Diversification strategy, financial performance and stability in the foodservice industry

Diversification strategy and its relationship to performance has been shown to increase the profitability and stability of firms. An investigation was conducted to determine the relationship between diversification strategy and financial performance and stability of firms in the foodservice industry. Rumelt\u27s (1974) diversification measure was utilized and modified to analyze the performance and stability of seventy-three foodservice firms from 1988-1991; Statistical testing using non-parametric tests showed no significant differences between diversification strategy and financial performance and stability of foodservice firms over the entire period from 1988-1991. However, when the time-frame was reduced to 2 sub-periods; before and during recession, significant differences were found in the variability in return on assets and total stock returns. The results showed that the business cycle affects the market performance and stability of foodservice firms

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry

Post-Harvest Storage Studies With Selected Fruits

It has been estimated that one-fourth of the fresh fruits harvested are never consumed because of spoilage. This spoilage amounts to many thousands of tons of fruits which are valued annually at several million dollars. Several factors are responsible for the post-harvest spoilage of fruits, namely, pathological, physiological, and mechanical. Men in the past have used various methods to control pathological spoilage of foods. The recent development of nuclear radiation, antibiotics, fungicides, and packaging films provides new methods for prolonging the shelf-life of many fruits. These may prove important in countries like India where refrigeration facilities are not readily available and food shortage has always been a problem. Likewise, in the United States, the present-day marketing of fresh fruits has become more and more complex because centers of consumption are increasingly remote from centers of production. To understand physiological and mechanical spoilage of fruits one should know that perishable products are alive, even though the connection with the source of nourishment has been severed. Continued metabolism and increase in respiration result in over-ripeness, physiological decay, and wilting. The deterioration of fruits by the processes of accelerated respiration induced by ripening, physical changes, and subsequent mechanical damage during transit cannot be stopped; but it can be retarded by lowering the temperature, by treating with respiratory inhibitors, and by careful handling

Contribution of Sfisim to Kashmir: Historical Perspective

This paper focuses on the perception of Kashmiri Pandit participants on Sufism and Rishi culture of Kashmir This generation of Kashmiri Pandit have lived significant years of their lives in Kashmir and have remained closely associated with the Sufi and Rishi traditions of Kashmir They have had immense faith in the shrines of Sufi saints The shrines of Sufi saints were revered by Kashmiri Pandits not only in a similar manner but more than their Kashmir i Muslim compatriots as told by the o lder generation of Kashmiri Muslims participants Kashmiri Muslims had deep faith in these shrines That has also contributed towards strengthening the of bond of brotherhood bahichara between Kashmiri Muslims and Kashmiri Pandits as both had close association with these practices irrespective of their own religious faith

Starch Grain Characters, Amylose, and Amylo-Pectin Contents in Relation to Pollination Time and Formation of Cotyledons in \u3cem\u3ePhaseolus lunatus\u3c/em\u3e L. and \u3cem\u3ePhaseolus polystachyus\u3c/em\u3e L.

Beans are an important source of carbohydrates, proteins, minerals, and vitamins for millions of vegetarians in the world, especially in Asia. The quality and harvesting time of beans depend upon the purpose for which the beans are used. For example, for canning and freezing the beans should be harvested when they are neither starchy nor watery but should be sugary. The processing industry in Asia is not highly developed. Hence, the food is usually preserved by sun drying. Sun dried beans are often consumed the year around

IoT Based Machine Learning Weather Monitoring and Prediction Using WSN

A novel approach to analysis and prediction is provided by the internet of things-based time monitoring and prediction system using wireless sensor networks (WSN) and machine learning techniques (ML). To give accurate meteorological data in real time, the integrated system uses IoT, WSN, and ML. Making informed decisions requires these insights. Includes strategically positioned infrared points that are used to gather meteorological information, such as temperature, humidity, pressure, and wind speed, among other things.The machine's automatic data processing methods are then used in a central processing unit to collect and analyse the data. By seeing patterns and drawing diagrams utilising previously collected data, ML models are able to comprehend intricate temporal dynamics. An important development in this system is its predictive capabilities. Artificial intelligence has the processing power to precisely forecast short-term weather patterns, enabling the rapid transmission of warnings for extreme localised events and the reduction of potential dangers.The combination of historical data, real-time sensor inputs, and automated analysis produces the predictive potential. The "Internet of Things" architecture used to develop this system makes it simpler to gather meteorological data. A number of industries, including as agriculture, transportation, emergency management, and event planning, are encouraged to make data-based decisions since users can quickly obtain current meteorological conditions and forecasts through user-friendly web interfaces or mobile applications

Design of 3-side Truncated Patch Antenna for UWB Applications

A 3-sided truncated microstrip patch antenna for ultra wideband (UWB) applications has been presented in this paper. The proposed antenna is compact in size and design on FR4 substrate. In order to validate the antenna performance, simulated results have been reported using HFSS EM solver. The proposed antenna is feasible for WLAN, WIMAX, Wi-Fi and other various wireless applications

Enhancing Security in Internet of Healthcare Application using Secure Convolutional Neural Network

The ubiquity of Internet of Things (IoT) devices has completely changed the healthcare industry by presenting previously unheard-of potential for remote patient monitoring and individualized care. In this regard, we suggest a unique method that makes use of Secure Convolutional Neural Networks (SCNNs) to improve security in Internet-of-Healthcare (IoH) applications. IoT-enabled healthcare has advanced as a result of the integration of IoT technologies, giving it impressive data processing powers and large data storage capacity. This synergy has led to the development of an intelligent healthcare system that is intended to remotely monitor a patient's medical well-being via a wearable device as a result of the ongoing advancement of the Industrial Internet of Things (IIoT). This paper focuses on safeguarding user privacy and easing data analysis. Sensitive data is carefully separated from user-generated data before being gathered. Convolutional neural network (CNN) technology is used to analyse health-related data thoroughly in the cloud while scrupulously protecting the privacy of the consumers.The paper provide a secure access control module that functions using user attributes within the IoT-Healthcare system to strengthen security. This module strengthens the system's overall security and privacy by ensuring that only authorised personnel may access and interact with the sensitive health data. The IoT-enabled healthcare system gets the capacity to offer seamless remote monitoring while ensuring the confidentiality and integrity of user information thanks to this integrated architecture