Greater Price Research Articles

Kripto Para Merkezli Kara Para Aklama Senaryolarının Adli Bilişim Açısından İncelenmesi

One of the biggest innovations brought by the digitalized world is undoubtedly the invention of crypto money, which is decentralized, anonymous and complex, and connected to blockchain technology. This relatively new technology has attracted the attention of many people with its revolutionary changes in payment systems and great price movements in the market, as well as the economic balances it has changed around the world. In addition to this interest, it also attracted the attention of crime and crime organizations in a short time, and over time it turned into a tool used by illegal organizations such as laundering the proceeds of crime. Although this structure was initially exposed to the reaction of some states at the level of nation states, on the other hand, it managed to get the support of many states. However, although the spread of blockchain-based money laundering methods is an undeniable problem for all states, a significant cooperation has not been achieved by international collaborations and organizations to prevent this situation. On the other hand, it is of great importance for law enforcement and forensic analysts to clarify this situation and to fight against these structures in order to protect national interests. In this study; In this study, an approach that will detect money laundering is tried to be presented through sample scenarios by bringing a broad perspective to crypto money-based money laundering methods, which are very difficult to trace due to their nature. In addition, it is expected that the difficulties in implementation of the proposed approach will be clearly addressed and will shed light and inspire further study.

The Law of the Gospel: Shifting Interpretations of a Temple Covenant throughout Latter-day Saint History

The Law of the Gospel: Shifting Interpretations of a Temple Covenant throughout Latter-day Saint History

Multi-objective optimization of IoT-based green building energy system using binary metaheuristic algorithms

Green building energy optimization systems (GBEOS) are of great interest to academics and industry professionals. One of the main challenges of GBEOS is optimizing energy consumption while maintaining people's comfort level. This paper proposes a metaheuristic-based GBEOS for optimizing energy consumption within a smart green building operating under a smart grid paradigm while considering the local environment and energy demand behaviors. In this regard, two complementary control procedures are developed: the supply-part optimizer (SPO) and the demand-part optimizer (DPO). By combining SPO and DPO, six binary multi-objective optimization algorithms, including Xtreme gradient boosting (XGBoost), multiverse optimizer (MVO), moth flame optimization (MFO), shuffled frog leaping algorithm (SFLA), moth flame optimization, imperialist competitive algorithm (ICA), and chimp optimization algorithm (ChOA) are developed to simultaneously minimizes costs and maximizes client comfort satisfaction (CS). First of all, considering the importance of convergence speed, seven unimodal, six multimodal, and twenty complex benchmark optimization functions are used to evaluate the proposed approach's convergence behavior. Afterward, an efficient weighting mechanism is used to handle the cost-comfort trade-off, allowing the user to discover a reasonable trade-off between monetary expense and comfort level. Then, in order to determine the influence of the pricing scheme's nature on the potential savings achieved through EMS, three individual models named real-time pricing (RTP), time-of-utilize pricing (TUP), and fixed-pricing plan (FPP) are proposed. The results show that ChOA presents the best result in terms of convergence, with 19 out of 33 test functions; also, XGBoost has the second-best performance. In addition, results show that suggested metaheuristic algorithms significantly increase PV energy penetration for self-consumption and lower power costs while keeping an optimal balance between CS and economical costs. Moreover, using dynamic pricing systems, i.e., RTP or TUP, results in great user price savings than FPP. To sum up, ChOA is found to be the best algorithm in this challenge, followed by XGBoost in second place.

A perspective on physical reservoir computing with nanomagnetic devices

Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this success comes at a great price; the energy requirements for training advanced models are unsustainable. One promising way to address this pressing issue is by developing low-energy neuromorphic hardware that directly supports the algorithm's requirements. The intrinsic non-volatility, non-linearity, and memory of spintronic devices make them appealing candidates for neuromorphic devices. Here, we focus on the reservoir computing paradigm, a recurrent network with a simple training algorithm suitable for computation with spintronic devices since they can provide the properties of non-linearity and memory. We review technologies and methods for developing neuromorphic spintronic devices and conclude with critical open issues to address before such devices become widely used.

Deep Reinforcement Learning-Based Dynamic Pricing for Parking Solutions

The growth in the number of automobiles in metropolitan areas has drawn attention to the need for more efficient carpark control in public spaces such as healthcare, retail stores, and office blocks. In this research, dynamic pricing is integrated with real-time parking data to optimise parking utilisation and reduce traffic jams. Dynamic pricing is the practice of changing the price of a product or service in response to market trends. This approach has the potential to manage car traffic in the parking space during peak and off-peak hours. The dynamic pricing method can set the parking fee at a greater price during peak hours and a lower rate during off-peak times. A method called deep reinforcement learning-based dynamic pricing (DRL-DP) is proposed in this paper. Dynamic pricing is separated into episodes and shifted back and forth on an hourly basis. Parking utilisation rates and profits are viewed as incentives for pricing control. The simulation output illustrates that the proposed solution is credible and effective under circumstances where the parking market around the parking area is competitive among each parking provider.

Numerical Evaluations for Robotic Turning with a Scheduled Modulatory Gain-Based Chatter Controller

During the turning production process, a material is cut by using a specified material removal strategy in order to produce the desired final form and dimension. Tool chatter is a widespread undesired dynamic instability that arises during fundamental machining processes such as milling, drilling, and turning. The dynamic interaction of the components of the cutter tool and the surface of the material being cut is just one of the numerous process variables that can result in chatter vibrations. Usually, the vigorous turning that quickly releases the metal chip causes the cutter to oscillate excessively with respect to the workpiece. Tool chatter can result in excessive wear, a shorter tool life, poor surface quality, and misaligned geometry. Due to the poor quality of the surface finish, this can consequently result in greater prices, postponed deliveries, and even lost orders. The ability of a gain modulation-based control strategy to improve the product finish in robotic turning has been examined in this investigation along with a number of other process parameters. A two-link manipulator dynamical model has been used and numerical outcomes are presented for the efficacy of the control toward achieving an improved product surface finish.

Joseph Fielding Smith's Evolving Views on Race: The Odyssey of a Mormon Apostle-President

Joseph Fielding Smith's Evolving Views on Race: The Odyssey of a Mormon Apostle-President

Corporate culture: The interview evidence

Corporate culture: The interview evidence

The Old Toponymy and New Topography of Zion: Utah, Photography, and Daniel George's Series God to Go West

The Old Toponymy and New Topography of Zion: Utah, Photography, and Daniel George's Series <i>God to Go West</i>

Index Design: Hedging and Manipulation

This paper studies optimal index design to facilitate both hedging and alleviate illegal manipulation in a competitive equilibrium paradigm, modified to deal with manipulation. Specifically, a large trader is trading both derivatives and assets that effectively hides her trades behind the competitive market clearing mechanism. Unlike the strategic game paradigm, a volume-weighted average pricing (VWAP) index introduces basis risk and encourages manipulation because of the additional randomness in volume weight and the greater price impact enjoyed by the large trader. In contrast, an equal-weighted average pricing (EWAP) index preserves market completeness and discourages manipulation.

The Factors Influencing Consumer Buying Decision of Electronic Products

Consumer behaviour study is an effort to understand the buying tendencies of buyers for their end use. Consumer buying decisions direct how healthy the company's selling policy fits market demand. The persistent invention in electronic products accompanied by great price war followed by various opponent products available in every market, has commanded sellers to focus on the consumers' buying behaviour. This study examines the effect of influencing determinants on consumer buying decision of electronic products amongst different socio-demographic profiles. The comprehensive analysis indicates that social and personal factors are strongly associated with the consumer buying decision of consumers which supports our previous study on similar ground and situational determinant is the new which play almost parallel role. The result also helps manufacturers and dealers in understanding consumer buying behaviour and assist in improvement on buyer gratification. It was recommended that sellers should take cognizance of the fact that socio-personal factors are the fundamental determinants of buyers' want and behavior and should therefore be considered when producing electrical products for semi-urban markets.

Multiperiod Portfolio of Energy Purchasing Strategies including Climate Scenarios

Because electricity retailers must ensure that energy supply matches end-user demand, electricity that is not traded through bilateral contracts is typically traded in power exchanges which are subject to great price volatility. In Colombia, the spot price is a reflection of climate variability because approximately 70% of the country’s electricity is generated by large hydropower stations. In this study, we forecast 2018′s prices and calculated its corresponding purchase margins using the 2015 to 2017 bilateral contract prices for electricity plus power exchange price information and climate information. Our forecasts included climate uncertainty and evaluated two multi-period portfolio methods for deciding among three purchasing strategies: bilateral contracts in the regulated market, bilateral contracts in the non-regulated markets, and purchases in the power exchange. The results indicate that retailers should follow a middle course that is neither conservative nor risky. Creation of portfolios independent of the multi-period method can balance purchases through bilateral contracts and in the power exchange in a way that considers climatic uncertainty. This type of balanced portfolio could control medium-term risks of price volatility and result in good levels of purchase margins.

Internet Retailing and Pricing Decisions: An Examination in the Italian Gambling Market

The rapid growth of e-commerce over the last few years has sparked a stream of research that analyzed the impact of Internet retailing on market prices. It has been theorized that the low entry and transaction costs associated with electronic commerce should lead to a reduction in prices, especially for homogeneous products. Some scholars have verified, through empirical research, whether the prices of specific products and services sold through the electronic distribution channel are, as hypothesized, lower than those practiced in brick and mortar stores. The results of this research, even if they mostly confirm the greater price efficiency of e-commerce compared to the physical sales network, are however not univocal. This paper intends to offer an original contribution in this field of study, examining a particular industry that in recent years has been affected by an exponential increase in online sales, that of gambling. The aim of this work is to analyze whether in the Italian sports betting market, in line with theoretical hypotheses, online prices are lower than offline prices and whether the development of Internet sales has been accompanied by greater market efficiency and, therefore, a generalized reduction in prices. From a methodological point of view, the study was developed by collecting and processing the official market data of the regulated sports betting sector in Italy provided by the Agency of Customs and Monopoly, for the years ranging from 2011 to 2019, thus carrying out a longitudinal analysis on price levels and related changes over time. The results of the analysis have shown that in the period analyzed in the Italian regulated sports betting market the average prices paid for the betting products offered by the gambling websites remained lower, in a range going from 38 to 48 percent, as compared to those practiced by betting shops. It also emerged that there was a general reduction in the average price levels of betting products equal to almost 50 percent. These results have interesting managerial implications for gambling operators and provide some indications for state institutions that are responsible for gambling policy and legislative changes.

Why do firms purchase directors' and officers' liability insurance? – perspective from economic policy uncertainty

PurposeThis study aims to investigate whether firms purchase directors' and officers' liability (D&amp;O) insurance when the country-level economic policy uncertainty (EPU) is high.Design/methodology/approachThis study uses D&amp;O insurance data from Chinese listed firms between 2003 and 2019 to conduct regression analyses to examine the association between D&amp;O insurance and EPU.FindingsThe results show that government EPU, despite being an exogenous factor, increases the likelihood of firms' purchasing D&amp;O insurance, and this effect is more pronounced when firms are exposed to great share price crash risk and high litigation risk, suggesting that firms intend to purchase D&amp;O insurance possibly due to the accentuated stock price crash risk and litigation risk associated with EPU. In addition, the results indicate that the effect of EPU on the D&amp;O insurance purchase decision is moderated by the provincial capital market development and internal control quality.Practical implicationsThe study highlights the role of uncertain economic policies in shareholder approval of D&amp;O insurance purchases.Originality/valueThe study enriches the literature on the determinants of D&amp;O insurance purchases by documenting novel evidence that country-level EPU is a key institutional factor shaping firms' decisions to purchase D&amp;O insurance.

Lady Clara Cavendish: Reynolds and Rymer’s Political Hoax

In 1858, G. W. M. Reynolds’s (1814–79) popular penny periodical Reynolds’s Miscellany introduced a new ‘authoress’, Lady Clara Cavendish. Reynolds bragged that Cavendish’s novels would reveal Hanoverian court corruption—for a great price, which he happily paid. However, as some Victorian critics speculated, Cavendish was herself a fiction. She and her novels are in fact the inventions of Reynolds and his regular employee James Malcolm Rymer (1814–84), who in the 1840s created ‘Sweeney Todd’ and ‘Varney, the Vampire’ for the penny blood publisher Edward Lloyd. This essay contends that Reynolds and Rymer’s Cavendish is not a random collection of pieces united merely by a byline. Instead, Cavendish’s supposed productions combine with paratextual material such as Reynolds’s advertising to articulate a consistent personality. Reading the Cavendish phenomenon as a holistic literary corpus reveals that in creating it, Reynolds and Rymer advance a didactic and political mission. In keeping with their involvement in Chartism, the Cavendish hoax enlists the rhetoric of ‘Old Corruption’ to support Chartist ideals, especially the political awakening of the ‘industrious millions’. By presenting Cavendish as an aristocrat and court insider, Reynolds and Rymer invest their political critique with authority they could not otherwise have achieved. For Reynolds and Rymer, therefore, the hoax did not constitute a departure or escapist fantasy, but a potentially more persuasive affirmation of the ideological commitments that they shared. Reading it today throws into bold relief those shared perspectives, which critics are only beginning to recover and re-appraise.

Does type of robotic platform make a difference in the final cost of robotic-assisted radical prostatectomy?

This study evaluates the difference of robot-assisted radical prostatectomy (RARP) costs in patients with similar preoperative characteristics operated on using the da Vinci® SP and Xi robotic platforms. We performed a retrospective analysis on 71 consecutive patients with prostate cancer who underwent RARP with the SP robot between June 2019 and April 2020. Propensity score (PS) matching was performed and 71 patients were selected from a cohort of 875 who underwent RARP with the Xi robot in the same period. We divided the total expense per surgery into the cost of disposable materials, robotic instruments (initial purchasing cost divided by the number of "lives"), and operative room costs. Only variable costs are included in this study, as fixed costs do not vary between procedures and are the same for both cohorts. Fixed costs include anesthesia, pathology, surgeon, and hospitalization fees. The median total cost for SP-RARP was $5586 ($5360-$5982) USD and $4875 ($4661-$5093) USDwith the XI for a median cost difference of $707 ($584-$832) (P < 0.001). The median cost of disposables for the SP was $1877 ($1588-$2193) USD and for the Xi $1527 ($1407-$1781) USD,P < 0.001. Non-disposable instruments cost per case (fixed cost) was $1610 and $1270 USD for the SP and Xi, respectively. The cost of radical prostatectomy in the SP cohort is higher than the Xi cohort. The greater price was primarily due to the increased cost of instruments and disposable materials. In our experience, the lack of GelPOINT and space maker is also crucial factors to decrease the SP total cost.

An Analysis Framework to Study the Effects of Green Finance on Sustainable Smart Cities

Despite the fact that many countries around the world have adopted green growth as their strategy for economic development and those studies have investigated the factors that influence green growth from a variety of perspectives in sustainable smart cities, there is a paucity of literature that focuses on the impact that fintech and green finance have on green growth. This study attempts to design a complete index to assess the green growth of regional economies from the point of view of the development of fintech. The index will be based on an in-depth examination of the effect mechanism that green finance has on green growth. Additional study reveals that innovations in fintech mostly foster green economic development by means of green lending and green investment. As a result, advancements in fintech have the potential to foster green productivity expansion by elevating the development degree of green finance. This is a field that has a great deal of reference importance for most nations. The development of financial technology has the opposite effect on the building of sustainable smart cities. This is mostly because both the development and commoditization of fintech need more resources, and these resources also come at a greater price.

Analysis on shadow price and abatement potential of carbon dioxide in China's provincial industrial sectors.

CO2 emission performance evaluation is crucial to make abatement policies. Knowledge about the potential and costs of CO2 reduction could provide information guides for policymakers and help them implement targeted measures. However, relevant studies are rarely subdivided into detailed industrial sectors, and results are lack of inter-industry comparisons. To fill this gap, this study estimates provincial technical inefficiency, abatement potential, and shadow price of CO2 from fuel combustion in China's 25 industries in 2001-2017. Results show that China's industry could ideally reduce CO2 emissions by a further 22.01-33.27%, averaging 1645.96 MtCO2. Technical efficiency, abatement potential, and cost vary across provinces and industries and should therefore be fully considered when designing emission reduction targets and control policies. Provinces and industries with low technical efficiency, large-scale emissions, great abatement potential and low shadow price are the key to emission reduction. We thus identify key provinces and industries that need to take on more abatement responsibility. Those findings are of great significance to the formulation of carbon reduction targets and the implementation of abatement policies, and prove the feasibility of China's trans-regional carbon trading. It is suggested to prioritize key industries into the trading system and further promote inter-provincial cooperation through carbon trading.

Causes and effects of inflation in Poland

&#x0D; In the paper it is discussed the causes and effects of inflation in Poland. The paper analyzes inflation in recent years, including changes caused by the outbreak of the COVID-19 pandemic. Undoubtedly, the spread of the coronavirus has contributed to the changes in the economy. Inflation is one of the main macroeconomic indicators that reflect the economic situation of a certain country. It occurs when the prices of goods and services in the market increase, so each subsequent year you can buy less for the same amount. Inflation occurs when the price increase is constant and persists over a specific period of time, then the purchasing power decreases (M. Gamrot, 2014). It is not a rule that the overall price index is influenced most by the products that have the greatest price appreciation. The pass-through to the inflation rate also depends on the share of a product's "weight" in conventional household consumption expenditures. CPI inflation in 2021 in Poland is influenced, to the greatest extent, by energy prices causing food prices increase and core economic inflation. The factors forming inflation, are the so-called, inflation expectations significantly influencing consumption or investment decisions. Measures taken in the economic policy, such as a significant loosening of monetary or fiscal policy contributed to the mitigation of the effects of COVID-19.

Integrated Approach to Clean and Green Environment Estimation

Abstract: This paper delineates a prototype for assessing, viewing, and estimating some environmental constraints such as temperature, humidity, toxic gas levels in intensely contaminated regions, and collection of garbage in the surrounding areas. This system was developed using the Arduino Uno microcontroller and various sensors namely DHT11, MQ-135, HC-SR04 Ultrasonic, it is a device of great scalability levels, price effectiveness and suitable for other environmental monitoring applications. Environmental air parameters directly have an effect on the current entity, and will amend from regularity or maybe every single second in a while, with a speedy manufacture beyond several decades earlier and dramatic increase of demand for individuals to observe the native air quality. The atmosphere is a tumultuous system, air quality is predisposed by several aspects and may vary hastily. Air constraints and quality directly have an effect on human’s normal lives, and also wellbeing of outside tasks. At present times, technologies are getting smarter day-by-day, as to clean the environment waste management system was developed by using Arduino. This Ultrasonic sensor is integrated to the microcontroller and is positioned on the top of the dustbin. If dustbin is not upheld then this can cause an insalubrious environment and further affects the people living in close proximities this article comprises comprehensive illustration of the system architecture, hardware and software requirements. The practicality of the system is validated through the publication of the outcomes achieved. Keywords: DHT11 sensor, MQ-135 sensor, HC-SR04 Ultrasonic sensor, Arduino UNO, Jumper wires.