Detection of Grape Clusters in Images using Convolutional Neural Network

Convolutional Neural Networks and Deep Learning have revolutionized every field since their inception. Agriculture has also been reaping the fruits of developments in mentioned fields. Technology is being revolutionized to increase yield, save water wastage, take care of diseased weeds, and also increase the profit of farmers. Grapes are among the highest profit-yielding and important fruit related to the juice industry. Pakistan being an agricultural country, can widely benefit by cultivating and improving grapes per hectare yield. The biggest challenge in harvesting grapes to date is to detect their cluster successfully; many approaches tend to answer this problem by harvest and sort technique where the foreign objects are separated later from grapes after harvesting them using an automatic harvester. Currently available systems are trained on data that is from developed or grape-producing countries, thus showing data biases when used at any new location thus it gives rise to a need of creating a dataset from scratch to verify the results of research. Grape is available in different sizes, colors, seed sizes, and shapes which makes its detection, through simple Computer vision, even more challenging. This research addresses this issue by bringing the solution to this problem by using CNN and Neural Networks using the newly created dataset from local farms as the other research and the methods used don’t address issues faced locally by the farmers. YOLO has been selected to be trained on the locally collected dataset of grapes

cISP: A Speed-of-Light Internet Service Provider

Low latency is a requirement for a variety of interactive network applications. The Internet, however, is not optimized for latency. We thus explore the design of cost-effective wide-area networks that move data over paths very close to great-circle paths, at speeds very close to the speed of light in vacuum. Our cISP design augments the Internet's fiber with free-space wireless connectivity. cISP addresses the fundamental challenge of simultaneously providing low latency and scalable bandwidth, while accounting for numerous practical factors ranging from transmission tower availability to packet queuing. We show that instantiations of cISP across the contiguous United States and Europe would achieve mean latencies within 5% of that achievable using great-circle paths at the speed of light, over medium and long distances. Further, we estimate that the economic value from such networks would substantially exceed their expense

STYLE SHIFTING FROM NATIVE TO NON-NATIVE ENGLISH FICTION VIA MULTIPLE PERSPECTIVES: A COMPARATIVE ANALYSIS OF JANE AUSTEN’S PRIDE AND PREJUDICE AND SONIAH KAMAL’S UNMARRIAGEABLE

The paper examines the style shifting in two novels, Jane Austen's Pride and Prejudice and Soniah Kamal's Unmarriageable, both of which are written in English but from different cultural and linguistic backgrounds. The study aims to analyze the stylistic differences between native English and non-native English fiction through multiple lenses, including code-switching, Urduization, and style shifting. The study begins by providing a brief overview of the two novels and their respective cultural and linguistic contexts. It presents the concept of style shifting and its importance in literary analysis. It is explained how style shifting can be used as a tool to examine the intersection of language and culture in literary works. The paper explores how both Pride and Prejudice and Unmarriageable utilize code-switching to reflect the linguistic and cultural identities of the characters. The study underscores the importance of considering linguistic and cultural diversity in literary analysis and provides insights into the stylistic differences between native and non-native English fiction. The study ends with the suggestions that both "Pride and Prejudice" and "Unmarriageable" are works of fiction, and both deal with themes of love, marriage, and societal expectations. However, they are set in different time periods and cultural contexts, and as such, the writing styles of the two novels differ

Prevalence of Self-Medication among Urban and Rural Population of Islamabad, Pakistan

Purpose: To evaluate the prevalence and associated factors of self-medication among urban and rural population of Islamabad, Pakistan.Methods: A cross-sectional study was conducted among 500 participants using random sampling method. A pretested questionnaire was used to collect the data from urban and rural areas of Islamabad. Chi  square/Fisher’s exact test was used to compare two groups.Results: Overall, 61.2% of participants practised self-medication and it was more prevalent among 15-30 years age group. An association was found between self-medication and residence, gender, and education (p<0.05). A majority of participants (n = 364, 72.8%) trusted Allopathic system the most. Pain was the most likely indication (n = 207, 67.6%) for which participants self-medicated (p<0.05). Analgesics were the most likely (n = 187, 61.1%) medicine class used (p<0.05), majorly, paracetamol. Mild illness (n = 128, 41.8%) was determined as the most common reason (p<0.05). Generally, higher proportion of urban participants reported “previous experience” and “time saving” as the most common reason for the practice of self-medication in contrast to “economical” and “lack of health care facilities” described by rural participants. A majority of the participants (n = 186, 60.8%) self-medicated on their own initiative  (p<0.001). Generally, higher percentage of urban participants reported family/friends (27.9% versus 15.7%) as the commonest source in contrast to medical professionals (21.6% versus 5.2%) reported by rural respondents.Conclusion: This study shows an association between self-medication and gender, residence, and education. Urban and rural participants significantly differ on the most common reason, symptom, source and class of drug used for self-medication.Keywords: Self medication, Prevalence, Rural, Urban, Analgesic

Success of transgenic cotton (Gossypium hirsutum L.): Fiction or reality?

Cotton (Gossypium hirsutum L.) being one of the top most cash crop is reckoned as main pillar of textile industry. Cotton cultivation has experienced an outstanding escalation story over the years. The per unit yield and area under cultivation have all incremented to record towering levels. But question is how Bt cotton has contributed and whether it is satisfactory or not. At present for finding a conclusion, we need unfathomable analyses and investigations related to multiple aspects of global cotton cultivation. Genetic engineering is considered as an imperative tool in cotton breeding with a role in empowerment of traditional strategies for improvement in net yield and related factors. Among multitude of reasons for massive shifting to Bt cotton cultivation in the world include inadequate germplasm, climatic conditions, irrigated area, usage of fertilizers and pesticides. We should consider Bt cotton a miracle solution .Therefore, it is probable that Bt cotton along with newly developed strategies, improved irrigation systems and superior chemical application may enhance the production quality and quantity as well. Our review brings into light the success of cotton genetic engineering over the last two decades and probable future prospects

Untangling Header Bidding Lore

Header bidding (HB) is a relatively new online advertising technology that allows a content publisher to conduct a client-side (i.e., from within the end-user's browser), real-time auction for selling ad slots on a web page. We developed a new browser extension for Chrome and Firefox to observe this in-browser auction process from the user's perspective. We use real end-user measurements from 393,400 HB auctions to (a) quantify the ad revenue from HB auctions, (b) estimate latency overheads when integrating with ad exchanges and discuss their implications for ad revenue, and (c) break down the time spent in soliciting bids from ad exchanges into various factors and highlight areas for improvement. For the users in our study, we find that HB increases ad revenue for web sites by 28backslash% compared to that in real-time bidding as reported in a prior work. We also find that the latency overheads in HB can be easily reduced or eliminated and outline a few solutions, and pitch the HB platform as an opportunity for privacy-preserving advertising

An Enhanced Multi-Objective Gray Wolf Optimization for Virtual Machine Placement in Cloud Data Centers

Cloud computing offers various services. Numerous cloud data centers are used to provide these services to the users in the whole world. A cloud data center is a house of physical machines (PMs). Millions of virtual machines (VMs) are used to minimize the utilization rate of PMs. There is a chance of unbalanced network due to the rapid growth of Internet services. An intelligent mechanism is required to efficiently balance the network. Multiple techniques are used to solve the aforementioned issues optimally. VM placement is a great challenge for cloud service providers to fulfill the user requirements. In this paper, an enhanced levy based multi-objective gray wolf optimization (LMOGWO) algorithm is proposed to solve the VM placement problem efficiently. An archive is used to store and retrieve true Pareto front. A grid mechanism is used to improve the non-dominated VMs in the archive. A mechanism is also used for the maintenance of an archive. The proposed algorithm mimics the leadership and hunting behavior of gray wolves (GWs) in multi-objective search space. The proposed algorithm was tested on nine well-known bi-objective and tri-objective benchmark functions to verify the compatibility of the work done. LMOGWO was then compared with simple multi-objective gray wolf optimization (MOGWO) and multi-objective particle swarm optimization (MOPSO). Two scenarios were considered for simulations to check the adaptivity of the proposed algorithm. The proposed LMOGWO outperformed MOGWO and MOPSO for University of Florida 1 (UF1), UF5, UF7 and UF8 for Scenario 1. However, MOGWO and MOPSO performed better than LMOGWO for UF2. For Scenario 2, LMOGWO outperformed the other two algorithms for UF5, UF8 and UF9. However, MOGWO performed well for UF2 and UF4. The results of MOPSO were also better than the proposed algorithm for UF4. Moreover, the PM utilization rate (%) was minimized by 30% with LMOGWO, 11% with MOGWO and 10% with MOPSO

cISP: A Speed-of-Light Internet Service Provider

Low latency is a requirement for a variety of interactive network applications. The Internet, however, is not optimized for latency. We thus explore the design of wide-area networks that move data at nearly the speed of light in vacuum. Our cISP design augments the Internet's fiber with free-space microwave wireless connectivity over paths very close to great-circle paths. cISP addresses the fundamental challenge of simultaneously providing ultra-low latency while accounting for numerous practical factors ranging from transmission tower availability to packet queuing. We show that instantiations of cISP across the United States and Europe would achieve mean latencies within 5% of that achievable using great-circle paths at the speed of light, over medium and long distances. Further, using experiments conducted on a nearly-speed-of-light algorithmic trading network, together with an analysis of trading data at its end points, we show that microwave networks are reliably faster than fiber networks even in inclement weather. Finally, we estimate that the economic value of such networks would substantially exceed their expense