INDUSTRY ACADEMIA COLLABORATION IN THE CONTEXT OF OPEN INNOVATION: EMPIRICAL EVIDENCE FROM PAKISTAN

Industry & academia are building pillars of a country’s knowledge base economy. Industry focus is on practical significance while role of academia is to disseminate knowledge. Although they seem different in their focus; however, there are similarities for innovation-based partnerships. Once Industry & Academia are embedded in the notion of “open innovationâ€, both parties can benefit from collaboration. This is a quantitative study in which drawing upon resource dependence theory, a framework is developed for collaborating factors between industry and academia in the context of Pakistan. Sample from industry and academia is studied using survey instrument and impact of collaboration is measured on magnitude and level of innovation. LISREL based modeling technique is used for quantitatively analyzing proposed framework. Two questions are addressed in this study; What are the antecedents of industry and academia to collaborate in the context of open innovation, and the impact of collaboration on magnitude and level of innovation? This study contains key implications for education sector, industry and policy makers for enhancement of knowledge base in Pakistan

INDUSTRY ACADEMIA COLLABORATION IN THE CONTEXT OF OPEN INNOVATION: EMPIRICAL EVIDENCE FROM PAKISTAN

Industry & academia are building pillars of a country’s knowledge base economy. Industry focus is on practical significance while role of academia is to disseminate knowledge. Although they seem different in their focus; however, there are similarities for innovation-based partnerships. Once Industry & Academia are embedded in the notion of “open innovation”, both parties can benefit from collaboration. This is a quantitative study in which drawing upon resource dependence theory, a framework is developed for collaborating factors between industry and academia in the context of Pakistan. Sample from industry and academia is studied using survey instrument and impact of collaboration is measured on magnitude and level of innovation. LISREL based modeling technique is used for quantitatively analyzing proposed framework. Two questions are addressed in this study; What are the antecedents of industry and academia to collaborate in the context of open innovation, and the impact of collaboration on magnitude and level of innovation? This study contains key implications for education sector, industry and policy makers for enhancement of knowledge base in Pakistan

Short term energy consumption forecasting using neural basis expansion analysis for interpretable time series

Smart grids and smart homes are getting people\u27s attention in the modern era of smart cities. The advancements of smart technologies and smart grids have created challenges related to energy efficiency and production according to the future demand of clients. Machine learning, specifically neural network-based methods, remained successful in energy consumption prediction, but still, there are gaps due to uncertainty in the data and limitations of the algorithms. Research published in the literature has used small datasets and profiles of primarily single users; therefore, models have difficulties when applied to large datasets with profiles of different customers. Thus, a smart grid environment requires a model that handles consumption data from thousands of customers. The proposed model enhances the newly introduced method of Neural Basis Expansion Analysis for interpretable Time Series (N-BEATS) with a big dataset of energy consumption of 169 customers. Further, to validate the results of the proposed model, a performance comparison has been carried out with the Long Short Term Memory (LSTM), Blocked LSTM, Gated Recurrent Units (GRU), Blocked GRU and Temporal Convolutional Network (TCN). The proposed interpretable model improves the prediction accuracy on the big dataset containing energy consumption profiles of multiple customers. Incorporating covariates into the model improved accuracy by learning past and future energy consumption patterns. Based on a large dataset, the proposed model performed better for daily, weekly, and monthly energy consumption predictions. The forecasting accuracy of the N-BEATS interpretable model for 1-day-ahead energy consumption with day as covariates remained better than the 1, 2, 3, and 4-week scenarios

An Empirical Analysis of the Child Labor in the Carpet Industry of Kashmir: Some Major Findings

In the present paper an attempt has been made to study various facts of child labor. Children have been defined here as those in the age group of 6-14 years, working in their family owned or non-family carpet weaving units. The major focus was (I ) to find socio-educational life pattern of child labor, (ii) to locate factors compelling them to join labor force, (iii) to identify their socio-economic and family background, (iv) to delineate various positive and negative aspects of their working conditions,(v) to find the level of earnings of child and its  impact on household income, (vi) to highlight the effects of abolition of child labor on the household, (vii) to identify the role of employers in eliminating child labor, and (viii) to know the opinion of parents and employers on child labor. Multi- stage sampling was used to select child labors from 100 households engaged in carpet units of five village of Quimoh development block of Kulgam district, which was the universe of the present study. In its effort to collect more authentic data, the study has included parents (82) of the child workers and their employers (50) as well. The tools used for data collection were interview schedules besides observations, block development offices etc. The major findings and conclusions that emerge from the analysis and discussion are briefly summarized in the present paper. Apart from these, certain important recommendations are made to ameliorate the condition of child workers in contemporary society and also to prevent the entry of children in carpet weaving in future society

Prevalencija i patološke promjene uzrokovane trakavicom Raillietina cesticillus u domaće kokoši (Gallus gallus domesticus) u himalajskom području Kašmira s umjerenim podnebljem – kratko priopćenje

Research was undertaken into Raillietina cesticillus infection in scavenging indigenous chicken in the Kashmir valley from January 2005 to December 2006. A total of 478 birds of different age groups and both sexes were randomly selected from 10 villages and screened through clinical, parasitological and pathoanatomical examinations. The study indicated that 23.22% (111/478) of the chicken were infected with R. cesticillus either singly or in association with other parasites - Amoebotaenia sphenoides, Raillietina tetragona and Choanotaenia infundibulum. Annual occurrence of the infection was found to be 24.03% (56/233) and 22.44% (55/245). There was a marked seasonal difference in load and mean intensity of infection. A histologically variable degree of degenerative changes was observed with more severe changes in heavy infestation. The inflammatory reaction was characterized by predominant infiltration of heterophils and lymphocytes.U radu je prikazana prevalencija trakavice Raillietina cesticillus u domaće kokoši na području Kašmirske doline u razdoblju od siječnja 2005. do prosinca 2006. Ukupno je pretraženo 478 kokoši različite dobi i spola. Kokoši su nasumično sakupljene na području 10 sela. Za svaku je kokoš zabilježen klinički, parazitološki i patoanatomski nalaz. Istraživanjem je dokazano da je 23,22% (111/478) kokoši bilo invadirano istom trakavicom. U nekih životinja osim ove trakavice dokazane su i druge trakavice poput Amoebotaenia sphenoides, Raillietina tetragona i Choanotaenia infundibulum. Godišnja učestalost trakavice R. cesticilus iznosila je 24,03% (56/233) i 22,44% (55/245). Dokazana je i razlika u sezonskoj učestalosti i to u odnosu na broj trakavica i prosječan intenzitet invazije. Izraženije patohistološke promjene dokazane su u ptica s većom invazijom. Upalni se infiltrat pretežito sastojao od neutrofila i limfocita

ESTIMATION OF AGGREGATE CONSUMPTION FUNCTION FOR HIGH INCOME COUNTRIES

Aggregate Real Private Consumption (ARPC) is one of themajor components of the Gross Domestic Product (GDP) thatcontributes to specify any economy’s long term living standards. The contribution of ARPC stands on average around 55%. It is therefore important to understand the components of consumption, which is almost more than half of the aggregate economic expenditure. The study is an attempt to make a case for developing countries to bring policy level changes in order to determine the consumption pattern of developing countries’ GDP. Using an appropriate empirical model, the study investigates the validity of Permanent Income Hypothesis (PIH) and Absolute Income Hypothesis (AIH) on ARPC for selected developed economies. The results of the study reveal that the importantdeterminants of ARPC in the long-run are real GDP and wealth, while in the short-run they are real interest rate and unemployment rate

Milligan Morgan Haemorrhoidectomy vs LigaSure Haemorrhoidectomy : Comparative Postoperative Outcomes

Objective: To compare the traditional Milligan Morgan haemorrhoidectomy with haemorrhoidectomy using LigaSure in terms of postoperative complications, patient satisfaction and hospital stay. Methodology: This is a randomized controlled trial carried out at the Department of Surgery Liaquat university hospital Jamshoro from July 2017 to June 2019. A total of 88 patients were admitted with the diagnoses of 3rd and 4th degree haemorrhoid were included in the study. Patients were randomly divided into two groups by lottery method. Group A underwent Milligan Morgan Haemorrhoidectomy and group B underwent Haemorrhoidectomy by Ligasure after the informed consent. Outcomes of both procedures were also compared by complications, patient satisfaction and hospital stay. Results: Out of 88 patients 35 were male (39.78%) and 53 were female (60.22%). The most common group of age involved was between 35–55 years. Third degree Haemorrhoids were present in 40 (45.45%) of patients while the remaining 48 (54.55%) had fourth degree Haemorrhoids. Group A included 44(50%) cases while Group B included 44 (50%) cases. The mean operating time of Group A was 50.5 (minutes) with a standard deviation of 11.5 while it was 35.5 ± 9.4 in B group. The mean blood loss in group A was 65.30 ml with a standard deviation of 14.58 while it was 45.45 ml ± 20.49 in group B. Conclusion: The Haemorrhoidectomy done by Ligasure is comparatively better than the Milligan Morgan Heamorrhoidectomy, in terms of operative time, less bleeding, less pain, less hospital stays and early return to work

Improved MRO inventory management system in oil and gas company : increased service level and reduced average inventory investment

This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A (Q, r) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The (Q, r) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization