FEDRESOURCE: Federated Learning Based Resource Allocation in Modern Wireless Networks

Deep reinforcement learning can effectively deal with resource allocation (RA) in wireless networks. However, more complex networks can have slower learning speeds, and a lack of network adaptability requires new policies to be learned for newly introduced systems. To address these issues, a novel federated learning-based resource allocation (FEDRESOURCE) has been proposed in this paper which efficiently performs RA in wireless networks. The proposed FEDRESOURCE technique uses federated learning (FL) which is a ML technique that shares the DRL-based RA model between distributed systems and a cloud server to describe a policy. The regularized local loss that occurs in the network will be reduced by using a butterfly optimization technique, which increases the convergence of the FL algorithm. The suggested FL framework speeds up policy learning and allows for adoption by employing deep learning and the optimization technique. Experiments were conducted using a Python-based simulator and detailed numerical results for the wireless RA sub-problems. The theoretical results of the novel FEDRESOURCE algorithm have been validated in terms of transmission power, convergence of algorithm, throughput, and cost. The proposed FEDRESOURCE technique achieves maximum transmit power up to 27%, 55%, and 68% energy efficiency compared to Scheduling policy, Asynchronous FL framework, and Heterogeneous computation schemes respectively. The proposed FEDRESOURCE technique can increase discrimination accuracy by 1.7%, 1.2%, and 0.78% compared to the scheduling policy framework, Asynchronous FL framework, and Heterogeneous computation schemes respectively

Analysis of Factors Responsible For of Work Stress In Chemical Industries In Kerala, India

This study examines the influence of factors responsible for work stress among the employees in the chemical industries in Kerala, India. The sample size of the subjects selected for the study consists of 75 Engineers, 110 Supervisors and 675 Workers in the selected chemical industries in kerala ,India. Seven factors were identified with the existing literatures, and in consultation with safety experts for the evaluation of work stress. The instrument developed by using these factors had validity, unidimensionality and reliability. The response rate was 81.3%. It is observed that existence the factors responsible for work stress among all the categories of employees in these industries

Advanced Navigation System for Aircraft Applications

Various forms of navigation are present in today’s world, leading from satellite based navigation to several archaic forms of navigation like star gazing. Now, lots of technologies are available to achieve this but with certain limitations. For example, FOG based navigation provides accuracy with in 0.10-100 range which is not sufficient for various military applications. Therefore, there is a need to design a system which will have better accuracy and thus requires development of ring laser gyro-based inertial systems. This paper concentrates on the aided navigation system based on ring laser gyro of 0.01 deg/hr class and GPS - GLONASS to further enhance the capability of system in terms of accuracy. The usage of such systems not only provides accurate results momentarily but it also persists for longer duration with the aid of GPS - GLONASS for applications like aircraft, ship and long range missiles. The system provides accuracy of the level of 1 Nm/hr in pure navigation and 30 m with the aid of GPS - GLONASS. Apart from this, the availability of gyro-compass and baro-inertial algorithms further enhances the system capabilities and made them self dependent to the major extent.Defence Science Journal, 2013, 63(2), pp.131-137, DOI:http://dx.doi.org/10.14429/dsj.63.425

Evaluation of Mandibular Anatomy Related to Sagittal Split Ramus Osteotomy using Three Dimensional Computed Tomography Scan Images

SUMMARY AND CONCLUSION: Spiral CT scan were taken in all patients undergoing BSSRO, prior to the surgical procedure. The CT data were imported into the MIMICS software and three dimensional image was created and analysed to assess the anatomical position of the mandibular foramen and inferior alveolar nerve. From our study we conclude as follows. 1. Spiral CT data is accurate in reproducing the surgical anatomy of the mandible. The Values obtained from CT scan accurately correlate with the measurement made intra operatively. 2. OPG represents the location and course of the inferior alveolar nerve, but measurements made from the OPG will not be useful intraoperatively due to irregular magnification. 3. The average anatomical measurements will not be useful to make osteotomy during SSRO, since there was wide range of variation in the anatomical position. It is better to take CT scan and assess the nerve position in every individual cases rather than taking average measurements. 4. The antilingula is not a reliable landmark to assess the position of the mandibular foramen. 5. Accurate identification of the course of Inferior alveolar nerve significantly reduces the incidence of neurosensory deficit. Although all the patients in our study had a satisfactory outcome, further studies are needed with a larger sample size to confirm these findings

POTENTIAL PHYTOCONSTITUENTS FROM NATURAL PRODUCTS FOR COMBATING AGAINST CORONAVIRUS DISEASE-19 (SEVERE ACUTE RESPIRATORY SYNDROME CORONAVIRUS‐2) - A REVIEW

Coronavirus called as coronavirus diseases (COVID)-19 (severe acute respiratory syndrome coronavirus [SARS‐CoV]‐2) is a viral infection which is spreading to a great extent and affecting many people worldwide, many developed and developing countries are severely affected by the virus. The World Health Organization (WHO) is taking serious preventive measures to stop this viral infection worldwide. The coronavirus is a big threat to human beings and controlling the emerging viral infections is a global concern. Antiviral drug such as Remdesivir has been approved by the FDA, but combating against these viral infections is a great challenge to scientists and researchers with the available few antiviral drugs due to severe side effects and toxicity. Many drugs such as hydroxy chloroquin, Remdesivir, and vaccines have been recommended for combating this virus. Few Polyherbal formulations and Ayurvedic formulations containing antiviral phytoconstituents have been recommended to boost the immunity. Some drugs and phytoconstituents are under different phases of human clinical trials. The currently available synthetic drugs and vaccines for the treatment of viral infections have severe side effects. Medicinal plants play a critical role in treating viral infections by developing immunity against viral diseases. Some medicinal plants which were used as antipyretic, analgesic, and anti-inflammatory activity helped in treating various diseases and viral infections. Many plants contain flavonoids such as quercetin, luteolin, apigenin, and polyphenols such as thymoquinone, phytosteroids such as cucurbitacin and others which may likely to act as antioxidants and immunomodulatory that can fight against COVID-19. The current review provides information on phytochemical constituents present in medicinal plants, their mechanism of action, in silico molecular docking studies and human clinical trials to treat viral disorders

A Constraint Programming and Hybrid Approach to Nurse Rostering Problems

This paper describes a decision support methodologies for nurse rostering problem in a modern hospital environment. In particular, it is very important to efficiently utilise time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preference. We presented a complete model to formulate all the complex real-world constraints, solution approach and Hybrid approaches to nurse rostering problem. DOI: 10.17762/ijritcc2321-8169.15037

Potential analysis of sunspot parameters and behaviour of random noise

Changes in solar magnetic field are responsible for initialisation and maintenance of different solar processes. Sunspots are clear manifestations of field variations and are good indicators of solar activity. Nature of activity can be well understood by analyzing the underlying sunspot dynamics. Techniques of potential analysis are used in this paper to investigate sunspot numbers and sunspot area, during the period 1875-2012, for finding out their stochastic behaviour. The presence of instabilities in the time series of sunspot numbers and sunspot area are examined in detail. The level of instability in sunspot numbers was observed to be maximum in the years 1953-1955, while that in sunspot area was maximum during 1887-1889. This study also concludes that random noise has a greater effect on dynamics of sunspot area than that on dynamics of sunspot numbers. Presence of high level of noise is noticed in both parameters during 1923-1925. Effect of random noise on the dynamics of sunspot number and area was shown to be very high during the years close to sunspot minima. Results reported can be helpful in predicting evolution of solar activity, which would be crucial in understanding solar-terrestrial phenomena

Total synthesis of (+) Artemisinin

(+) Artemisinin is a sesquiterpene endoperoxide lactone with an unprecedented structure is a natural medicine for the treatment of malaria in particular drug against drug resistant malaria and cerebral malaria. The total synthesis of this novel sesquiterpene is described using an inter-molecular radical reaction on important intermediate iodolactone starting from terpene (+) isolimonene

The Journey of Building Defence Technological Capability

57-62Starting from the design of simple equipment to the development of the most advanced systems DRDO has continued its quest for indigenous defence systems development