Impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution

[EN] In this paper, impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution has been studied. The phenomenon of substitution is considered in a stock-out situation and when items become out of stock due to demand then unfulfilled demand is asymmetrically substituted by another item. We formulate the inventory model mathematically and derived optimal ordering quantities, optimal total costs and extreme value of substitution rate for all possible cases. Moreover, pseudo-convexity of the total inventory cost function is obtained and the solution procedure is provided. Numerical example and sensitivity analysis have been presented to validate the effectiveness of the inventory model and substantial improvement in total optimal inventory cost with substitution with respect to optimal total inventory cost without substitution is seen.Mishra, RK.; Mishra, VK. (2020). Impact of cost of substitution and joint replenishment on inventory decisions for joint substitutable and complementary items under asymmetrical substitution. WPOM-Working Papers on Operations Management. 11(2):1-26. https://doi.org/10.4995/wpom.v11i2.13730OJS12611

Design and Validation of Blast Non-propagation Wall for Multi-Compartmented Explosive Storage Structure of Capacity 5T NEC per Compartment

Conventional magazines for hazard division 1.1 are constructed using bricks and reinforced cement concrete (RCC) for which storage inside quantity distance (SIQD) is 2.4 W1/3 m, where W is Net Explosive Content in kg. New composite called laced reinforced concrete (LRC) has been developed recently, for which SIQD has been reduced up to 0.5 W1/3 m. Due to substantial reduction in separation distances, the requirement of land area has been reduced significantly. Although SIQD has been reduced drastically due to development of new composite, the other quantity distances like process inside quantity distance (PIQD) and outside quantity distance (OQD) decreased marginally. To reduce these quantity distances, the solution is multi-compartmented structures based on Unit Risk Principle. The application of unit risk principle enables the separation of explosives into compartments in such a manner that initiation of explosives in one compartment does not result in initiation of the explosives in adjacent compartments. This is achieved by special design of explosive storage buildings incorporating blast non-propagation walls between adjacent compartments storing explosives. Quantity distances are reduced for such magazines, as maximum credible limit corresponds to the quantity of explosive in one compartment. Present paper describes design and full scale testing of blast non-propagation wall between two compartments of a multi-compartmented explosive storage structure with storage capacity of 5 T Net Explosive Content (NEC) of HD 1.1 per compartment. The blast non-propagation wall comprising of sand filling and air gap between LRC walls has been designed for desired attenuation of blast parameters as well as for arresting high velocity fragments/debris. The design has been validated by fully instrumented design validation field trial. The conduct of the trial as well as the results are discussed in this paper

MEDA- AN IMPORTANT MEMBER OF ASTAVARGA IS SUFFERING FROM IDENTIFICATION AND STANDARDIZATION

Meda is one of the most important plants included in Astavarga. This plant is used in variety of Ayurvedic formulations such as Cyavanprasa. Dried underground parts (rhizomes) of this plant are used for medicinal purpose. This plant is claimed to possess rejuvenating, health promoting, immune system strengthening, anti-oxidant and cell regenerating properties. Also claimed to promote body fat, healing fractures, control fever, abdominal thirst, diabetic condition, seminal weakness, and as a cure for Vata, Pitta and Rakta dosa. The demand of this herb is increasing day by day but due to scarcity of this plant in wild, unaware about authentic botanical source, non-existing cultivation practices there is widespread problem of adulteration or substitution with other plants. The poor quality of raw material affect the quality of end product formed. So by taking into account the above situation this systematic review/ metadata analysis has conducted to find out adulteration in Meda

CLINICAL STUDY OF BABOOL (ACACIA ARABICA WILLD.) AND KUKUNDAR (BLUMEA LACERA D.C.) ON ASRIGDARA

Rakta is known to be a vital substance of body. As the disease is characterized by excess flow of blood out of the body, Raktastambhana Chikitisa is beneficial. Treatment prescribed for Raktatisara, Raktapitta, Raktarsha, Guhyaroga and Garbhasrava is also useful. Considering this aspect, Raktastambhaka, Raktsodhana, Raktapittaghna effects are desired in treatment. Haemostatic drugs should be used by giving due consideration to the association of Doshas diagnosed on the basis of colour and smell of the blood. Aims and Objectives: To evaluate the efficacy of Babool and Kukundar and comparative clinical study of Babool and Kukundar on Asrigdara. Materials and Methods: For the present study, patients fulfilling the clinical criteria for diagnosis of Asrigdara will be selected irrespective of their age, sex, religion, etc, in random from O.P.D. section of M. M. M. Govt. Ayurveda College hospital, Udaipur (Raj.). Case history of all the patients was taken in the specially prepared proforma. Conclusion: Babool due to its astringent taste and Kunkundar due to its bitter taste, both drugs pacify excessive Pitta humour which is main cause of Asrigdara. Their chemical constituents possess haemostatic and anti-inflammatory properties thus considering these facts, these drugs have been selected for present study

Advancing coding theory and mean field games via decentralized optimization and deep learning

The advent of new learning approaches like deep learning and reinforcement learning has enhanced our capability to look at decentralized optimization problems with new dimensions and solve them with new insights. In this work, we have focused on such problems in coding theory for communication systems and mean-field games. We consider a coding problem where the transmitter and the receiver cooperate in a decentralized manner to develop an encoding strategy for channels with feedback. We use control theory basics like Markov decision process (MDP), dynamic programming, and deep learning to solve these problems. We also consider an interference channel problem where the transmitters cooperate in a distributed fashion and obtain an encoding scheme to maximize the sum rate. Finally, we consider a multi-agent system and use a decentralized mechanism of mean eld games and reinforcement learning to solve for the optimal strategies. In part I, we propose linear sequential coding for communication channels with passive noisy output feedback with peak power constraint and a total power constraint. We propose a dynamic programming algorithm that solves an MDP to obtain analytical expressions for the scheme and the final Mean Squared Error (MSE) expression. We show the outperformance of our schemes against the state-of-the-art schemes. In part II, we use RNN based encoder at the transmitter and the receiver for encoding channels with active feedback, which outperform the traditional approaches. We also propose an analytical scheme by interpreting the codes obtained using the deep learning method. We also implement our scheme on a hardware SDR setup and showcase the performance improvement in the over-the-air environment. In part III, we consider a multiuser interference channel with transmitter and receiver pairs. Prior work proposed schemes using linear interference alignment techniques to transmit the messages through interference-free subspaces. We propose deep learning approaches to develop encoding schemes for the messages. We showcase that using message bits for training can produce intelligent non-intuitive encoding schemes that perform better than the general interference alignment schemes. In part IV, we consider the classic game theory problem of mean-field games, which we solve using sequential decomposition and model-free reinforcement learning techniques, which are more efficient than those previously used for multi-agent systems. We also provide an inverse reinforcement algorithm that proposes optimal strategies for games without the knowledge of the reward function.Electrical and Computer Engineerin

Edge Computing in IoT: Vision and Challenges

The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction

RELEVANCE OF KAKOLI (ONE AMONG ASTAVARGA) IN ANCIENT AYURVEDIC TREATISE ALONG WITH ETYMOLOGY OF ITS VARIOUS SANSKRIT SYNONYMS

The knowledge about medicinally useful plants in the early age is scientifically documented, and systematically organized in Ayurveda Samhitas, Nighantus and other texts. The ancient nomenclature of Ayurvedic herbs was not only useful for their identification but also to know their medicinal values for example, Payasvinī means galactogogue, Kākolī means which contains high moisture value, Madhurā means Madhura in Rasa, etc. Moreover, our Acharyas also suggested different names of the Ayurvedic herbs based on their habits, taxonomy and uses. Though the modern science is successful in classifying the flora taxonomically, but could not reach up to the ground breaking concept of classifying plants according to their medicinal properties. Being aware of taxonomic aspects of nomenclature along with the torch of synonyms coined by ancient seers one may be able to preserve the treasury traditional medicinal knowledge. Kākolī has been mentioned as one of the Aṣṭavarga plants. Kākolī has also been documented in the various Saṁhitā and Nighaṇṭu. Description of Kākolī along with its Sanskrit synonyms, habitat and medicinal properties has also been mentioned in different Nighaṇṭu. However, due to the lack of appropriate taxonomic data, mainly three plant species i.e., Roscoea purpurea Sm., Roscoea capitata Sm. and Roscoea alpina Royle are widely accepted as Kākolī. The main objective of this study was to critically review the Sanskrita name of Kākolī described in classical Ayurvedic literature along with medicinal properties

Image Contrast Enhancement with Brightness Preserving Using Feed Forward Network

Image improvement techniques are very useful in our daily routine.In the field of image enhancement Histogram Equalization is a very powerful, effective and simple method. Histogram Equalization (HE) is a popular, simple, fast and effective technique for improving the gray image quality. Contrast enhancement was very popular method but it was not able to preserve the brightness of image. Image Dependent Brightness Preserving Histogram Equalization (IDBPHE) technique improve the contrast as well as preserve the brightness of a gray image. Image features Peak Signal to Noise Ratio (PSNR) and Absolute Mean Brightness Error (AMBE) are the parameters to measure the improvement in a gray image after applying the algorithm. Unsupervised learning algorithm is an important method to extract the features of neural network. We propose an algorithm in which we extract the features of an image by unsupervised learning. After apply unsupervised algorithm on the image the PSNR and AMBE features are improved