Deterministic scheduling for energy efficient and reliable communication in heterogeneous sensing environments in industrial wireless sensor networks

The present-day industries incorporate many applications, and complex processes, hence, a large number of sensors with dissimilar process deadlines and sensor update frequencies will be in place. This paper presents a scheduling algorithm, which takes into account the varying deadlines of the sensors connected to the cluster-head, and formulates a static schedule for Time Division Multiple Access (TDMA) based communication. The scheme uses IEEE802.15.4e superframe as a baseline and proposes a new superframe structure. For evaluation purposes the update frequencies of different industrial processes are considered. The scheduling algorithm is evaluated under varying network loads by increasing the number of nodes affiliated to a cluster-head. The static schedule generated by the scheduling algorithm offers reduced energy consumption, improved reliability, efficient network load management and improved information to control bits ratio

Association of hypoadiponectemia with smokeless/dipping tobacco use in young men

Background: Low levels of adiponectin, an adipocytokine with anti-diabetic, antiatherogenic and cardioprotective properties, is associated with increased risk of coronary disease in young men. Previous studies have demonstrated that smokeless tobacco is linked with a reduction of plasma adiponectin levels. However, the influence of smokeless tobacco (dipping tobacco) on plasma adiponectin levels still remains unknown. This study was conducted to assess the plasma adiponectin levels in young men who were using dipping tobacco. Methods: This was a community based study, which consisted of 186 young lean healthy males aged 20 to 35 years. Among these, 96 men were dipping tobacco users (BMI = 23.07 ± 2.68) and 90 were non-dipping tobacco users (BMI = 23.67 ± 1.46). Serum adiponectin levels were assessed by Enzyme Linked ImmunoSorbent Assay (ELISA). Results: A statistically significant difference in the mean adiponectin level between tobacco dipper and non-dipper groups was observed (p = 0.0001). A significant difference between the two groups was also observed in baseline parameters including triglyceride and random blood sugar levels (p < 0.05). However, no significant difference was observed between the two groups in other clinical parameters. Conclusions: Findings of this study suggest that dipping tobacco use was significantly associated with low level of adiponetin in community dwelling young males. This emphasizes the importance of developing community intervention to reduce the use of dipping tobacco, which will reduce the tobacco associated disease burden in the community and will improve public health

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Software-Defined Approach for Communication in Autonomous Transportation Systems

Autonomous driving technology offers a promising solution to reduce road accidents, traffic congestion, and fuel consumption. The management of vehicular networks is challenging as it demands mobility, location awareness, high reliability and low latency of data traffic. In this paper, we propose a novel communication architecture for vehicular network with 5G Mobile Networks and SDN technologies to support multiple core networks for autonomous vehicles and to tackle the potential challenges raised by the autonomous driving vehicles. Data requirements are evaluated for vehicular networks with respect to number of lanes and cluster size, to efficiently use the frequency and bandwidth. Also, the network latency requirements are analysed, which are mandatory constraints for all the applications where real time end-to-end communication is necessary. A test environment is also formulated to evaluate improvement in vehicular network using SDN-based approach over traditional core networks

A novel MAC proposal for critical and emergency communications in industrial wireless sensor networks

In this paper, three MAC protocols, EE-MAC, CF-MAC and OD-MAC, are proposed. EE-MAC incorporates emergency communication and allows immediate channel access for emergency traffic. CF-MAC compensates regulatory and open-loop control traffic and introduces a prioritized access for high priority nodes. It also allows nodes with critical data to reserve communication slots using control channel. Whereas OD-MAC presents a deadline based dynamic scheduler which ensures timely delivery of time-critical information. The paper presents mathematical modelling of the proposed protocols. For evaluation purposes, the performance of the proposed protocols is compared to IEEE 802.15.4e LLDN. The results show that the proposed protocols offer up to 92% reduction in delay in emergency communications at the cost of 5% to 15% increase in delay of time-insensitive data. A 60% and 85% reduction was observed in the channel access delay for regulatory and open-loop control traffic respectively along with notable improvements in communications reliability

The Relationship of Leader-Member Exchange and Organizational Citizenship Behavior, the Moderating Impact of the Role of Subordinate LMX

The fundamental purpose of the study is to check the impact of leader-member exchange (LMX) with reference to having in view the superior authority LMX and Subordinate LMX on organizational citizenship behavior (OCB). This study also focus on the role of subordinate-LMX on OCB, the role of subordinate-LMX would be examined as moderating variable. The estimated results described that LMX form the superior side has a good impact on OCB, while the impact of LMX by subordinate has not significant impact on OCB. Findings of this study enhancing the existing Research work. Moreover managerial implication and findings of this research work are based on extensive literature. Key words: Leader-member exchange, Organizational citizenship behavio

Antiviral activity of organic molecules having sulfonamide moiety: An insight of recent research

Sulfonamide derivatives are well known for their antibacterial activity as manifested by ‘Sulfa Drugs’, for example, sulfamethoxazole etc. In addition, they are associated with a large number of pharmacological activities such as anti-microbial, anti-inflammatory, anti-cancer, anti-oxidant, anti-viral etc. This work has emphasized their application as antiviral agents such as HIV (human immunodeficiency virus), HCV (hepatitis C virus) etc. We have presented here a number of sulfonamide derivatives exhibiting remarkable antiviral potential

Synthesis and characterization of some new Schiff base derivatives of gabapentin, and assessment of their antibacterial, antioxidant and anticonvulsant activities

Purpose: To synthesize and characterize some new gabapentin Schiff base derivatives, and to assess their antibacterial, antioxidant and antiepileptic activities.Methods: Four Schiff base derivatives of gabapentin, termed G1, G2, G3 and G4, were synthesized by condensation with benzoin, vanillin, acetophenone, and benzophenone, respectively. Their chemical identities were established by FTIR, 1 H NMR and 13C NMR techniques. The new compounds were screened for antibacterial activity using agar well method, antioxidant activity by DPPH assay, and anticonvulsant activity against pentylenetetrazole (PTZ) induced seizures in mice.Results: All the compounds showed antibacterial activity against the test strains to variable degrees, while the parent drug did not exhibit antibacterial activity. The zones of inhibition of compound G2 against Micrococcus luteus (36.2 ± 1.0 mm) and Serratia marcescens (28.2 ± 1.0 mm), and of compound G4 against Stenotrophomonas maltophilia (36.8 ± 1.0 mm) were larger compared to thestandard drug, doxycycline, exhibiting zones of inhibition 28.2 ± 1.3, 28.2 ± 0.9 and 20.0 ± 0.9 mm, respectively. In addition, compounds G1 and G2 possessed significantly greater (p < 0.05) radical scavenging activity (82.3 ± 1.8 and 92.3 ± 2.2 %, respectively) than the precursor drug, gabapentin (63.2± 2.6 %). The seizure scores for compounds G1 (0.7 ± 0.06) and G2 (0.9 ± 0.07) were comparable(p ˃ 0.05) with gabapentin (0.8 ± 0.06), while compounds G3 and G4 were less active (p < 0.05) than gabapentin.Conclusion: Compounds G1 and G2 exhibit good antibacterial and antioxidant activities while retaining the anticonvulsant activity of the parent drug, gabapentin, thus making them suitable candidates for further development for the treatment of neurodegenerative pathologies associated with bacterial infections. Keywords: Gabapentin, Antibacterial, Seizures, Antioxidant, Anticonvulsan

Diagnosis and monitoring of Alzheimer's patients using classical and deep learning techniques

Machine based analysis and prediction systems are widely used for diagnosis of Alzheimer's Disease (AD). However, lower accuracy of existing techniques and lack of post diagnosis monitoring systems limit the scope of such studies. In this paper, a novel machine learning based diagnosis and monitoring of AD-like diseases is proposed. The AD-like diseases diagnosis process is accomplished by analysing the magnetic resonance imaging (MRI) scans using deep learning and is followed by an activity monitoring framework to monitor the subjects’ activities of daily living using body worn inertial sensors. The activity monitoring provides an assistive framework in daily life activities and evaluates vulnerability of the patients based on the activity level. The AD diagnosis results show up to 82% improvement in comparison to well-known existing techniques. Moreover, above 95% accuracy is achieved to classify the activities of daily living which is quite encouraging in terms of monitoring the activity profile of the subject