A supply chain model with service level constraints and strategies under uncertainty
یک مدل زنجیره تامین با محدودیت ها و استراتژی های سطح خدمات تحت عدم قطعیت-2021
In the current socio-economic situation, the daily demand for essential goods in the business sector is always changing owing to various unavoidable reasons. As a result, choosing the right method for profitable business has become quite tricky. This study introduces different business strategies based on constant and fuzzy demands. There are two types of constraints considered in this model to avoid the backorder cost. However, combining the service-level constraints with the constant and fuzzy demand, this study compares the total costs, and finally, the best strategy is established. Moreover, investing a small amount, this model improves the quality of the products and reduces the vendor’s setup cost. Depending on the number of transported products, this model follows the transportation discount policy for hassle-free delivery of the products with a minimum delivery rate. The Kuhn-Tucker optimization technique is employed, and global optimality is verified numerically, analytically using the Hessian matrix. This model’s robustness is discussed through a comparative study, numerical examples, sensitivity analysis, graphical representation, and managerial insights. Finally, some concluding remarks along with future extensions are discussed.
KEYWORDS: Supply chain management (SCM) | Controllable lead time | Fuzzy demand | Transportation discounts | Distribution-free approach (DFA) | Service level constraints (SLC)
عکس العمل های شناختی، عاطفی و رفتاری مصرف کننده به واقعیت افزوده در تجارت الکترونیک: مطالعه تطبیقی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 17 - تعداد صفحات فایل doc فارسی: 36
این مقاله به بررسی مزیت نسبی واقعیت افزوده نسبت به ارائه محصول در وب می پردازد. مدل واکنش مصرف کننده را طراحی کرده و واکنش مصرف کنندگان به نرم افزار مکانی آی کی ایی ای و وب سایت موبایلی آی کی ایی ای در گوشی های هوشمند مقایسه می کنیم. نتایج نشان می دهد که واقعیت افزوده عملکرد بهتری نسبت به ارائه محصول در وب سایت دارد در حالی که عکس قضیه به ازای کارایی رسانه درست است. نتایج نشان می دهد ارائه محصول در وب با ایجاد لذت واکنش عاطفی (پسند محصول، لذت جویی) و شناختی (اثربخشی محصول، اعتماد انتخابی) به ویژگی واقعیت افزوده همراه است. برای دستیابی به قصد خرید بالا، آنها باید تعامل را با مشتری افزایش دهند و از محصول انتخاب شده اطمینان یابند.
کلید واژه ها: واقعیت افزوده | بازاریابی واقعیت افزوده | همخوانی واقعیت شناخته شده | سیستم واکنش مصرف کننده | تجارت الکترونیکی | نمایش محصول
|مقاله ترجمه شده|
Exponential operational laws and new aggregation operators for intuitionistic multiplicative set in multiple-attribute group decision making process
قوانین عملیاتی نمایی و اپراتورهای تجمیع جدید برای مجموعه چند برابر شهودی در فرایند تصمیم گیری گروهی چند صفت-2020
The intuitionistic multiplicative preference set is one of the replacements to the intuitionistic fuzzy preference set, where the preferences related to the object is asymmetrical distribution about 1. In it, Saaty’s 1–9 scale has been used to represent the uncertain and imprecise information. Meanwhile, an aggregation operator by using general operational laws for some fuzzy sets is an important task to aggregate the different numbers. Motivated by these primary characteristics, it is interesting to present the concept of exponential operational laws, which differs from the traditional laws by the way, in which bases are real numbers while exponents are the intuitionistic multiplicative numbers. In this paper, we develop a methodto solve the Multiple Attribute Group Decision Making (MAGDM) problem under the Intuitionistic Multiplicative Sets (IMS) environment. To do it, firstly, we define some new exponential operational laws and a score function for IMS and studied their properties. Secondly, based on this, we develop some averaging and geometric aggregation operators and characterize their various properties. Thirdly, a novel approach is promoted to solve MAGDM problems with IMS information. Finally, some numerical illustrations are given with a comparative study to verify the approach.
Keywords: Intuitionistic multiplicative sets | MAGDM | Exponential operational laws | Aggregation operators | Score function
A novel representation of time-varying viscosity with power-law and comparative study
نمایش جدیدی از ویسکوزیته متغیر با زمان با قانون قدرت و مطالعه مقایسه ای-2020
Time-varying viscosity of viscoelastic materials has been found to induce complex rheology behaviors, which cannot be well characterized by the classical viscoelastic models. In this paper, different types of time-varying viscosity, namely, linearly varying viscosity, exponentially varying viscosity, and the proposed power-law viscosity are introduced with the applications to describing experimental data. Subsequently, these time-varying viscosities are embedded into the classical viscoelastic models. The relaxation and creep responses of the modified viscoelastic models are analytically derived and compared with the performance of the corresponding fractional models. The results indicate that the proposed power-law viscosity and the exponentially varying viscosity are capable of characterizing both thixotropy and rheopexy. The modified Maxwell model with power-law viscosity agrees well with the creep and relaxation responses of time-varying materials. It is also found that viscoelastic materials exhibiting thixotropy show faster rheological responses than the materials exhibiting rheopexy.
Keywords: Time-varying viscosity | Power-law viscoelastic model | Relaxation response | Creep response
Impact of a visual decision support tool in project control: A comparative study using eye tracking
تأثیر یک ابزار پشتیبانی از تصمیم بصری در کنترل پروژه: یک مطالعه مقایسه ای با استفاده از ردیابی چشم-2020
This paper presents the results of a comparative study where two decision support tools in project control have been selected: the S-Curve and Activity Gazer. The objective of the research is to characterize the impact of the visual decision-support tool in project control on the project planners decision. Using eye tracking, a withinsubject experiment was conducted with 17 participants where they were asked to make a diagnostic on a project portfolio. Results show that, despite the fact that a representation using the S-Curve helps reduce the time of diagnostics, both tools seem to have the same effect on the quality of the diagnostic by the participant. Also, we find that a representation where Activity Gazer is present is less mentally demanding than a representation where the S-Curve is present. These results suggest that the S-Curve could be improved to reduce the mental charge needed to analyze it and that new visualization tools could help project planners in their daily work.
Keywords: Project control | Visualization | Eye tracking | Activity Gazer | Project management | Decision support
MapReduce based tipping point scheduler for parallel image processing
مانبندی نقطه اوج بر اساس MapReduce برای پردازش تصویر موازی-2020
Nowadays, Big Data image processing is very much in need due to its proven success in the field of business information system, medical science and social media. However, as the days are passing by, the computation of Big Data images is becoming more complex which ultimately results in complex resource management and higher task execution time. Researchers have been using a combination of CPU and GPU based computing to cut down the execution time, however, when it comes to scaling of compute nodes, then the combination of CPU and GPU based computing still remains a challenge due to the high commu- nication cost factor. In order to tackle this issue, the Map-Reduce framework has come out to be a viable option as its workflow optimization could be enhanced by changing its underlying job scheduling mech- anism. This paper presents a comparative study of job scheduling algorithms which could be deployed over various Big Data based image processing application and also proposes a tipping point scheduling algorithm to optimize the workflow for job execution on multiple nodes. The evaluation of the proposed scheduling algorithm is done by implementing parallel image segmentation algorithm to detect lung tu- mor for up to 3GB size of image dataset. In terms of performance comprising of task execution time and throughput, the proposed tipping point scheduler has come out to be the best scheduler followed by the Map-Reduce based Fair scheduler. The proposed tipping point scheduler is 1.14 times better than Map- Reduce based Fair scheduler and 1.33 times better than Map-Reduced based FIFO scheduler in terms of task execution time and throughput. In terms of speedup comparison between single node and multiple nodes, the proposed tipping point scheduler attained a speedup of 4.5 X for multi-node architecture.
Keywords: Job scheduler | Workflow optimization | Map-Reduce | Tipping point scheduler | Parallel image segmentation | Lung tumor
Three groups of suspects in police reported rape cases: First-time suspects, recidivists and unidentified suspects. A comparative study
سه گروه از مظنونین در پلیس موارد تجاوز جنسی را گزارش کردند: مظنونان برای اولین بار ، تکرار کننده های جرم و مظنونان ناشناس. یک مطالعه تطبیقی-2020
Background: Previous studies show that reported suspects in adult rape cases often have a criminal record, and that many are rape recidivists. Annual numbers of police reported rapes have dramatically increased but the proportion of rapes being prosecuted and numbers of convictions are low. To increase knowledge about the suspects in cases of police reported rapes; whether they have committed the crime before or not may inform preventive measures. Aims: To compare suspect, victim, and assault related characteristics among different groups of police-reported rape suspects (first-time suspects, recidivist suspects and unidentified suspects). Methods: Retrospective, descriptive study of suspects in cases of rape or attempted rape reported by women ≥16 years of age in the Sør-Trøndelag police district, Norway, from 2003 to 2010. Results: Among the 356 suspects included, 207 (58%) were first-time suspects, 75 (21%) were recidivists and 74 (21%) were unidentified. Being a first-time suspect was significantly associated with victim being <18 years, recidivist suspect was significantly associated with victim being a partner, both suspect- and victim unemployment, and suspect reporting intake of other drugs than alcohol. When suspects were unidentified, victims were more likely to have consumed alcohol prior to assault, and reporting the suspect being of non-Western origin. Also, the reporting of a public venue was more frequent when unidentified suspect. Conclusions: The study shows different patterns in groups of suspects as to victim and assault characteristics. Detection and description of such differences can provide valuable information for future prevention programs, police investigation methods and health care guidelines.
On the Effectiveness of AI-Assisted Anomaly Detection Methods in Maritime Navigation
در مورد تأثیر روشهای تشخیص ناهنجاری به کمک هوش مصنوعی در پیمایش دریایی-2020
The automatic identification system (AIS) has become an essential tool for maritime security. Nevertheless, how to effectively use the static and dynamic voyage information of the AIS data in maritime traffic situation awareness is still a challenge. This paper presents a comparative study of artificial intelligence (AI) techniques on their effectiveness in dealing with various anomalies in maritime domain using the AIS data. The AIS on-off switching (OOS) anomaly is critical in maritime security, since AIS technology is susceptible to manipulation and it can be switched on and off to hide illegal activities. Thus, we try to detect and distinguish between intentional and nonintentional AIS OOS anomalies through our AI-assisted anomaly detection framework. We use AIS data, in particular positional and navigational status of vessels, to study the effectiveness of seven AI techniques, such as artificial neural network, support vector machine, logistic regression, k-nearest neighbors, decision tree, random forest and naive Bayes, in detecting the AIS OOS anomalies. Our experimental results show that ANN and SVM are the most suitable techniques in detecting the AIS OOS anomalies with 99.9% accuracy. Interestingly, the ANN model outperforms others when trained with a balanced (i.e., same order of samples per class) dataset, and SVM, on the other hand, is suitable when training dataset is unbalanced.
In search of a free movement of forensic evidence: Towards minimum standards to determine evidence admissibility?
در جستجوی حرکت آزاد شواهد پزشکی قانونی: به سمت حداقل استانداردها برای تعیین میزان قابل قبول بودن شواهد؟-2020
In coming to a European Forensic Evidence Area, an European Union ambition to be reached by 2020, judicial cooperation in criminal matters should be levelled-up. Grounded on the legal basis provided by the Lisbon Treaty, this research identifies the minimum standards to be developed by looking into the actions taken both from a legal and from a forensic-scientific perspective to standardise the collection, storage and use of forensic expert evidence. In examining the feasibility of such standards, primary sources of legislation, policy documents and case-law on a European level are compared with a comparative study of domestic norms in six jurisdictions. Depending on the phase in the chain of custody and fundamental principle involved, but also on the level of cooperation between the forensic and legal actors, it was noticeable that the comparison led to different conclusions, depending on the refusal grounds provided by the member states and the necessity of intervention at the European level to safeguard the underlying fundamental values.
Keywords: Evidence admissibility | Judicial cooperation in criminal matters | Forensic evidence
The commons: A model for understanding collective action and entrepreneurship in communities
عوام: الگویی برای درک کنش جمعی و کارآفرینی در جوامع-2020
The creation of commons—resources that are shared, accessible, and collectively owned and managed by communities—is increasingly being adopted by social entrepreneurs as a way of contributing to community development and putting value into economic activities. Yet, little research is evident related to the entrepreneurial processes involved in the creation and commercialization of these shared resources. Drawing on the Institutional Analysis and Development framework developed by Ostrom (2005), I explain how commons are entrepreneurially created. Based on a comparative study of five community banks in Brazil, I derive two ideological principles of collective entrepreneurship that help sustain commercialization of commons without commodification, namely ‘self-organization’ and ‘right to access’. I elucidate how these principles are enacted across venture levels through downward and upward mechanisms of social control facilitated by entrepreneurs who enhance collective action. This article contributes to the entrepreneurship theory of commons by explaining how commons are entrepreneurially created and by adding the collective entrepreneurship principles and mechanisms that commons of different types need in order to achieve and sustain wealth-creation options without incurring the downsides of commodification.
Keywords: Commons | Decommodification | Community enterprise | Institutional Analysis and Development | framework | Microfinance | Brazil