Process In Order Research Articles

QPJVis Demo: Quality-Boost Progressive Join Query Processing System

Progressive query processing enables data scientists to efficiently analyze and explore large datasets. Data scientists can start further analyses earlier if the progressive result can represent the complete results well. Most progressive processing frameworks carefully control which parts of the input to process in order to improve the quality of progressive results. The input control strategies work well when the data are processed uniformly. However, the progressive results will be biased towards the join keys if the processed data are not uniform. A recently proposed input&output framework named QPJ corrects the bias by temporarily hiding some results. The framework dynamically estimates the distribution of the complete result and outputs progressive results with a similar distribution to the estimated complete result. This demo presents QPJVis, which is a progressive query processing system designed to inherently process the progressive queries using the QPJ framework. Additionally, we also implement an input control framework, Prism, in QPJVis so that users can compare the difference between the input&output framework and a purely input framework.

Проблемы привлечения адвокатом-защитником специалиста в уголовном судопроизводстве

The article studies the problems of attracting a specialist defense lawyer in criminal proceedings. The author examines the main reasons for the opposition of government entities to the right of the defense to present a specialist’s report, which contains a revision of the expert’s report. The legal positions of the European Court of Human Rights, as well as the Constitutional Court of the Russian Federation on issues of expert evidence are noted. In addition, the researcher turns to practical examples of both negative rejection of a specialist’s conclusion as unacceptable criminal procedural evidence, and the positive practice of perceiving a specialist’s conclusion as a basis for ordering a repeat forensic examination and even termination of a criminal case. Ultimately, the author concluded that it is necessary to reform the domestic criminal process in order to increase the efficiency of attracting a specialist defense lawyer as a means of countering criminal prosecution.

Readiness for sustainable accreditation management in higher education institutions: A mixed-method study in Indonesia

Obtaining an excellent accreditation rank in various study programs has become an urgency for universities in Indonesia because accreditation rankings are believed to have an impact on the provision of quality education. However, not all universities are able to achieve an excellent accreditation rank for all of the study programs they manage. This research aims to determine the readiness of the accreditation teams in managing accreditation in various study programs. The mixed method is used, with an explanatory sequential design. The participants involved are university leaders and accreditation teams in various study programs. The research results showed that an excellent accreditation rating cannot be achieved with ordinary organizational behavior but requires great effort, care, and commitment from both the leaders and the accreditation team. It also requires active and comprehensive participation from the academic community. The excellent rank in accreditation can only be obtained with superior effort and care. It is suggested that the readiness of the leaders and accreditation teams to manage accreditation optimally is a crucial aspect in achieving an excellent rating. In conclusion, there are at least three important aspects to consider in the accreditation process in order to achieve an excellent rank: the need to achieve the highest assessment, the effort and care needed to significantly impact the highest assessment, and the institution needs to ensure a quality culture through quality assurance and the International Organization for Standardization (ISO).

Revue systématique des méthodes d’évaluation du traitement sensoriel chez les enfants et adolescents autistes

Sensory processing has been a diagnostic criterion for autism spectrum condition since the fifth version of the DSM. However, there is no consensus regarding assessment methods. This article is a systematic review of methods for assessing sensory processing in children and adolescents with autism aged between 0 and 18 years, with three objectives: (1) to identify and organize, using PRISMA, the different methods used in scientific articles for assessing sensory processing in autism; (2) to discuss their advantages and limitations by using the COSMIN checklist; (3) to suggest possible recommendations. Analysis of the 142 articles selected revealed five types of assessment method: questionnaires, psychophysical measurements, electroencephalography, neuroimaging and observation. Questionnaires were the most frequently cited clinical method, while psychophysical tests were the most represented. Each method has limitations in terms of individual utilization due to non-standardized procedures and varied investigation targets. While this systematic review makes it possible to better identify the methods used in the clinical and research fields for sensory processing specificities in children and adolescents on the spectrum, it also highlights the fact that the lack of consensus on assessments is partly due to a problem of definition of this process. Future research will need to agree on a characterization of sensory processing in order to develop a common assessment.

Application of Software Robots and Deep Learning in Real time Processing of E-commerce Orders

Application of Software Robots and Deep Learning in Real time Processing of E-commerce Orders

An unbounded intensity model for point processes

We develop a model for point processes on the real line, where the intensity can be locally unbounded without inducing an explosion. In contrast to an orderly point process, for which the probability of observing more than one event over a short time interval is negligible, the bursting intensity causes an extreme clustering of events around the singularity. We propose a nonparametric approach to detect such bursts in the intensity. It relies on a heavy traffic condition, which admits inference for point processes over a finite time interval. With Monte Carlo evidence, we show that our testing procedure exhibits size control under the null, whereas it has high rejection rates under the alternative. We implement our approach on high-frequency data for the EUR/USD spot exchange rate, where the test statistic captures abnormal surges in trading activity. We detect a nontrivial amount of intensity bursts in these data and describe their basic properties. Trading activity during an intensity burst is positively related to volatility, illiquidity, and the probability of observing a drift burst. The latter effect is reinforced if the order flow is imbalanced or the price elasticity of the limit order book is large.

Tunisian Doctoral Students between Course Management and Effective Performance

Different teaching models have been used to enhance the teaching and learning process in order to meet the required achievements. This process keeps on changing for decades, particularly with the inclusion of the communicative approach. In this respect, a mooting point concerns how the interactive process of teachers and learners take place for designing course materials. Another vital point to consider is how to evaluate the achievements of a set of pedagogical packages offered for novice teachers in particular, which are merely a part of their constitutive formation and course management. These investigative points are conducted by loading the Tunisian doctoral students with the most effective pedagogical means so that they acquire the desired procedures for course planning and class management. These students are required to teach their classmates, pretending to be learners, within a micro-teaching context. The presupposed teachers are equipped with the necessary teaching means. The experiment consists in a scientific class session followed by a class discussion describing and assessing the presented courses performance. This pursued process represents a pedagogical mechanism for designing a yardstick for mapping out an assessing measure of the courses. It is found that the doctoral students use different cognitive techniques to manage their classes by assigning tasks with different levels of complexities. Finally, it is suggested that the presented courses leave traces of achievements. The doctoral students are able to diversify their pedagogical techniques during class management. What remain at issue are the pedagogical anomalies to avoid for a better teaching performance.

Development of IoT Kaizen System for Smart Lean Raw Material Inventory Management: A case study at an SME factory in Malaysia

Effective Raw Material Inventory Management is crucial for overall company performance, demanding significant improvements. In the current technologically advanced landscape, the imperative adoption of the Internet of Things (IoT) is crucial for propelling inventory management forward and amplifying the visibility of raw materials. This case study is dedicated to developing an IoT Kaizen System, meticulously aligned with the Smart Lean Factory Inventory Control Framework, tailored to enhance Raw Material Inventory Management within an SME factory in Seremban, Negeri Sembilan. With a focal point on Loft Layer materials, the study encompasses Raw Material Ordering, Receiving, and Charging Out Log operations. Leveraging web-based tools such as Google Sheets, AppSheet, and Looker Studio, the system adeptly digitizes manual processes, tracking real-time data and integrating data visualization tools for informed decision-making. Implemented within a genuine industrial context, the project is intricately tailored to meet the unique preferences and requirements of the company, ensuring a customized solution that aligns with industry standards and reflects specific operational nuances. The resulting digital system introduces a structured, simplified, and efficient approach to Raw Material Inventory Management, injecting enhanced operational control and adaptability into the company’s workflow. Through the system implementation, warehouse space was reduced by 15%, order processing was done fully digitally that achieve zero case of ordering error and achieved zero case of material stock out. This system can adjust to what’s needed in modern manufacturing. It proves that using innovation and technology can make a business better by making things run more smoothly and helping with decision-making.

AI-enhanced inventory and demand forecasting: Using AI to optimize inventory management and predict customer demand

The advent of artificial intelligence (AI) has ushered in a new era of efficiency and accuracy across various industries, with inventory management and demand forecasting being at the forefront of these advancements. Traditional inventory management techniques, often reliant on historical data and simple statistical models, fall short in addressing the dynamic and complex nature of contemporary markets (Chopra & Meindl, 2016). AI, with its advanced algorithms and machine learning capabilities, offers a transformative approach to these critical business functions. This paper explores the integration of AI technologies in optimizing inventory management and predicting customer demand. AI-enhanced inventory management involves the application of various AI technologies such as machine learning, natural language processing (NLP), computer vision, and robotics process automation (RPA) (Ivanov et al., 2017). Machine learning algorithms analyze vast amounts of historical data to identify patterns and trends, enabling more accurate predictions and adjustments in inventory levels. NLP processes unstructured data from sources like social media and customer reviews to provide deeper insights into market trends and customer preferences (Cambria & White, 2014). Computer vision technologies assist in real-time monitoring of inventory levels and identifying discrepancies through visual data, while RPA automates repetitive tasks like order processing and inventory tracking, thereby reducing human error and increasing efficiency (Aguirre & Rodriguez, 2017). This paper highlights significant improvements in forecast accuracy and inventory turnover rates achieved through AI implementation and discusses future implications for supply chain management.

The situation of "double protection" and its impact on evidence in criminal proceedings: appearance analysis and recommendations to lawyers

Relevance. A lawyer, not being a subject of proof in criminal proceedings, nevertheless, is an active participant in the proof process, which he carries out throughout his activities to protect his client from suspicion or formed and put forward an accusatory thesis. At the same time, the current situation of "double protection" significantly hinders the participation of a lawyer in proving innocence or lesser guilt in comparison with the accusatory thesis put forward, and at the same time establishes an obstacle to the implementation of the provisions enshrined in Article 48 of the Constitution of the Russian Federation, which enshrines the right of everyone to receive qualified legal assistance. The situation of "double protection" is one of the most negative factors in advocacy. In order to avoid the occurrence of a "double protection" situation, the author proposes an algorithm of actions when entering the process as a defender.Objective: to develop an algorithm for entering the process in order to avoid a situation of "double protection".The purpose of the study is to continue the research of advocacy in criminal proceedings, refuting the arguments of the prosecution and proving the innocence or lesser guilt of the defendant.Methodology. The methodological basis of the research was the universal dialectical method of cognition of socio-legal phenomena, general scientific research methods (analysis and synthesis, deduction and induction, system-structural and others). In addition, private scientific methods of cognition were used logical-formal and system analysis.The results of the study are both theoretical and applied in nature, and have elements of scientific novelty. The author considers the issues of the lawyer's entry into the criminal process by appointment, proposes an algorithm for the lawyer's actions in order to avoid possible violations and the emergence of a situation of "double protection".Conclusions. The discussion of the identified problems will allow us to develop solutions to eliminate the identified gaps in the implementation of protection in criminal proceedings, protect lawyers from possible violations of internal corporate regulations.

Hydrogen-Bonded Fibrous Nanotubes Assembled from Trigonal Prismatic Building Blocks.

In reticular chemistry, molecular building blocks are designed to create crystalline open frameworks. A key principle of reticular chemistry is that the most symmetrical networks are the likely outcomes of reactions, particularly when highly symmetrical building blocks are involved. The strategy of synthesizing low-dimensional networks aims to reduce explicitly the symmetry of the molecular building blocks. Here we report the spontaneous formation of hydrogen-bonded fibrous structures from trigonal prismatic building blocks, which were designed to form three-dimensional crystalline networks on account of their highly symmetrical structures. Utilizing different microscopic and spectroscopic techniques, we identify the structures at the early stages of the assembly process in order to and understand the growth mechanism. The symmetrical molecular building blocks are incorporated preferentially in the longitudinal direction, giving rise to anisotropic hydrogen-bonded porous organic nanotubes. Entropy-driven anisotropic growth provides micrometer-scale unidirectional nanotubes with high porosity. By combining experimental evidence and theoretical modeling, we have obtained a deep understanding of the nucleation and growth processes. Our findings offer fundamental insight into the molecular design of tubular structures. The nanotubes evolve further in the transverse directions to provide extended higher-order fibrous structures [nano- and microfibers], ultimately leading to large-scale interconnected hydrogen-bonded fiber-like structures with twists and turns. Our work provides fundamental understanding and paves the way for innovative molecular designs in low-dimensional networks.

Polyester Composite and Waste of Natural Materials Recyclable: Fracture Aspect After Tensile Test

Objective: This study aims to analyze the fractography of polymeric composites reinforced by recyclable materials, verifying the main types of defects present in the manufactured materials. Theoretical Framework: Composites can be understood as mutltiphasic materials that present a significant portion of the properties of their constintuintes. There are two phases, matrz and reinforcement. From the fractofrgographic analysis of the fracture surface of the material, one can evaluate the mechanisms of failure and interaction between the interfaces of the phases. Method: Specimens were manufactured using silicone molds according to ASTM D638. The matrix was unsaturated and pre-accelerated terephthalic polyester resin, while the reinforcement materials were: Jatoba wood residues, the hybridization of Jute and Sisal fibers, the hybrid of sisal and coffee grounds, and açaí leaves. Results and Discussion: For the composite with reinforcement of wood waste, there was a predominance of voids. For hybrids, the presence of the fibers culminated in the pull-out defect, therefore, using sisal fibers and coffee grounds, the presence of voids was also observed. The composite with acai leaves presented delamination between the reinforcement layers and the matrix. Research Implications: The analysis of the predominant defects, evaluates the possibility of improvement of the manufacturing process in order to certify the presence of this and promote and improve the efficiency of handling the material. Originality/Value: The use of natural and recyclable materials is of great importance from a sustainable analysis. In addition, it aims to generate added value to raw materials with little or no functionality.

Son et lumière in Proust

ABSTRACT Marcel Proust’s À la recherche du temps perdu is underpinned by an enduring tension between sight and the other senses. Conventional scholarship on Proust claims that the visual pole of this tension is linked to the intellect, as opposed to the association of the remaining senses with intuition and the unfathomable. This reading, however, presents an oversimplification of the complex economy of the senses explored by Proust insofar as it falls prey to visualism, a theoretical predisposition characterised by a double reduction of the perceptual experience. Challenging this tendency, this article draws on sensorial cross-modality and multisensory processes in order to interrogate the connection between sunlight and song in Proust’s novel. In particular, we focus on the ‘little barometer man’ at the start of La Prisonnière, whom the narrator anticipates singing on his death bed ‘if there is a blink of sun’. We also consider this Proustian connection between song and sunlight in light of a longer tradition, including St Francis of Assisi’s ‘Canticle of Brother Sun’ and the statue of Memnon’s dawn song. Proust’s consequent demythologising of light and his materialist approach to song support an attempt to consider light shorn of its usual metaphorical connotations.

Transcriptomic Hallmarks of Hypoxic-Ischemic Brain Injury: Insights from an in Vitro Model.

Hypoxic-ischemic injury of neurons is a pathological process observed in several neurological conditions, including ischemic stroke and neonatal hypoxic-ischemic brain injury (HIBI). An optimal treatment strategy for these conditions remains elusive. The present study delved deeper into the molecular alterations occurring during the injury process in order to identify potential therapeutic targets. Oxygen-glucose deprivation/reperfusion (OGD/R) serves as an established in vitro model for the simulation of HIBI. This study utilized RNA sequencing to analyze rat primary hippocampal neurons that were subjected to either 0.5 or 2 h of OGD, followed by 0, 9, or 18 h of reperfusion. Differential expression analysis was conducted to identify genes dysregulated during OGD/R. Time-series analysis was used to identify genes exhibiting similar expression patterns over time. Additionally, functional enrichment analysis was conducted to explore their biological functions, and protein-protein interaction (PPI) network analyses were performed to identify hub genes. Quantitative real-time polymerase chain reaction (qRT-PCR) was used for validation of hub-gene expression. The study included a total of 24 samples. Analysis revealed distinct transcriptomic alterations after OGD/R processes, with significant dysregulation of genes such as Txnip, Btg2, Egr1 and Egr2. In the OGD process, 76 genes, in two identified clusters, showed a consistent increase in expression; functional analysis showed involvement of inflammatory responses and signaling pathways like tumor necrosis factor (TNF), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and interleukin 17 (IL-17). PPI network analysis suggested that Ccl2, Jun, Cxcl1, Ptprc, and Atf3 were potential hub genes. In the reperfusion process, 274 genes, in three clusters, showed initial upregulation followed by downregulation; functional analysis suggested association with apoptotic processes and neuronal death regulation. PPI network analysis identified Esr1, Igf-1, Edn1, Hmox1, Serpine1, and Spp1 as key hub genes. qRT-PCR validated these trends. The present study provides a comprehensive transcriptomic profile of an in vitro OGD/R process. Key hub genes and pathways were identified, offering potential targets for neuroprotection after hypoxic ischemia.

The Shadow of the Film Monuments. Canonisation of the Czechoslovak New Wave as a Discursive Operation

The Czechoslovak New Wave represents an important chapter in the history of Central European cinema, and the body of films produced in Czechoslovakia in the 1960s is deservedly considered part of both national and European cultural heritage. This essay draws on the notion that the canon of the New Wave has established itself as a myth, obscuring the visibility of the newer Czech film production. Searching for the roots of the discursive nature of this canon, it finds it in a synergy of two opposing cultures. While the conservative communist power compiled the index of films associated with the 1960s reform process in order to stop their circulation, the dissenting community incorporated the same canon as a part of its collision with that power, a collision which manifested among others in the field of language. The transition of Czech cinema in the 1990s brought the Czechoslovak New Wave back to the spotlight, yet previous rhetorical use of this canon deepened the confusion between the discursive and the aesthetic and affirmed it as an unequivocal national monument. Exploring these tensions, I conclude that a new reading of the Czechoslovak New Wave heritage might be needed to make way for newer canons of films experimenting with different aesthetic and production approaches.

Problems and Countermeasures in the Open Recruitment of Public Institutions

As a vital channel for talent introduction in public institutions, open recruitment is an effective means to strengthen the construction of talent teams and promote the rapid development of these institutions. With its policy that evolves with the times, fair and unified organization, and standardized and orderly processes, open recruitment in public institutions ensures fairness, justice, and transparency in the talent recruitment process. However, as the era progresses, issues in the open recruitment of public institutions have gradually emerged, and there is an urgent need to improve various aspects such as recruitment conditions, examination formats, talent introduction channels, and post-appointment management. This paper deeply analyzes the characteristics and existing problems of open recruitment in public institutions and puts forward corresponding optimization strategies to improve the efficiency and quality of recruitment, aiming to help public institutions reach a new level of development.

Investigation of the thermal conductivity of SiO2 glass using molecular dynamics simulations

AbstractA recent study showed that generating local crystalline paths within a glassy matrix provides only a moderate increase in thermal conductivity until the path fills most of the total volume. It was indicated that percolation theory governs the thermal conductivity in such crystalline‐implanted glass composites. In this study, we use computer simulations to investigate the effect of partial vitrification by breaking structural order of silica crystals by local vitrification. Such locally vitrified crystal structures are made by the bond‐transposition method, where the extent of vitrification can be tuned. Also, we test melt‐quenching of three SiO2 crystalline structures (α‐quartz, coesite, and stishovite) to make silica glasses with different densities. The cooling rates and pressures were varied during the melting process in order to obtain glass structures with varied degrees of order. Our results show that the thermal conductivity of silica glasses calculated using Green–Kubo relation decreases rapidly as soon as the crystallinity is disturbed by bond transition or generated local glassy phase. This implies the phonon mean free path rapidly shrinks with even a small number of scatterers, regardless of the original polymorph. Through the investigation of the pressure effect, a strong proportional relation between the thermal conductivity and the density is found among all silica samples. Such correlation can be accounted by assuming a constant integral term in the Green–Kubo relation without the volume scaling, which is reasonable based on a weak dependence of κV on the density of silica glass except with a slight increase at low quench pressures. We hypothesize that when the quench pressure increases moderately, an increase of characteristic ring size tends to generate a more flexible SiO2 structure which results more phonon scattering. Green–Kubo modal analysis further shows that the contribution from modes at low frequencies is suppressed when SiO2 is melt‐quenched at higher pressure and vice versa.

Implementasi Model Prototye Dalam Pembuatan Aplikasi Pemesanan dan Perawatan Taxi Berbasis Website

Travel Janyakng Group is a travel company that operates in the car rental sector, where currently the company is facing several problems such as consumer inconvenience in ordering, apart from that, there are also difficulties in managing car maintenance data at the company. Seeing these problems, with the era of information technology Currently, companies can take steps, namely creating a website-based information system with the aim of improving the taxi ordering and maintenance process, as well as improving service to consumers. There are several methods used, namely the software development method using a prototype model and the data collection method using observation, interviews and literature study, while for building website-based applications the PHP and MySQL languages ​​are used, while for the application prototype the Balsamiq Wireframes application is used. In this application there will be three activities involved, namely user, admin and taxi driver. By using this application, it is hoped that the company can improve the quality of service to customers, make the ordering and maintenance process more efficient and the company can make better strategic decisions

Optimizing Robotic Mobile Fulfillment Systems for Order Picking Based on Deep Reinforcement Learning.

Robotic Mobile Fulfillment Systems (RMFSs) face challenges in handling large-scale orders and navigating complex environments, frequently encountering a series of intricate decision-making problems, such as order allocation, shelf selection, and robot scheduling. To address these challenges, this paper integrates Deep Reinforcement Learning (DRL) technology into an RMFS, to meet the needs of efficient order processing and system stability. This study focuses on three key stages of RMFSs: order allocation and sorting, shelf selection, and coordinated robot scheduling. For each stage, mathematical models are established and the corresponding solutions are proposed. Unlike traditional methods, DRL technology is introduced to solve these problems, utilizing a Genetic Algorithm and Ant Colony Optimization to handle decision making related to large-scale orders. Through simulation experiments, performance indicators-such as shelf access frequency and the total processing time of the RMFS-are evaluated. The experimental results demonstrate that, compared to traditional methods, our algorithms excel in handling large-scale orders, showcasing exceptional superiority, capable of completing approximately 110 tasks within an hour. Future research should focus on integrated decision-making modeling for each stage of RMFSs and designing efficient heuristic algorithms for large-scale problems, to further enhance system performance and efficiency.

Has the pandemic changed soccer training methodologies?

Introduction. The covid-19 pandemic affected the world of sports very directly. This forced the coaching staffs of the different clubs to reinvent themselves in their training processes in order to avoid the loss of sports performance of their squads, adapting their training methodologies to the conditions that prevailed at all times. Therefore, the objective of this research has been to find out if there are changes in the training and planning modes of soccer coaches during and after the pandemic. Methods: For this work, a cross-sectional descriptive study was carried out in a sample made up of 517 coaches from different divisions and nationalities. To characterize the sample, descriptive measures were used and Pearson's chi-square was used to study whether there is a relationship between the variables studied. All statistical analyses were performed with Stata version 12 (StataCorp., United States) and statistical significance was always established at a p value < 0.05. Results: The results of this study indicated that, regardless of the division in which they developed their profession, the coaches were forced to make methodological changes and substantial modifications in the planning of the sessions. They avoided contact exercises and focused on tactical and psychological aspects during and since the pandemic. Conclusion: The results of this study can be very useful for future technical bodies when it comes to distributing training and workload. Keywords: soccer; methodology; training; coaches; pandemic; COVID-19