Suchergebnisse

The sustainable consumption and production is crucially relevant for Pakistan, given the massive degradation and depletion of natural resources due to the population explosion – and agricultural and industrial development pursued without regard for environmental sustainability. Freshwater availability has declined and quality of drinking water has deteriorated, leading to increase in water-borne diseases. The decaying water infrastructure results in a 40pc water loss in conveyance from dams to farms, for agricultural development. Industrial, agricultural, and household chemicals are freely imported and used without any regulatory system. Massive depletion of natural resources has meant the cutting of trees, resulting in increased timber imports. Pakistan National Action Plan (PNAP) was developed in May 2017 to achieve the sustainable goal particularly goal 12, which is about Sustainable Consumption and Production (SCP). This paper focuses on the ingenious activity and strategy devised in the PNAP for the preparedness, implementation and monitoring of the SDG-12, as National Developmental Agenda of Pakistan. Utilizing library research methods, the major material used for this research is qualitatively collected by analyzing the contents of documents. For primary data, government documents have been consulted. Whereas the secondary data has been collected from books and articles available on the theme.

The sustainable consumption and production is crucially relevant for Pakistan, given the massive degradation and depletion of natural resources due to the population explosion – and agricultural and industrial development pursued without regard for environmental sustainability. Freshwater availability has declined and quality of drinking water has deteriorated, leading to increase in water-borne diseases. The decaying water infrastructure results in a 40pc water loss in conveyance from dams to farms, for agricultural development. Industrial, agricultural, and household chemicals are freely imported and used without any regulatory system. Massive depletion of natural resources has meant the cutting of trees, resulting in increased timber imports. Pakistan National Action Plan (PNAP) was developed in May 2017 to achieve the sustainable goal particularly goal 12, which is about Sustainable Consumption and Production (SCP). This paper focuses on the ingenious activity and strategy devised in the PNAP for the preparedness, implementation and monitoring of the SDG-12, as National Developmental Agenda of Pakistan. Utilizing library research methods, the major material used for this research is qualitatively collected by analyzing the contents of documents. For primary data, government documents have been consulted. Whereas the secondary data has been collected from books and articles available on the theme.

The use of data from social networks such as Twitter has been increased during the last few years to improve political campaigns, quality of products and services, sentiment analysis, etc. Tweets classification based on user sentiments is a collaborative and important task for many organizations. This paper proposes a voting classifier (VC) to help sentiment analysis for such organizations. The VC is based on logistic regression (LR) and stochastic gradient descent classifier (SGDC) and uses a soft voting mechanism to make the final prediction. Tweets were classified into positive, negative and neutral classes based on the sentiments they contain. In addition, a variety of machine learning classifiers were evaluated using accuracy, precision, recall and F1 score as the performance metrics. The impact of feature extraction techniques, including term frequency (TF), term frequency-inverse document frequency (TF-IDF), and word2vec, on classification accuracy was investigated as well. Moreover, the performance of a deep long short-term memory (LSTM) network was analyzed on the selected dataset. The results show that the proposed VC performs better than that of other classifiers. The VC is able to achieve an accuracy of 0.789, and 0.791 with TF and TF-IDF feature extraction, respectively. The results demonstrate that ensemble classifiers achieve higher accuracy than non-ensemble classifiers. Experiments further proved that the performance of machine learning classifiers is better when TF-IDF is used as the feature extraction method. Word2vec feature extraction performs worse than TF and TF-IDF feature extraction. The LSTM achieves a lower accuracy than machine learning classifiers.

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m2 outdoors and and 6000 m2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks. ; Fundación para la Ciencia y Tecnología; 10.13039/100007225-Ministry of Science and Technology; Institute for Information and communications Technology Promotion IITP grant funded by the Korea government MSIT; Basic Science Research Program through the National Research Foundation of Korea NRF funded by the Ministry of Science; MSIT Ministry of Science and ICT Korea under the ITRC; Slovak Research and Development Agency; Strategic Priority Research Program; Korea government NFA; ICT R and D Program of MSIPIITP; 10.13039/501100004837-Ministerio de Ciencia e Innovación; JSPS KAKENHI; ICT R and D Program of MSIPIITP. ; Peer reviewed