Methodological Directions for the Study of Memes

The chapter proposes an empirically oriented analysis of the memetic production on Instagram. Defined as multimodal cultural artifacts, combining visual and textual material to convey humoristic messages, internet memes proliferate across the web, spawning new popular formats and layouts. However, many scholars still rely on outdated conceptualisations or limited samples for their studies. To anchor investigation on memes to the actual production, the research answers the questions: (1) Which meme formats are currently circulating online? (2) How do popular meme formats convey their message? To this end, a dataset of static images collected on Instagram was examined with qualitative visual and discourse analysis. Findings point at the possibility to adopt a bottom-up approach to recognize and classify memes, exploiting shared features of content and form. Furthermore, this categorization offers insights on the most productive mechanisms of meme production: contextually, results show a tendency towards formats that trigger identification, leveraging on relatable life situations.

Optimization of the precision gear grinding operation based on integrated information system

In accordance with the principles of hierarchical management, a comprehensive two-level management system is presented for the development and manufacturing of products for the stages of pre-production (the upper level of the management hierarchy) and for the actual production stage (the lower level of the management hierarchy). At the stage of pre-production, the gear grinding operation design on the “MAAG” type machines was carried out. For this purpose, a technique for optimizing the gear grinding parameters for a two dish-wheel rolling scheme has been developed, a mathematical optimization model containing an objective function with restrictions imposed on it has been created. The objective function is the gear grinding machine time, which depends on the operation parameters (gear grinding stock allowance, cutting modes, grinding wheel specification, part material) and the design features of the gears being ground (module, diameter, number of teeth, radius of curvature of the involutes). The article shows that at the stage of pre-production, the gear grinding optimization is a method of operation design. At the stage of actual production, a closed-loop automatic control system with feedback on the deviation of the adjustable value (gear grinding power) automatically supports the numerical power values that were found at the operation design stage, taking into account ensuring defect-free high-performance gear grinding (minimum number of working strokes and maximum longitudinal feeds). At this stage, i.e. when a robust longitudinal feed automatic control system is operating, the optimization carried out at the previous stage (pre-production) sets the functioning algorithm for the adaptive system with corresponding control algorithm. Thus, at the production stage (when the gear grinding machine is running), the operation optimization is a control method. Therefore, it is shown that with two-level control, the gear grinding operation optimization performs a dual function. On the one hand, it is a design method (at the pre-production stage), and on the other – a management method (at the actual production stage). With this approach, i.e. with the integration of production and its preparation based on a single two-level management, the efficiency of a single integrated design and production automation system is significantly higher due to general (unified) optimization, rather than partial one.

An Integrated and Automated Workflow to Enhance Production Efficiency and Compliance in a Giant Offshore Field

Daily production compliance is fundamental to sustain reservoir management excellence and ultimately achieve an optimum oil recovery. The production activities execution is critical to adhere to the reservoir management guidelines and best practices. It is a more challenging task in brownfields due to the limitation of controlling system and limited access especially in offshore fields. A timely and efficient approach is undoubtedly necessary to enhance production efficiency and compliance. An integrated and automated tool has been innovated to analyze and report well production status against the guidelines and requirements in a mature offshore field with more than 50 years history. This systematic approach has been developed through integrating the planned rate, daily actual production rate, latest flow tests, and current well performance. Noncompliance is reported automatically on a user defined time scale, including daily, weekly, monthly or any customized time range within the month time. Daily violation report is generated automatically and sent to production operation for prompt adjustments and other requested actions. The automated workflow enables both daily production reporting and production compliance reporting. Daily production reporting is a routine work, which usually takes a lot of time every day. The workflow is capable of reducing 90% of the time comparing to the manual way. Production compliance reporting is currently mainly focusing on the comparison of actual production to planned rate and guideline rate. Any exception will be reported as violation. The violation dashboard summarizes the details based on the user selected time range. On daily basis, an email containing the violation details could be generated and sent to the corresponding teams for corrective actions. In this giant brown field, production GOR is a primary controlling parameter. The latest flow tests have been taken into account to evaluate the gas production compliance. Any violation to the GOR guidelines will be reported in the same communication email for timely correction. With the innovated tool, the violation ratio of the giant offshore field has been successfully reduced and controlled. The usual responding time for corrections has been dramatically reduced from months to days.

THE PRODUCTION OF SPACE: A BALKAN PERSPECTIVE

The article describes the approach to and condenses some of the main arguments presented in the author’s book Beyond Balkansim: The Scholarly Politics of Region Making. It charts the main phases in the scholarly conceptualization of the Balkans and its characteristics and, against this background, tackles the question: What can we learn from the Balkan case about the actual production of regions?

Development of auto loading device in bearing positioning lip stamping

With the continuous development of our economy, the types and quantity of engine bearing are increasing. In order to prevent the bearing moving in the bearing pedestal, one or both ends of the bearing need to make positioning lip for axial positioning. In order to meet the needs of mass bearing production, an auto loading device for positioning lip of bearing is proposed in this paper. The horizontal conveyor belt and loading guide are used to make the blank turn to the required angle, and then the double cylinder valve and push rod motor are used to realize the time-sharing conveying and continuous loading of the blank. During the loading process, there are inclined slideway and blocking plate to avoid the collision between blanks and ensure the reliable loading bearings. Through the actual production verification, the developed device has the advantages of simple structure, low cost, fine working stability, and made great improving in the efficiency and safety for production of bearing.

Influence of Total Production on the Planting Structure of Significant Vegetable Crops in the Republic of Serbia

Summary The purpose of this paper is to examine, on the basis of the total production and distribution area parameters analyzed, a potential relationship between the actual production of major vegetable crops in Serbia in the current year and the following year’s distribution of planting areas devoted to the crops considered. The analysis was performed for the period 2005-2019. The results obtained indicate that the current year’s production of certain vegetable crops such as potatoes, cabbage, kale, peppers and beans affect the following year’s distribution of their planting areas.

Research on Stereo Library Based on Homogeneous Markov Chain

The intelligent inventory has not yet been implemented in the automated three-dimensional library. The warehouse basically relies on the accounts of the warehouse. It is really necessary to check the pallets manually with the help of a stacker, or venture into the aisle to check on the spot, or install radio frequency identification (RFID) on the pallet. The radio frequency recognition device on the stacker’s loading platform obtains the information of a specific pallet to achieve a physical inventory. After investigation, the results that can pass the three-dimensional library system automatic library are still blank. For the three-dimensional library, the intelligent inventory is of great significance to the actual production. It can automatically identify whether the goods in the designated cargo space are consistent with the storage according to the needs of the warehouse manager, so the demand for the intelligent inventory is very urgent.

Vibration characteristics analysis and structure optimization of air-pressure subsoiler

Aiming at the problems of strong vibration, inconsistent subsoiling depth and high failure rate of air-pressure subsoiler, air-pressure subsoiler vibration characteristics was studied. In order to decrease the vibration, For the first time, the vibration characteristics of air-pressure subsoiler were obtained by modal analysis and vibration test. The vibration characteristics of the whole air-blown subsoiler are analyzed Through time domain analysis, it is found that the vibration acceleration of four deep loosening shovel is inconsistent. When the diesel engine is started, it is easy to cause inconsistent subsoiler depth. Then, by analyzing the vibration characteristics of the whole air-pressure subsoiler, it can be known that the external excitation source of the air-blown subsoiler is close to its own natural frequency. In order to avoid resonance caused by the vibration frequency of the external excitation source being close to the natural frequency of the air-pressure subsoiler, and to reduce the inconsistency of the subsoil depth, we optimize the design of air-pressure subsoiler. Instead of diesel engines, the steering gear box is connected with tractor power output shaft to provide power. The modal simulation of the optimized air-pressure subsoiler shows that the first-order natural frequency is obviously improved and the external excitation frequency is successfully avoided. It not only avoids resonance, reduces the damage of resonance components, but improves the service life of the subsoiler, greatly improves the structural reliability of the air-pressure subsoiler, at the same time, removes the main external excitation source, which greatly reduces the vibration in actual production and the inconsistency of subsoiling, which is of great significance in actual production. It provides a reference for the research of vibration characteristics, resonance avoidance and structure optimization of agricultural equipment.

Drifting pitch awareness after exposure to altered auditory feedback

Various studies have claimed that the sense of agency is based on a comparison between an internal estimate of an action’s outcome and sensory feedback. With respect to speech, this presumes that speakers have a stable pre-articulatory representation of their own speech. However, recent research suggests that the sense of agency is flexible and thus in some contexts we may feel like we produced speech that was not actually produced by us. The current study tested whether the estimated pitch of one’s articulation (termed ‘pitch awareness’) is affected by manipulated auditory feedback. In four experiments, fifty-six participants produced isolated vowels while being exposed to pitch-shifted auditory feedback. After every vocalization, participants indicated whether they thought the feedback was higher or lower than their actual production. After exposure to a block of high-pitched auditory feedback (+500 cents pitch shift), participants were more likely to label subsequent auditory feedback as “lower than my actual production”, suggesting that prolonged exposure to high-pitched auditory feedback led to a drift in participants’ pitch awareness. The opposite pattern was found after exposure to a constant -500 cents pitch shift. This suggests that pitch awareness is not solely based on a pre-articulatory representation of intended speech or on a sensory prediction, but also on sensory feedback. We propose that this drift in pitch awareness could be indicative of a sense of agency over the pitch-shifted auditory feedback in the exposure block. If so, this suggests that the sense of agency over vocal output is flexible.

Fault Diagnosis of Intelligent Production Line Based on Digital Twin and Improved Random Forest

Digital twin (DT) is a key technology for realizing the interconnection and intelligent operation of the physical world and the world of information and provides a new paradigm for fault diagnosis. Traditional machine learning algorithms require a balanced dataset. Training and testing sets must have the same distribution. Training a good generalization model is difficult in an actual production line operation process. Fault diagnosis technology based on the digital twin uses its ultrarealistic, multisystem, and high-precision characteristics to simulate fault data that are difficult to obtain in an actual production line to train a reliable fault diagnosis model. In this article, we first propose an improved random forest (IRF) algorithm, which reselects decision trees with high accuracy and large differences through hierarchical clustering and gives them weights. Digital twin technology is used to simulate a large number of balanced datasets to train the model, and the trained model can be transferred to a physical production line through transfer learning for fault diagnosis. Finally, the feasibility of our proposed algorithm is verified through a case study of an automobile rear axle assembly line, for which the accuracy of the proposed algorithm reaches 97.8%. The traditional machine learning plus digital twin fault diagnosis method proposed in this paper involves some generalization, and thus has practical value when extended to other fields.