Citrullus lanatus var. colocynthoide) is an underutilized wild cucurbit plant, closely related to desert watermelon, which is grown abundantly in some African countries. Gurum seeds can play a significant role in health and nutrition due to their high oil content. This review describes the nutritional composition of gurum seeds and their oil profile. Gurum seeds are a good source of oil (27–35.5%), fiber (26–31%), crude protein (15–18%), and carbohydrates (14–17%). Gurum seeds oil is extracted by supercritical CO₂ (SFE), screw press, and solvent extraction techniques. The gurum seeds oil is composed of unsaturated fatty acids with a high proportion of linoleic acid (C18:2) and oleic acid (C18:1). Gurum seeds oil contains various bioactive compounds, such as tocopherols, phytosterols, and polyphenols. It is reported that solvent extraction gives a higher yield than the screw press and SFE, but the SFE is preferred due to safety issues. More studies are required for producing better quality gurum seeds oil by using novel extraction techniques that can increase oil yield.