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Author(s):  
Arinbjörn Kolbeinsson ◽  
Naman Shukla ◽  
Akhil Gupta ◽  
Lavanya Marla ◽  
Kartik Yellepeddi

Ancillaries are a rapidly growing source of revenue for airlines, yet their prices are currently statically determined using rules of thumb and are matched only to the average customer or to customer groups. Offering ancillaries at dynamic and personalized prices based on flight characteristics and customer needs could greatly improve airline revenue and customer satisfaction. Through a start-up (Deepair) that builds and deploys novel machine learning techniques to introduce such dynamically priced ancillaries to airlines, we partnered with a major European airline, Galactic Air (pseudonym), to build models and algorithms for improved pricing. These algorithms recommend dynamic personalized ancillary prices for a stream of features (called context) relating to each shopping session. Our recommended prices are restricted to be lower than the human-curated prices for each customer group. We designed and compared multiple machine learning models and deployed the best-performing ones live on the airline’s booking system in an online A/B testing framework. Over a six-month live implementation period, our dynamic pricing system increased the ancillary revenue per offer by 25% and conversion rate by 15% compared with the industry standard of human-curated rule-based prices.


SENTRALISASI ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 77
Author(s):  
Putri Noviati ◽  
Elva Nuraina ◽  
Nur Wahyuning Sulistyowati

This study aims to analyze PT INKA's export marketing strategy towards competitive advantage until 2018. Researchers use primary and secondary data sources with interview and documentation data collection techniques. The results of the study revealed that PT. INKA has: (1) Strength, very competitive pricing power and strong human resources, especially the marketing team, in addition to the influence of marketing assistance from the ambassador (RI for overseas); (2) Weaknesses in the export marketing strategy lie in production, one of which is engines and wheels which are still imported by China, which does not yet have the International Railway Industry Standard Certification (IRIS); (3) Opportunities, can make efforts to further strengthen the penetration of Indonesian companies in the African region; (4) Threats, to providers of facilities and infrastructure needs that must be obtained from imports from other countries, besides that competitors are afraid to dare to reduce interest costs or extend the tenor for the purchase of goods. The high taxes that must be issued for the delivery of goods are the biggest threat, this is confirmed by the informants.


2022 ◽  
Vol 16 (4) ◽  
pp. 96-104
Author(s):  
Evgeniy Ivanov ◽  
Liya Malinina ◽  
Nikolay Pushkarenko ◽  
Lyudmila Kornilova ◽  
Anatoliy Korotkov

The modern hop-growing industry occupies a small share in the structure of domestic agricultural production. However, being the main supplier of hops, as the most important agricultural raw material for many sectors of the economy, it has been on the rise in recent years and is increasing production volumes every year. This is largely facilitated by financial government support in terms of reimbursement of current and capital costs associated with the establishment of hops and the cultivation of hops. The purpose of the study is to consider the main theoretical and methodological aspects of organizing production accounting, which will provide unified approaches to justifying costs for filing applications by hop farms for government subsidies. As a result of the analysis, it turned out that there is no updated regulatory framework for accounting for the reflection of costs in hop-growing farms, including the basic industry standard “Hop-growing. Terms and definitions ”, and in the very mechanism for issuing state subsidies, the question of the structure and content of the information carrier about the costs incurred has not been finally worked out. A small number of international and Russian studies to determine the essential characteristics of hops as a biological asset have a negative impact on the construction of the accounting process. Consideration of the theory and study of the practice of organizing the accounting of costs in hop farms made it possible to update the accounting procedures for the main agro-technological stages in accordance with the current regulatory documents in this area and to put forward the thesis on the need to use 1 ton of alpha-acid as a calculating unit and a universal meter when making calculations with counterparties


2022 ◽  
Author(s):  
Subhagata Chattopadhyay ◽  
Rupam Das ◽  
Shalini Gaur

Abstract Lyfas is a smartphone-based biomedical application that captures the cardiovascular autonomic biomarkers (CVb), surrogating for mental health attributes. SD1/SD2 biomarker assesses the sympathovagal balance and is considered to be a potential indicator of Lyfas anxiety score (LAS). A total of 1837 males and 973 females took Lyfas (hypersensitivity-checked) and Hamilton Anxiety Rating Scale (HAM-A) self-scoring tests. LAS has been statistically validated by Linear regressions, one-way ANOVA, t-stat, correlations (r), and Bland Altman agreement assessment with respect to HAM-A. Sensitivity, specificity, precision, accuracy, Fscore, and Youden’s index (j-stat) are computed. Results show that (i) Lyfas is not a very hypersensitive instrument (mean-variance is 0.6). (ii) It can predict HAM-A with 94.7% accuracy (R2) and is a statistically significant model (p <0.05). (iii) LAS and HAM-A are positively correlated by 97%, the t-stat value of 5.38 for the population indicates that the two instruments have a significant mean difference. (iv) Bland Altman test showcases the overall agreement of 12.95% due to different modes and scales of measurements. (v) on average, LAS is 87.78% accurate, 86.82% precise, and its’ 65.2% j-stat value proves that Lyfas is a novel industry-standard smartphone biomarker application that can be used to accurately screen anxiety disorders.


Author(s):  
Christophe Bastien ◽  
Alexander Diederich ◽  
Jesper Christensen ◽  
Shahab Ghaleb

With the increasing use of Computer Aided Engineering, it has become vital to be able to evaluate the accuracy of numerical models. This research poses the problem of selection of the most accurate and relevant correlation solution to a set of corridor variations. Specific methods such as CORA, widely accepted in industry, are developed to objectively evaluate the correlation between monotonic functions, while the Minimum Area Discrepancy Method, or MADM, is the only method to address the correlation of non-injective mathematical variations, usually related to force/acceleration versus displacement problems. Often, it is not possible to differentiate objectively various solutions proposed by CORA, which this paper proposes to answer. This research is original, as it proposes a new innovative correlation optimisation framework, which can select the best CORA solution by including MADM as a subsequent process. The paper and the methods are rigorous, having used an industry standard driver airbag computer model, built virtual test corridors and compared the relationship between different CORA and MADM ratings from 100 Latin Hypercube samples. For the same CORA value of ‘1’ (perfect correlation), MADM was capable to objectively differentiate between 13 of them and provide the best correlation possible. The paper has recommended the MADM settings n = 1; m = 2 or n = 3; m = 2 for a congruent relationship with CORA. As MADM is performed subsequently, this new framework can be implemented in already existing industrial processes and provide automotive manufacturers and Original Equipment Manufacturers (OEM) with a new tool to generate more accurate computer models.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Khalid Twarish Alhamazani ◽  
Jalawi Alshudukhi ◽  
Saud Aljaloud ◽  
Solomon Abebaw

Chronic kidney disease (CKD) is a global health issue with a high rate of morbidity and mortality and a high rate of disease progression. Because there are no visible symptoms in the early stages of CKD, patients frequently go unnoticed. The early detection of CKD allows patients to receive timely treatment, slowing the disease’s progression. Due to its rapid recognition performance and accuracy, machine learning models can effectively assist physicians in achieving this goal. We propose a machine learning methodology for the CKD diagnosis in this paper. This information was completely anonymized. As a reference, the CRISP-DM® model (Cross industry standard process for data mining) was used. The data were processed in its entirety in the cloud on the Azure platform, where the sample data was unbalanced. Then the processes for exploration and analysis were carried out. According to what we have learned, the data were balanced using the SMOTE technique. Four matching algorithms were used after the data balancing was completed successfully. Artificial intelligence (AI) (logistic regression, decision forest, neural network, and jungle of decisions). The decision forest outperformed the other machine learning models with a score of 92%, indicating that the approach used in this study provides a good baseline for solutions in the production.


Author(s):  
М.М. Улитин ◽  
В.П. Бессчетнов

Изучали таксационные показатели лесных культур лиственницы Сукачева, заложенных в 1986 г. на юго-западной границе естественного распространения вида в Сергачском межрайонном лесничестве Нижегородской области. Координаты первого участка N 55.541378, E 45.471119; второго – N 55.541388, E 45.471125. Получена оценка эффективности их создания в указанном регионе. Методологической основой рабочих методик служил принцип единственного логического различия. Работа выполнялась полевым стационарным методом. Характеристика культур лиственницы давалась по результатам натурного обследования. Пробные площади закладывали в соответствии с действующим отраслевым стандартом. Подтверждена благоприятность лесорастительных условиях для естественного произрастания лиственницы Сукачева и широкие возможности интродукции близкородственных видов. Обнаружена неодинаковая изменчивость таксационных показателей. В частности, по диаметру ствола и его высоте она незначительна и отнесена преимущественно к низкому уровню: на первом участке 14,21% и 11,34%; на втором – 17,11 и 9,16% соответственно. По другим признакам изменчивость выше (чаще средний и повышенный уровень) и в ряде случаев достигает высокого (объем ствола) и очень высокого (коэффициент асимметрии кроны) уровня. Зафиксированы существенные различия между участками лесных культур по большинству таксационных показателей, подтвержденные дисперсионным анализом. Эффект их влияния на общий фон фенотипической дисперсии неодинаков. По диаметру ствола он минимален и составил 6,68±1,37%. Наибольшие оценки получены по расстоянию до первого живого сучка – 30,42±1,05%. Определено, что лесные культуры лиственницы Сукачева, созданные в Нижегородской области, достигая к возрасту 34 высоты 14 – 15 м, формируют насаждения первого класса бонитета. We studied the taxation indicators of forest crops of Sukhdev larch, laid in 1986 on the south-western border of the natural distribution of the species in the Sergachsky interdistrict forestry of the Nizhny Novgorod region. The coordinates of the first section are N 55.541378, E 45.471119; the second section is N 55.541388, E 45.471125. An assessment of the effectiveness of their creation in the specified region was obtained. The methodological basis of the working methods was the principle of the only logical difference. The work was carried out by the field stationary method. The characteristics of larch crops were given based on the results of a field survey. The test areas were laid in accordance with the current industry standard. The favorable forest conditions for the natural growth of Sukachev larch and the wide opportunities for the introduction of closely related species were confirmed. Unequal variability of taxation indicators was found. In particular, in terms of trunk diameter and height, it is insignificant and is mainly attributed to the low level: in the first section, 14.21% and 11.34%; in the second-17.11 and 9.16%, respectively. According to other signs, the variability is higher (more often the average and increased level) and in some cases reaches a high (trunk volume) and very high (crown asymmetry coefficient) level. Significant differences between forest crop plots were recorded in most of the taxation indicators, which were confirmed by the analysis of variance. The effect of their influence on the general background of the phenotypic variance is not the same. By the diameter of the trunk, it is minimal and amounted to 6.68±1.37%. The highest estimates were obtained for the distance to the first live knot – 30.42±1.05%. It is determined that the forest cultures of Sukachev larch, created in the Nizhny Novgorod region, reaching a height of 14-15 m by the age of 34, form plantings of the first class of bonitet.


2021 ◽  
Vol 2 (1) ◽  
pp. 28-33
Author(s):  
Handini Arga Damar Rani

Tehnik data mining dapat digunakan dalam berbagai bidang salah satunya dalam aspek data mining, buat memperkirakan sebuah penyakit dari data rekam medis pasien. Teknik riset yang dipakai pada riset ini mengikuti berbagai tahapan model “Cross-Industry Standard Process Data Mining” (CRISP-DM). Melalui metode klasifikasi dalam data mining, atribut data seperti usia, tekanan darah, berat badan, posisi janin, dan tinggi fundus uteri bisa dipakai buat memperkirakan kemungkinan penyakit pasien. Maka dari itu, peneliti menggunakan metode klasifikasi Naive Bayesian dan optimasi “Particle Swarm Optimization” (PSO) untuk prediksi kelahiran bayi guna mengecek prediksi status kelahiran bayi. Dari hasil prediksi itu bisa dipakai buat menetapkan rata-rata hasil kelahiran bayi setiap bulannya. Data yang kami pakai adalah jumlah ibu hamil 165. Selama pengujian digunakan perhitungan akurasi, akurasi, recall, dan AUC chart, dan model prediksi dievaluasi menggunakan 10 “fold cross-validation”. Dengan nilai akurasi 91,82% dan precission 100% serta recall 81,50% dan nilai AUC 0.90 termasuk kategori excellent classification pada model yang diujikan


Author(s):  
P S Szulczewski

This paper contains calculations of risk for a selected damage case scenario. The calculations took place with use of a risk model designed for evaluating the safety of ships and were compared with the available and published industry standard (as included in SOLAS 2009) as well. The comparison of results is presented in the form of a discussion and concludes that exact risk levels can be obtained at any stage of the vessel's life. The currently valid method as included in SOLAS 2009 regulation provides limited information about the actual survivability of a vessel in emergency conditions. It is hence very difficult to compare the current probabilistic model with risk based survivability calculations to evaluate the actual safety provided by an investigated vessel should it subsequently be severely damaged.


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jingjing Zheng ◽  
Shuhua Teng ◽  
Peirong Li ◽  
Wei Ou ◽  
Donghao Zhou ◽  
...  

With the continuous development of multimedia, more and more digital works such as videos are spread, stored, and used in the network. In recent years, digital copyright infringement disputes have occurred frequently. The traditional copyright protection system has some problems, such as difficulty confirming copyright, monitoring infringement, and obtaining evidence for rights protection. To this end, we have designed and implemented a novel video copyright protection scheme based on the blockchain and double watermarking technology. We use the image correlation coefficient method to extract video keyframes. And we combine with Contourlet Transform domain, QR decomposition, and SIFT algorithm to improve the robustness of watermark against geometric attacks on the premise of invisibility. After that, we use Arnold Transformation (Cat Map) based on the Maximum Entropy Threshold Segmentation to encrypt the robust watermark and strengthen the security. Moreover, based on the characteristics of the fragile watermarking, we accurately locate the attacked video’s tamper position and complete the integrity authentication of the watermarked video. In addition, the hash digest of the video watermark and the user ID of the copyright owner is signed by SM2 and uploaded to the blockchain. The user can register the copyright after passing the identity authentication. We conduct tests and security analysis on the blockchain performance of the system, the performance of the commercial cryptography algorithm, and the security of the watermarking system. The experimental results show that the blockchain used in this system conforms to the industry standard, the performance of SM2 and SM3 is better than ECC-256 and SHA-256, and the system security is well guaranteed.


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