A secure multifactor remote user authentication scheme for Internet of Multimedia Things environment

To attain ubiquitous connectivity of everything, Internet of Things (IoT) systems must include “multimedia things.” Internet of Multimedia Things (IoMT) is a heterogeneous network of smart multimedia things connected together and with other physical devices to the Internet so as to achieve globally available multimedia services and applications. Due to the ever increasing amount of multimedia data in IoT environments, securing these systems becomes crucial. This is because these systems are easily susceptible to attacks when information or any service is accessed by the users. In this paper, we propose a secure three‐factor remote user authentication scheme for IoMT systems using ECC. The formal security proof performed using ROR model and BAN logic confirms that an attacker will not be able to extract sensitive user information. Through informal security analysis, we justify the resistance of the scheme against several security attacks. The performance comparison shows that the scheme is efficient in terms of computational cost, security features, and attack resistance. Furthermore, simulation of the scheme using AVISPA and Proverif proves that the scheme is secure against all active and passive attacks.     

Comparative Study of the Different Variants of the DV-Hop Based Node Localization Algorithms for Wireless Sensor Networks

Wireless Personal Communications - Node localization is one of the essential services where sensor nodes in the wireless sensor network collaborate to provide location information of sensor nodes...     

Enhancing Coverage Using Weight Based Clustering in Wireless Sensor Networks

Energy conservation in wireless sensor networks (WSNs) is a fundamental issue. For certain surveillance applications in WSN, coverage lifetime is an important issue and this is related to energy consumption significantly. In order to handle these two interlinked aspects in WSN, a new scheme named Weight based Coverage Enhancing Protocol (WCEP) has been introduced. The WCEP aims to obtain longer full coverage and better network life time. The WCEP is based on assigning different weight values to certain governing parameters which are residual energy, overlapping degree, node density and degree of sensor node. These governing parameters affect the energy and coverage aspects predominantly. Further, these four different parameters are prime elements in cluster formation process and node scheduling mechanisms. The weight values help in selection of an optimal group of Cluster Heads and Cluster Members, which result in enhancement of complete coverage lifetime. The simulation results indicate that WCEP performs better in terms of energy consumption also. The enhancement of value 24% in full coverage lifetime has been obtained as compared to established existing techniques.

     

Image and Video Forensics: A Critical Survey

With the extensive use of multimedia on internet and easy approachability of powerful image and video editing software, doctored visual contents have been extensively appearing in our electronic-mail in-boxes, Whatsapp, Facebook or any other social media. Recently, attempting blind tampering in visual contents have been progressively adopted. This paper presents a collaborative survey on detection of such attempts. Our aim is to establish an effective path, for researchers working in the field of image and video forensics, to unfold new aspects of forgery. This paper will avail the comprehensive study that will assist the researchers to go through the various challenges encountered in the previous work. The focus of this paper is to review the splicing and copy–move forgery detection methods in images as well as inter and intra-frame forgery challenges in videos, highlighting the commonly used datasets and hence assisting new researchers to work on with. The efficacy of the paper is that such collaborative survey under one umbrella is not available yet.

     

Semantic Information Extraction from Multi-Corpora Using Deep Learning

Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing technique for removal of ambiguity in input corpora, and the second phase proposes a novel deep learning-based long short-term memory with rectification in Adam optimizer and multilayer perceptron to find agricultural-based named entity recognition, events, and relations between them. The proposed algorithm has been trained and tested on four input corpora i.e., agriculture, weather, soil, and pest & fertilizers. The experimental results have been compared with existing techniques and it was observed that the proposed algorithm outperforms Weighted-SOM, LSTM+RAO, PLR-DBN, KNN, and Naïve Bayes on standard parameters like accuracy, sensitivity, and specificity.     

On the design and modeling of microcontrolled fuzzy nuclear power plant controller

The article presents a working model of Control rod insertion in nuclear power plant based on fuzzy logic and implemented with MC68HC11 microcontroller. The control rods are made of neutron absorbing metal. The amount of control rod insertion into a pressurized water reactor in a nuclear power plant controls the nuclear fission process by controlling the rate at which the chain reaction takes place. The temperature in the pressurized water tank varies with the load of power, the higher the demand of power the higher the temperature and vice versa. The control rods help to maintain the appropriate temperature in the core of the reactor. Nuclear Power plants use a very complicated control scheme, to vary the amount of control rod insertion which is very expensive and difficult to troubleshoot. We have developed a fuzzy model, tested its functionality by generating control surfaces, written the fuzzy inference software, downloaded in the EEPROM of MC68HC11, and interfaced it with 8 LED Bar to simulate control rod and two 8-bit DIP switches to enter inputs of Power Generation and Temperature of the core of the reactor. © 1996 John Wiley & Sons, Inc.     

Hidden Relationships between N-Glycosylation and Disulfide Bonds in Individual Proteins

N-Glycosylation (NG) and disulfide bonds (DBs) are two prevalent co/post-translational modifications (PTMs) that are often conserved and coexist in membrane and secreted proteins involved in a large number of diseases. Both in the past and in recent times, the enzymes and chaperones regulating these PTMs have been constantly discovered to directly interact with each other or colocalize in the ER. However, beyond a few model proteins, how such cooperation affects N-glycan modification and disulfide bonding at selective sites in individual proteins is largely unknown. Here, we reviewed the literature to discover the current status in understanding the relationships between NG and DBs in individual proteins. Our results showed that more than 2700 human proteins carry both PTMs, and fewer than 2% of them have been investigated in the associations between NG and DBs. We summarized both these proteins with the reported relationships in the two PTMs and the tools used to discover the relationships. We hope that, by exposing this largely understudied field, more investigations can be encouraged to unveil the hidden relationships of NG and DBs in the majority of membranes and secreted proteins for pathophysiological understanding and biotherapeutic development.     

A novel electronic micro-viscometer

Microsystem Technologies - This paper reports the development of a novel electronic micro-viscometer capable of measuring viscosity of different Newtonian fluids using less than 100 µl which...     

Heavy metal accumulation in vegetables irrigated with water from different sources

The present study was carried out to assess levels of different heavy metals like iron, manganese, copper and zinc, in vegetables irrigated with water from different sources. The results indicated a substantial build-up of heavy metals in vegetables irrigated with wastewater. The range of various metals in wastewater-irrigated plants was 116–378, 12–69, 5.2–16.8 and 22–46 mg/kg for iron (Fe), manganese (Mn), copper (Cu) and zinc (Zn), respectively. The highest mean levels of Fe and Mn were detected in mint and spinach, whereas the levels of Cu and Zn were highest in carrot. The present study highlights that both adults and children consuming vegetables grown in wastewater-irrigated soils ingest significant amount of these metals. However, the values of these metals were below the recommended maximum tolerable levels proposed by the [Joint FAO/WHO Expert Committee on Food Additives (1999). Summary and conclusions. In 53rd Meeting, Rome, June 1–10, 1999]. However, the regular monitoring of levels of these metals from effluents and sewage, in vegetables and in other food materials is essential to prevent excessive build-up of these metals in the food chain.     

Textural and pasting properties of potatoes (Solanum tuberosum L.) as affected by storage temperature

Fresh tubers from five potato (Solanum tuberosum L.) cultivars were stored at different temperatures (4, 8, 12, 16 and 20 °C) and 80–90% relative humidity for 18 weeks after harvest to examine the effect of storage temperature on their textural and pasting properties. Texture profile analysis was performed on raw and cooked potatoes using an Instron universal testing machine to measure textural parameters such as fracturability, hardness, cohesiveness, adhesiveness and springiness. Both raw and cooked potato tubers showed a considerable reduction in all textural parameters upon storage, irrespective of the storage temperature employed. Raw potatoes showed a decrease in fracturability and hardness with increasing storage temperature, whereas their cooked counterparts showed the opposite trend. The extent of change in the textural properties of both raw and cooked potatoes also varied among the different cultivars. Fresh and stored tubers from all cultivars were freeze‐dried, ground into flours and analysed for amylose content and pasting properties. The amylose content of flours prepared from potatoes stored at 4 and 8 °C was observed to be considerably lower than that of flours prepared from potatoes stored at 16 and 20 °C. Pasting characteristics such as peak viscosity, setback and final viscosity increased with increasing storage temperature, while the reverse was observed for pasting temperature, when studied using a rapid visco analyser. Breakdown in viscosity of the flour pastes from all cultivars was considerably reduced during storage, irrespective of the storage temperature employed. Copyright © 2006 Society of Chemical Industry