Search results for: earnings forecasts

Authors: Seema Singh, Puja Anand, Alok Bhasin

Abstract:

The interior design profession aims to create aesthetically pleasing design solutions for human habitats but of late, growing awareness about depleting environmental resources, both tangible and intangible, and damages to the eco-system led to the quest for creating healthy and sustainable interior environments. The paper proposes adapting traditionally produced organic wool textiles for the mainstream interior design industry. This can create sustainable livelihoods whereby eco-friendly bridges can be built between Interior designers and consumers and pastoral communities. This study focuses on traditional textiles produced by two pastoral communities from India that use organic wool from indigenous sheep varieties. The Gaddi communities of Himachal Pradesh use wool from the Gaddi sheep breed to create Pattu (a multi-purpose textile). The Kurumas of Telangana weave a blanket called the Gongadi, using wool from the Black Deccani variety of sheep. These communities have traditionally reared indigenous sheep breeds for their wool and produce hand-spun and hand-woven textiles for their own consumption, using traditional processes that are chemical free. Based on data collected personally from field visits and documentation of traditional crafts of these pastoral communities, and using traditionally produced indigenous organic wool, the authors have developed innovative textile samples by including design interventions and exploring dyeing and weaving techniques. As part of the secondary research, the role of pastoralism in sustaining the eco-systems of Himachal Pradesh and Telangana was studied, and also the role of organic wool in creating healthy interior environments. The authors found that natural wool from indigenous sheep breeds can be used to create interior textiles that have the potential to be marketed to an urban audience, and this will help create earnings for pastoral communities. Literature studies have shown that organic & sustainable wool can reduce indoor pollution & toxicity levels in interiors and further help in creating healthier interior environments. Revival of indigenous breeds of sheep can further help in rejuvenating dying crafts, and promotion of these indigenous textiles can help in sustaining traditional eco-systems and the pastoral communities whose way of life is endangered today. Based on research and findings, the authors propose that adapting traditional textiles can have potential for application in Interiors, creating eco-friendly spaces. Interior textiles produced through such sustainable processes can help reduce indoor pollution, give livelihood opportunities to traditional economies, and leave almost zero carbon foot-print while being in sync with available natural resources, hence ultimately benefiting the society. The win-win situation for all the stakeholders in this eco-friendly model makes it pertinent to re-think how we design lifestyle textiles for interiors. This study illustrates a specific example from the two pastoral communities and can be used as a model that can work equally well in any community, regardless of geography.

Keywords: design intervention, eco- friendly, healthy interiors, indigenous, organic wool, pastoralism, sustainability

Procedia PDF Downloads 127

Authors: Danah Al-Selahi, Sulaiman Al-Ghunaim, Bashayer Sadiq, Fatma Al-Otaibi, Ali Ameen

Abstract:

In light of recent changes affecting the Oil & Gas Industry, optimization measures have become imperative for all companies globally, including Kuwait Oil Company (KOC). To keep abreast of the dynamic market, a detailed Integrated Asset Plan (IAP) was developed to drive optimization across the organization, which was facilitated through the in-house developed software “Well Inventory Data Entry” (WIDE). This comprehensive and integrated approach enabled centralization of all planned asset components for better well planning, enhancement of performance, and to facilitate continuous improvement through performance tracking and midterm forecasting. Traditionally, this was hard to achieve as, in the past, various legacy methods were used. This paper briefly describes the methods successfully adopted to meet the company’s objective. IAPs were initially designed using computerized spreadsheets. However, as data captured became more complex and the number of stakeholders requiring and updating this information grew, the need to automate the conventional spreadsheets became apparent. WIDE, existing in other aspects of the company (namely, the Workover Optimization project), was utilized to meet the dynamic requirements of the IAP cycle. With the growth of extensive features to enhance the planning process, the tool evolved into a centralized data-hub for all asset-groups and technical support functions to analyze and infer from, leading WIDE to become the reference two-year operational plan for the entire company. To achieve WIDE’s goal of operational efficiency, asset-groups continuously add their parameters in a series of predefined workflows that enable the creation of a structured process which allows risk factors to be flagged and helps mitigation of the same. This tool dictates assigned responsibilities for all stakeholders in a method that enables continuous updates for daily performance measures and operational use. The reliable availability of WIDE, combined with its user-friendliness and easy accessibility, created a platform of cross-functionality amongst all asset-groups and technical support groups to update contents of their respective planning parameters. The home-grown entity was implemented across the entire company and tailored to feed in internal processes of several stakeholders across the company. Furthermore, the implementation of change management and root cause analysis techniques captured the dysfunctionality of previous plans, which in turn resulted in the improvement of already existing mechanisms of planning within the IAP. The detailed elucidation of the 2 year plan flagged any upcoming risks and shortfalls foreseen in the plan. All results were translated into a series of developments that propelled the tool’s capabilities beyond planning and into operations (such as Asset Production Forecasts, setting KPIs, and estimating operational needs). This process exemplifies the ability and reach of applying advanced development techniques to seamlessly integrated the planning parameters of various assets and technical support groups. These techniques enables the enhancement of integrating planning data workflows that ultimately lay the founding plans towards an epoch of accuracy and reliability. As such, benchmarks of establishing a set of standard goals are created to ensure the constant improvement of the efficiency of the entire planning and operational structure.

Keywords: automation, integration, value, communication

Procedia PDF Downloads 115

Authors: Charaia Vakhtang

Abstract:

Global oil prices are seeing new bottoms every day. The prices have already collapsed beneath the psychological verge of 30 USD. This tendency would be fully acceptable for the Georgian consumers, but there is one detail: two our neighboring countries (one friendly and one hostile) largely depend on resources of these hydrocarbons. Namely, the ratio of Azerbaijan in Georgia’s total FDI inflows in 2014 marked 20%. The ratio reached 40% in the January to September 2015. Azerbaijan is Georgia’s leading exports market. Namely, in 2014 Georgia’s exports to Azerbaijan constituted 544 million USD, i.e. 19% in Georgia’s total experts. In the January to November period of 2015, the ratio exceeded 11%. Moreover, Azerbaijan is Georgia’s strategic partner country as part of many regional projects that are designated for long-term perspectives. For example, the Baku-Tbilisi-Karsi railroad, the Black Sea terminal, preferential gas tariffs for Georgia and so on. The Russian economic contribution to the Georgian economy is also considerable, despite the losses the Russian hostile policy has inflicted to our country. Namely, Georgian emigrants are mainly employed in the Russian Federation and this category of Georgian citizens transfers considerable funds to Georgia every year. These transfers account for about 1 billion USD and consequently, these funds previously equalized to total FDI inflows. Moreover, despite the difficulties in the Russian market, Russia still remains a leader in terms of money transfers to Georgia. According to the last reports, money transfers from Russia to Georgia slipped by 276 million USD in 2015 compared to 2014 (-39%). At the same time, the total money transfers to Georgia in 2015 marked 1.08 billion USD, down 25% from 1.44 billion USD in 2014. This signifies the contraction in money transfers is by ¾ dependent on the Russian factor (in this case, contraction in oil prices and the Russian Ruble devaluation directly make negative impact on money transfers to Georgia). As to other countries, it is interesting that money transfers have also slipped from Italy (to 109 million USD from 121 million USD). Nevertheless, the country’s ratio in total money transfers to Georgia has increased to 10% from 8%. Money transfers to Georgia have increased by 22% (+18 million USD) from the USA. Money transfers have halved from Greece to 117 million USD from 205 million USD. As to Turkey, money transfers to Georgia from Turkey have increased by 1% to 69 million USD. Moreover, the problems with the national currencies of Russia and Azerbaijan, along with the above-mentioned developments, outline unfavorable perspectives for the Georgian economy. The depreciation of the national currencies of Azerbaijan and Russia is expected to bring unfavorable results for the Georgian economy. Even more so, the statement released by the Russian Finance Ministry on expected default is in direct relation to the welfare of the whole region and these tendencies will make direct and indirect negative impacts on Georgia’s economic indicators. Amid the economic slowdown in Armenia, Turkey and Ukraine, Georgia should try to enhance economic ties with comparatively stronger and flexible economies such as EU and USA. In other case, the Georgian economy will enter serious turbulent zone. We should make maximum benefit from the EU association agreement. It should be noted that the Russian economy slowdown that causes both regretful and happy moods in Georgia, will make negative impact on the Georgian economy. The same forecasts are made in relation to Azerbaijan. However, Georgia has many partner countries. Enhancement and development of the economic relations with these countries may maximally alleviate negative impacts from the declining economies. First of all, the EU association agreement should be mentioned as a main source for Georgia’s economic stabilization. It is the Georgian government‘s responsibility to successfully fulfill the EU association agreement requirements. In any case the imports must be replaced by domestic products and the exports should be stimulated through government support programs. The Authorities should ensure drawing more foreign investments and money resources, accumulating more tourism revenues and reducing external debts, budget expenditures should be balanced and the National Bank should carry out strict monetary policy. Moreover, the Government should develop a long-term state economic policy and carry out this policy at various Ministries. It is also of crucial importance to carry out constitutive policy and promote perspective directions on the domestic level.

Keywords: oil prices, economic growth, foreign direct investments, international trade

Procedia PDF Downloads 244

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

Procedia PDF Downloads 18