The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was (...) used. The Statistical Package of Social Sciences (SPSS) was also used for data analysis. The study reached a number of results, the most important of which are: The level of efficiency of educational performance in Palestinian and international universities from the point of view of postgraduate and undergraduate students was high. And that there are significant differences between the average views of the sample of the study on the efficiency of educational performance in Palestinian and international universities attributed to the University and to the benefit of international universities. The study concluded many recommendations, the most important of which is the necessity of continuing to develop e-learning strategies that affect the efficiency of educational performance and research commensurate with the university's position in the local and international community, which puts it on the best classification between local and international universities through e-learning. (shrink)

The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected (...) and (SPSS) was used for statistical data analysis. The study found a significant relationship between E- Learning strategies and the efficiency of research performance in universities. It also reached the participation of senior management in the research that develops the university performance in the Palestinian universities. The senior management indicated that they do not care to follow the policies of implementing the development of scientific research. While the senior management in foreign universities indicated that they are interested in following up the policies of implementing the development of scientific research. The study also showed that senior management in Palestinian universities does not care about providing the appropriate budget for E- Learning. The study recommended that the senior management of Palestinian universities should provide an E- Learning budget and encourage employees to continue using E- Learning strategies. The administration in the Palestinian universities should adopt and support outstanding research, and the need to encourage interest in the implementation of policies for the development of scientific research. (shrink)

Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and (...) performance relevant to SLMs. A descriptive-correlational research design was employed in the study with 88 non-randomly chosen participants from secondary schools in West Philippines. The learners’ GWA (general weighted average) was used to determine their performance and a survey questionnaire for their profile and attitude. Frequency counts, percentage, and Spearman’s rank correlation coefficient were used to analyze the data gathered with the aid of Jamovi software. Results revealed a strong correlation between attitude and performance, but there was no link between learner’s attitude and performance as to the learner’s profile. It was affirmed that attitude is a compelling factor that is related with performance. Hence, this research has broader ramifications that can direct the Bureau of Learning Delivery to orient the module writers to further contextualize the learning materials that can compound learner’s disposition and academic performance. (shrink)

This article intends to analyze the performance and the efficiency of companies and to identify the key factors that may explain it. It was selected a sample with 15 enterprises: 7 Portuguese and 8 Ukrainian ones, belonging to several industries. Financial and non-financial data was collected for 6 years, during the period of 2009 to 2014. Research questions that guided this work were: Are the enterprises efficient/profitable? What factors influence enterprises’ efficiency/performance? Is there any difference between (...) Ukrainian and Portuguese enterprises’ efficiency/performance, which factors have more influence? Which industrial sector is represented by more efficient/profitable enterprises? The main results showed that in average enterprises were efficient with low level of profitability. According to gained results several indicators were highlighted so that companies would pay more attention to them. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...) dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (shrink)

The increasing complexity and scale of modern computing needs have led to the development and adoption of cloud computing as a ubiquitous paradigm for data storage and processing. The hybrid cloud model, which combines both public and private cloud infrastructures, has been particularly appealing to organizations that require both the scalability offered by public clouds and the security features of private clouds. Various strategies for configuring and managing resources have been developed to optimize the hybrid cloud environment. These strategies aim (...) to balance conflicting objectives such as cost-efficiency, performance optimization, security, and compliance with regulatory standards. This exploratory research focused on evaluating the efficiency and limitations of different configuration strategies in hybrid cloud environments. Findings indicate that each approach presents distinct advantages. Improving resource utilization and automating governance processes are significant advantages of Policy-based Resource Management, which leads to costeffectiveness. Intelligent routing of traffic is a feature of Cross-cloud Load Balancing, resulting in optimized performance and higher service availability. By centralizing control, the Hybrid Cloud Service Mesh allows for secure and streamlined cross-service communication. A notable feature of Cross-cloud Container Orchestration is its ability to simplify the migration of applications across diverse cloud environments. For immediate threat detection and regulatory compliance, real-time monitoring is facilitated by Log Management and Analytics. However, Policy-based Resource Management can be complex and inflexible. Extra costs for data transfer between different cloud providers are a drawback of Crosscloud Load Balancing. Additional network hops create latency issues in Hybrid Cloud Service Mesh configurations. If configured incorrectly, Cross-cloud Container Orchestration could expose the system to security risks. Finally, Log Management and Analytics require both ample storage and advanced analytical capabilities. (shrink)

The project titled "Efficient Machine Learning Algorithm for Future Gold Price Prediction" focuses on the development of a machine learning model that can accurately predict future gold prices using historical data and various economic indicators. Gold has long been regarded as a safe-haven asset, and its price is influenced by multiple factors, including global economic conditions, inflation rates, interest rates, and geopolitical events. This research aims to design and implement a robust machine learning model that can analyze complex patterns and (...) trends in gold prices to generate reliable predictions. The project employs a range of machine learning techniques such as Linear Regression, Random Forest, and Support Vector Machines (SVM) to build the prediction model. It utilizes key features like historical price data, currency exchange rates, commodity prices, and stock market trends as input variables. The performance of the model is evaluated using standard metrics such as accuracy, precision, recall, and RMSE (Root Mean Squared Error). The final model is optimized for accuracy and efficiency, making it a useful tool for investors and financial analysts who seek to forecast gold prices and make informed investment decisions. (shrink)

Accelerated computing leverages specialized hardware and software techniques to optimize the performance of computationally intensive tasks, offering significant speed-ups in scientific, engineering, and data-driven fields. This paper presents a comprehensive study examining the role of accelerated computing in enhancing processing capabilities and reducing execution times in diverse applications. Using a custom-designed experimental framework, we evaluated different methodologies for parallelization, GPU acceleration, and CPU-GPU coordination. The aim was to assess how various factors, such as data size, computational complexity, and task (...) concurrency, impact processing efficiency. Our findings reveal that implementing accelerated computing can achieve substantial improvements, often reducing computation times by more than 60% compared to traditional sequential methods. This paper details the experimental setup, including algorithm selection and parallelization techniques, and discusses the role of memory bandwidth and latency in achieving optimal performance. Based on the analysis, we propose a streamlined methodology to guide the deployment of accelerated computing frameworks in various industries. Concluding with a discussion on future directions, we highlight potential advancements in hardware architectures and software optimizations that could further augment computational efficiency and scalability in accelerated computing. (shrink)

Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. The proposed approach is validated through extensive simulations, demonstrating significant improvements in energy consumption, packet delivery ratio, and overall network performance. The results suggest that the optimized aggregated packet transmission method can effectively extend the lifespan of duty-cycled WSNs while ensuring reliable data communication. (...) Future work will explore the integration of machine learning techniques for adaptive scheduling and the application of the proposed method to heterogeneous WSNs. (shrink)

Albania is part of the emerging economies of the Western Balkan region. Polis University is one of the pioneering institutions in the field of architecture, built environment, and city sciences that represents innovative methodologies and concepts for educational and scientific purposes. Nowadays, many constructions in Albania involve a wide range of different materials. The building envelope is one of the main elements that provide protection from the outside environment but also the required thermal comfort for the inhabitants. The necessary balance (...) must be archived between energy efficiency and the durability of buildings. This paper will focus on the thermal performance and materials composition of two different types of masonry walls, a constituent part of Polis University's main building. The study will be based on an experiment using specific instruments to diagnose these typologies of wall composition. The results are further analyzed and compared. Specific instruments such as the thermal camera (Testo 882), U-value(Testo 435-2), and “Silverline Digital Moisture Meter” (from POLIS Energy lab) are engaged. The collected data are further interpreted through graphs, tables, and diagrams for both cases. It is observed that ventilated facades perform much better than standard facades, therefore their usage is strongly recommended. (shrink)

Workforce education forms one of the core aspects of organizational learning which aims for performance as well as efficiency. Learning is goal-oriented in business organizations. Organizations' activities are highly-oriented towards customer satisfaction. Organizations learn from practice and delivery of services to meet consumer needs and necessities. Perfection, efficiency and smart practices define today's multinational organizational culture. But how do the multinational organizations achieve such perfections in their business operations? This paper addresses this issue by linking teleological aspects (...) of learning and practice to performance, adoption of routines, and learning-induced adaptation in order to explain how they achieve "perfection" in practice and operations. Further, the paper attempts to study a particular aspect of organizational (teleological perfectionism) process by modeling scenarios which define goal oriented organizational learning and adaptation, and underpins how such teleological processes effectively benefit organizations in the long run. Conclusions drawn up from an example being modeled in this paper suggest that teleology, or teleological dynamics play significant role in shaping today's organizations and help explain some (or high) degree of perfectionism in their operations. (shrink)

In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and (...) simulated annealing. By focusing on both resource utilization and SLA compliance, the proposed approach aims to reduce latency, improve throughput, and maximize overall system efficiency. The research introduces a novel framework that incorporates real-time monitoring, dynamic resource allocation, and adaptive threshold settings to ensure consistent SLA adherence while optimizing computing performance. (shrink)

As the Internet of Things (IoT) continues to expand, ensuring secure and efficient data storage and retrieval becomes a critical challenge. IoT devices, often constrained by limited computational resources, require lightweight encryption protocols that balance security and performance. This paper presents an optimized encryption protocol designed specifically for lightweight, searchable data in IoT environments. The proposed protocol utilizes advanced optimization techniques to enhance the efficiency and security of searchable encryption, enabling rapid data retrieval without compromising the integrity and (...) confidentiality of the data. The protocol leverages a hybrid cryptographic approach, combining symmetric and asymmetric encryption, to ensure robust protection against unauthorized access while maintaining low computational overhead. Furthermore, the implementation of an optimized keyword indexing mechanism facilitates fast and accurate search operations, making the protocol well-suited for real-time IoT applications. Extensive experiments were conducted using various IoT datasets to evaluate the performance of the proposed protocol in terms of encryption speed, search efficiency, and overall security. The results demonstrate that the optimized encryption protocol significantly outperforms existing methods, offering a scalable solution that meets the stringent requirements of IoT systems. This research contributes to the field by providing a practical and secure encryption solution that addresses the unique challenges of IoT environments, paving the way for more secure and efficient IoT networks. (shrink)

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, (...) including divide-and-conquer, hybrid sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (shrink)

Buildings are the largest energy consumer worldwide, according to the United Nations Environment Programme (UNEP). Most of the building’s energy consumption is in the building’s life cycle stage. Therefore, achieving sustainable development at the national level requires minimizing the building’s effects on the environment via reducing energy consumption by buildings. The building’s energy performance will be predicted and evaluated by the energy simulation. Using BIM in EPAs significantly reduces time and costs. This study aimed to optimize energy consumption in (...) buildings using Building Information Modeling (BIM) Technology, which can assess energy performance in the building. In this research, the general form of the building was modeled on the Autodesk Revit Software. The main shape of the building was chosen for modeling after reviewing the proposed designs. Then, the building energy consumption was calculated using the relevant tools in this scope, according to the materials, equipment, and project location. Finally, the best possible mode was selected by examining different modes of energy consumption. The results showed that 61.48% difference between the best mode of energy consumption optimization and the current mode of the building and 79.35% compared to the initial mode. Finally, parametric studies of alternative cost optimization schemes showed that saving 58.23% of the building’s current status for a 30-year horizon. (shrink)

The LIBOR Market Model has become one of the most popular models for pricing interest rate products. It is commonly believed that Monte-Carlo simulation is the only viable method available for the LIBOR Market Model. In this article, however, we propose a lattice approach to price interest rate products within the LIBOR Market Model by introducing a shifted forward measure and several novel fast drift approximation methods. This model should achieve the best performance without losing much accuracy. Moreover, the (...) calibration is almost automatic and it is simple and easy to implement. Adding this model to the valuation toolkit is actually quite useful; especially for risk management or in the case there is a need for a quick turnaround. (shrink)

The exponential growth of data storage requirements has become a pressing challenge in hybrid cloud environments, necessitating efficient data deduplication methods. This research proposes a novel Smart Deduplication Framework (SDF) designed to identify and eliminate redundant data, thus optimizing storage usage and improving data retrieval speeds. The framework leverages a hybrid cloud architecture, combining the scalability of public clouds with the security of private clouds. By employing a combination of client-side hashing, metadata indexing, and machine learning-based duplicate detection, the framework (...) achieves significant storage savings without compromising data integrity. Real-time testing on a hybrid cloud setup demonstrated a 65% reduction in storage needs and a 40% improvement in data retrieval times. Additionally, the system employs blockchain for immutable logging of deduplication activities, enhancing transparency and traceability. This study concludes with an evaluation of the deduplication framework's impact on cost efficiency, system performance, and potential scalability. Future enhancements aim to integrate multi-cloud interoperability and advanced compression algorithms to further refine storage management. (shrink)

The performing arts and their financing have been analyzed by cultural economics. Many papers have focused on importance of state intervention both as a financing agent, as a provider and producer of cultural services. Otherwise, several studies have appeared focusing on management of the performing arts in Management Accounting framework. This paper shows relevance of performance indicators for evaluating cultural policies and focuses on symphony orchestras financed with public funds. The objective is verifying strategy compliance and measure the efficient (...) and effective use of the public resources and evaluate the social and cultural profitability too. This paper also proposes a change in the symphonic orchestras current strategy for increasing social and cultural profitability. (shrink)

In the current digital environment, cyberattacks continue to pose a serious risk and difficulty. Internet of Things (IoT) devices are becoming more and more vulnerable due to security problems like ransomware, malware, poor encryption, and IoT botnets. These flaws may result in ransom demands, data tampering, illegal access, and system risks. Creating strong cybersecurity procedures for contemporary smart environments is essential to resolving these problems. This strategy uses proactive network traffic monitoring to spot any dangers in the Internet of Things (...) ecosystem. Our approach is to improve Smart Environments' security and awareness of potential threats. Two IoT gateways were used to examine the effectiveness and performance of a deep neural network (DNN) model. The results were promising: the model caused an average increase of less than 30 kb/s in network bandwidth and a mere 2% rise in CPU usage. Additionally, memory and power consumption were minimal, with 0.42 GB and 0.2 GB of memory usage for NVIDIA Jetson and Raspberry Pi devices, respectively, and an average 13.5% increase in power consumption per device. The machine learning models achieved nearly 93% detection accuracy and a 92% F1 score on the datasets used. Our framework demonstrates an effective and efficient method for detecting malware and attacks in Smart Environments. (shrink)

The objective of this study is to Analyze the Financial Position and Performance of the Axis and Kotak Mahindra Bank in India based on their financial characteristics. We have chosen the CAMEL model and t-test which measures the performance of bank from each of the important parameter like capital adequacy, asset quality, management efficiency, earning quality, liquidity and Sensitivity. The present study is conducted analyze the consistency of the profitability of the Axis and Kotak Mahindra bank’s. It (...) is analyses that the ratio of credit deposit is maximum of Kotak Mahindra Bank Ltd and it shows efficient management of the bank. The ratio of earning per share is maximum for Axis Bank Ltd i.e. 50.28 and the ratio of return on Assets is minimum for Axis Bank Ltd. The CAMELS’ analysis and t-test concludes that there is no significance difference between the Axis and Kotak Mahindra bank’s financial performance but the Kotak Mahindra bank performance is slightly less compared with Axis Bank. (shrink)

Verbal fluency tasks are often used in neuropsychological research and may have predictive and diagnostic utility in psychiatry and neurology. However, researchers using verbal fluency have uncritically assumed that there are no category-or phoneme-specific effects on verbal fluency performance. We recruited 16 healthy young adult subjects and administered two semantic (animals, trees) and phonemic (K, M) fluency tasks. Because of the small sample size, results should be regarded as preliminary and exploratory. On the animal compared to the tree task, (...) subjects produced significantly more legal words, had a significantly lower intrusion rate, significantly shorter first-response latencies and final silence periods, as well as significantly shorter between-cluster response latencies. These differences may be explained by differences in the category sizes, integrity of the categories’ borders, and efficiency of the functional connectivity between subcategories. On the K compared to the M task, subjects produced significantly more legal words and had significantly shorter between-cluster response times. Counterintuitively, a corpus analysis revealed there are more words starting with ⟨m⟩ compared to ⟨k⟩ in the experimental language. Our results potentially have important implications for research utilizing verbal fluency, including decreased reproducibility, questionable reliability of diagnostic and predictive tools based on verbal fluency, decreased knowledge accumulation, and increased number of publications with potentially misleading clinical interpretations. (shrink)

In the competitive and dynamic world of financial technology (fintech), high performance and low latency are crucial for real-time transactions and data processing. Microservices architecture, combined with efficient caching mechanisms, significantly enhances scalability and responsiveness. VMware GemFire, an in-memory data grid, provides robust caching solutions that, when paired with Java 17’s Z Garbage Collector (ZGC) and heap Least Recently Used (LRU) eviction strategies, can maximize cache performance. This paper proposes a system integrating GemFire with ZGC to optimize memory (...) management, reduce latency, and maintain high throughput. The heap LRU eviction strategy ensures that the least recently used data is evicted first when memory limits are reached, maintaining high cache hit rates and reducing the risk of the JVM running out of memory. By adjusting ZGC and using heap LRU eviction, this combined method makes it easier for microservices to handle changing workloads, grow horizontally, and speed up data access, which improves the overall performance and reliability of the system. Different settings for SoftMaxHeapSize have different effects on heap usage, operation throughput, and garbage collection performance. The results of the experiments show how to tune GemFire cache performance to work best in a microservices environment. (shrink)

One element in the choice of a constitutional design or model of democracy is the criterion of efficiency. Different political scientists, however, understand the word ‘efficiency’ in different ways. The author suggests a distinction between its two main meanings: (1) efficiency-action capacity and (2) effectiveness-socioeconomic performance. It is not just socio-economic effectiveness that is important, but also political efficiency-action capacity. Efficiency-action capacity is closely linked with the theory of democracy put forward by Schumpeter and (...) adopted by the majority of political scientists today. Thus efficiency is essential not only for the government (in that it simplifies the operation of power) but also, and even more importantly, for the governed, for the citizens (in that it simplifies the choice and peaceful removal of the rulers, i.e. the executive). (shrink)

Server-less computing, also known as Function as a Service (FaaS), revolutionizes cloud architecture by allowing developers to focus on code and functionality without managing underlying infrastructure. This paradigm enhances resource management efficiency by dynamically allocating resources only when needed, thus optimizing cost and performance. Server-less models, epitomized by platforms like AWS Lambda, Google Cloud Functions, and Azure Functions, provide automatic scaling and fine-grained billing, making them ideal for applications with variable workloads. While challenges such as cold start latency (...) and complex debugging exist, the benefits of server-less computing—including cost savings, simplified deployment, and accelerated innovation—make it a transformative approach in the cloud computing landscape. This paper explores the principles, benefits, challenges, and practical applications of server-less computing in modern cloud architectures, highlighting its potential to drive efficiency and innovation. (shrink)

Clinical practice is a part of the integral learning method in nursing education. The use of information and communication technologies (ICT) in clinical learning is highly encouraged among nursing students to support evidence-based nursing and student-centered learning. Through the information-processing lens of the mindsponge theory, this study views performance expectancy (or perceived usefulness) and effort expectancy (or perceived ease of use) as results of subjective benefit and cost judgments determining the students’ ICT using intention for supporting clinical learning, respectively. (...) Therefore, the study examines whether effort expectancy moderates the relationship between performance expectancy and the intention to use ICT among Moroccan nursing students. The Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of 702 Moroccan nursing students. We found that nursing students’ performance expectancy is positively associated with the intention to adopt ICT and social media, while effort expectancy positively moderates this relationship. Moreover, the model with effort expectancy as the moderator was discovered to have a significantly larger weight than the model with effort expectancy as the direct predictor, validating our information-processing reasoning. This study provides a new perspective on the interplay between the benefit and cost perceptions of ICT use to support clinical learning methods in nursing education. Moreover, given the limited education resources, especially in developing countries like Morocco, we recommend nursing education and training prioritize communicating the benefits of ICTs and social media over ease of use. Doing so would help improve the effectiveness and efficiency of nursing education and training while lowering costs. (shrink)

The primary objective of this research is to enhance the precision and speed of stock handling while minimizing human intervention and error. Our design incorporates state-of-the-art sensors, real-time tracking systems, and autonomous robots programmed with advanced algorithms for object identification, gripping, and movement. We propose a systematic workflow for automating the storage and retrieval process, starting from the identification of the stock to its precise placement and retrieval within the storage facility. The design also addresses potential challenges such as robot (...) mobility, collision avoidance, and space optimization. Performance metrics, including accuracy, time efficiency, and system scalability, are measured using simulation-based experiments in a controlled environment. The results show significant improvements in operational efficiency compared to traditional stock management approaches. This integration paves the way for future advancements in fully automated warehouses, reducing the need for human labor and increasing reliability. Finally, we discuss potential enhancements, including AI-based decision-making algorithms, multi-robot collaboration, and integration with Internet of Things (IoT) for real-time data analysis and continuous system improvement. (shrink)

The purpose of the study is to reveal the relationship between the justification of strategic decisions and the increase in efficiency of transnational corporations (TNC). The conceptual bases of the justification of strategic decisions for increasing the efficiency of TNC are suggested, the development of which involves research of the preconditions on which their implementation is based, analysis of the main aspects of TNC's activity and accordance with the principles of justification of strategic decisions, strategic decision-making. The results (...) of the comprehensive diagnostic examination of TNC of leading bearings manufacturers are presented, which revealed the problems of their functioning on the market, changes in the dynamics of performance indicators, differences in the use of opportunities, financial state, strategic positions on the market, the efficiency of made decisions. A model for selecting a decision strategy for TNC is suggested. Practical recommendations of implementing strategic decisions for increasing the efficiency of activity of TNC of leading bearings manufacturers are given. (shrink)

The research aims to identify the reality of modern methods applied in the process of performance assessments of employees in the municipalities of Gaza-strip, Complete Census method of community study was used, (571) questionnaires were distributed to all members of the community study, (524) questionnaires were recovery with rate of (91.76%). The most important findings of the study: There were statistically significant relationship differences between the applications of modern methods in the performance assessments of employees in the municipalities (...) of Gaza-strip. There was statistically significant relationship between the evaluation criteria that fit the required performance and the application of standards evaluations on performance of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the use of methods, models for the evaluation of appropriate functions and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the feedback and the application of performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the efficient, professional assessors and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the extent of awareness of subordinates, participation in the evaluation of their performance and the application of the performance assessments of employees in the municipalities of Gaza-strip. The research also concluded a series of recommendations, including: that the design of evaluation models must be done with the participation of the employees and inform them of it, and that a date must be set to provide feedback and discuss the results with them, that they should be allowed grievance in front of an ad hoc committee in accordance with the known system. Direct manager must inform employees of their performance assessment date, discuss the results of the evaluation with them, and others should be involved with the direct manager of employees in their performance evaluation. The application of modern methods of performance evaluation through the good and purposeful planning should be used, analyzing and employing the results in administrative decisions regarding the employees, and the application of modern methods must be used in an effective and efficient performance evaluation. (shrink)

This paper affords the design and improvement of a semi-active suspension system for an automobile. The main idea is to increase the semi-active suspension system damping vibration of the automobile body even as crossing the bump and sine pavement on the road. This system is modelled for 1 / 4 car system after which the entire system has been simulated usingMat lab/Simulink. It is used to physically simulate the quarter vehicle system of the automobile and have a look at the (...) time domain response to the road disturbances.H infinity controllers is used to govern the damping properties of the semi-active suspension system mechanically. The system is designed in contrast to the most of the available suspension systems using a third order hydraulic actuator. The proposed system is compared with H2 optimal controller to test the performance of the system for the control targets suspension deflection, body acceleration and body travel for the bump and sine road disturbances. The simulation result of this studies reveal the efficiency of the advanced H∞controller for the quarter car semi-active suspension system. (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments (...) with the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

Globalization and technological advancement has made market competitive. To survive in market every organization needs to maintain high performance. It can only be possible when the employees working in organization perform more efficiently than competitors. Increase in competition of market has made employee performance a big question to organization for its survival in global competition. Study reveals performance of employee is affected by various component of human resource management i.e. Job satisfaction, leadership, training &development and work stress. (...) HRM is managing people effectively and efficiently to achieve strategic aims of organization. This study focuses on analyzing the impact of HR components on performance of employee. It also compares impact of HR component respect to public and private organizations. The study finds HR components have significant positive relationship with employee performance except work stress. Study also interprets findings irrespective of organization type. (shrink)

These days, Thin-client devices are continuously accessing the Internet to perform/receive diversity of services in the cloud. However these devices might either has lack in their capacity (e.g., processing, CPU, memory, storage, battery, resource allocation, etc) or in their network resources which is not sufficient to meet users satisfaction in using Thin-client services. Furthermore, transferring big size of Big Data over the network to centralized server might burden the network, cause poor quality of services, cause long respond delay, and inefficient (...) use of network resources. To solve this issue, Thinclient devices such as smart mobile device should be connected to edge computing which is a localized near to user location and more powerful to perform computing or network resources. In this paper, we introduce a new method that constructs its architecture on Thin-client -edge computing collaboration. Furthermore, present our new strategy for optimizing big data distribution in cloud computing. Moreover, we propose algorithm to allocate resources to meet Service Level Agreement (SLA) and Quality of Service (QoS) requirements. Our simulation result shows that our proposed approach can improve resource allocation efficiently and shows better performance than other existing methods. (shrink)

The increasing complexity and demands of next-generation networks necessitate the integration of Artificial Intelligence (AI) to enhance their efficiency and security. This article explores advancements in AI-driven communication systems, focusing on optimizing network performance, ensuring robust security measures, and addressing the challenges of scalability and real-time adaptability. By analyzing case studies, emerging technologies, and recent research, this study highlights AI's transformative potential in redefining communication systems for future applications.

Artificial Intelligence (AI) is rapidly transforming Human Resource Management (HRM) by enhancing the efficiency and effectiveness of key functions such as recruitment, performance management, and employee engagement. This paper explores the integration of AI technologies in HRM, focusing on their potential to revolutionize these critical areas. In recruitment, AI-driven tools streamline candidate sourcing, screening, and selection processes, leading to more accurate and unbiased hiring decisions. Performance management is similarly transformed, with AI enabling continuous, data-driven feedback and personalized (...) development plans that align with organizational goals. Furthermore, AI facilitates more engaging and tailored employee experiences by leveraging predictive analytics to anticipate and address employee needs. Despite these advancements, the paper also addresses the ethical considerations and challenges associated with AI in HRM, including data privacy concerns and the risk of over-reliance on automated systems. Through a comprehensive analysis, this paper aims to provide insights into how AI can be strategically leveraged to optimize HRM practices, while highlighting the need for a balanced approach that integrates human judgment with technological innovation. (shrink)

High-Performance Computing (HPC) has become a cornerstone for enabling breakthroughs in artificial intelligence (AI) by offering the computational resources necessary to process vast datasets and optimize complex algorithms. As AI models continue to grow in complexity, traditional HPC systems, reliant on central processing units (CPUs), face limitations in scalability, efficiency, and speed. Emerging technologies like quantum computing and specialized hardware such as Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), and Field Programmable Gate Arrays (FPGAs) are poised to (...) address these challenges. This research paper explores various HPC techniques used to optimize and accelerate AI algorithms, focusing on quantum computing’s potential for parallelism and specialized hardware's capabilities in delivering faster computation and energy efficiency. It delves into current advancements, comparative analyses of different HPC methods, and the integration of hybrid quantum-classical approaches to further enhance AI optimization. The study also examines the challenges of implementing these technologies at scale, with an eye toward the future of AI acceleration and the role of HPC in maintaining energy efficiency while meeting computational demands. Through this investigation, we aim to provide a comprehensive overview of how quantum computing and specialized hardware are reshaping the landscape of AI, paving the way for more advanced, efficient, and sustainable AI solutions. (shrink)

The effect of time pressure on metacognitive control is of theoretical and empirical relevance and is likely to allow us to tap into developmental differences in performances which do not become apparent otherwise, as previous studies suggest. In the present study, we investigated the effect of time pressure on metacognitive control in three age groups (10-year-olds, 14-year-olds, and adults, n = 183). Using an established study time allocation paradigm, participants had to study two different sets of picture pairs, in an (...) untimed and a timed condition. The results showed that metacognitive self-regulation of study time (monitor-based study time allocation) differed between age groups when studying under time pressure. Even though metacognitive control is firmly coupled at 10 years of age, the overall level of self-regulation of adults was higher than that of children and adolescents across both study time conditions. This suggests that adults might have been more sensitive to experiential metacognitive cues such as JoL for the control of study time. Moreover, the timed condition was found to be more effective than the untimed, with regard to study time allocation. Also, there was an age effect, with adults being more efficient than 10- and 14-year-olds. (shrink)

Evolutionary economics often focuses on the comparison between economic competition and the process of natural selection to select the fitter members of a given population. But that neglects the other "half" of an evolutionary process, the mechanism for the generation of new possibilities that is key to dynamic efficiency. My topic is the process of parallel experimentation which I take to be a process of multiple experiments running concurrently with some form of common goal, with some semi-isolation between the (...) experiments, with benchmarking comparisons made between the experiments, and with the "migration" of discoveries between experiments wherever possible to ratchet up the performance of the group. The thesis is that parallel experimentation is a fundamental dynamic efficiency scheme to enhance and accelerate variation, innovation, and learning in contexts of genuine uncertainty or known ignorance. Within evolutionary biology, this type of parallel experimentation scheme was developed in Sewall Wright's shifting balance theory of evolution. It addressed the rather neglected topic of how a population on a low fitness peak might eventually be able to go "downhill" against selective pressures, traverse a valley of low fitness, and then ascend a higher fitness peak. The theme of parallel experimentation is used to recast and pull together dynamic and pluralistic theories in economics, political theory, philosophy of science, and social learning. (shrink)

Purpose. To determine the potential of deforming broaching for the improvement of efficiency of cutter chisels in the mining industry. Methodology. The study of the application of the technological process of deforming broaching was carried out based on the experimental research into conditions of assembly of press couplings corresponding to cutting rock-destroying tools, the working surface of which is reinforced with solid-alloy inserts. Findings. Based on the conducted research, a new process of assembling the crowns of cutter chisels with (...) the use of deforming broaching was developed. Originality. It was determined that the range of angles of inclination of generatrix of the working cone of the deforming element and the roll-treading lip of the insert, which are necessary for efficient machining and pressing in crowns of cutters, is 4–16°. It was proven that the “solid alloy-steel” press couplings for cutter chisels will have the maximum bearing capacity at total tension a/d0 ≤ 3 %. It was found that it is necessary to foresee the following distribution of tensions: to perform 2 % of deformation by preliminary deforming broaching, and 1 % ‒ by pressing in an insert Practical value. The use of deforming broaching makes it possible to increase the strength of fastening the inserts of cutter chisels by 2 times, to reduce specific consumption of the tool by 4.4 times, and to increase the average drilling rate by 4 times. (shrink)

This paper examines the differences in the impact of ownership types and economic sectors on the business efficiency of 4,733 enterprises in Vietnam by the year of 2015. By the method of analysis of variance (ANOVA), it is shown that while types of ownership, foreign, state and private ownership, have a significant and different impact on the performance of businesses, the difference in economic sectors does not affect the enterprise efficiency. In addition, when testing simultaneous effect of (...) these factors, some findings are as follows: private-owned enterprises’ efficiency in the manufacturing and service sectors is better than those in agriculture, forestry and fishing sector; conversely, foreign invested enterprises operating in agriculture, forestry and fishing sector own better performance than theirs in manufacturing and service sectors; state-owned enterprises in manufacturing and service sectors is very less efficient than theirs in agriculture, forestry and fishing sector. (shrink)

By studying the effect of human resource development on strengthening the firm's total capabilities this literature review investigates the relationship between the development of human capabilities and company performance by studying the effects of human resource development on strengthening a firm’s total capabilities. To provide a thorough grasp of the subject, the review synthesizes and analyzes pertinent research articles, academic papers, and industry reports. SPSS version 22 statistical software was used for social sciences. Descriptive and inferential statistics were used (...) to analyze the questionnaire data. To attain a lasting competitive advantage, the assessment also emphasizes the significance of fostering a learning culture, adopting cutting-edge procedures, and putting in place efficient training and development programs. The main findings show that investing in the growth of human capabilities has a favorable impact on the success of the company, especially when those investments are made in conjunction with the growth of the organization's capabilities. Investing in an employee's skill and capability development boosts productivity, enhances innovation, reduces costs, fosters customer loyalty and satisfaction, and provides a company with a competitive advantage. (shrink)

Buildings are the largest energy consumer in the world, according to the United Nations Environment Program. Most of the energy will be used during the building life-cycle stage. Thus, achieving sustainable development at the national level requires minimizing the impact of buildings on the environment by reducing energy consumption. Using Building Information Modeling technology in energy performance assessment could be significantly reduced time and cost. This study aimed to optimize energy consumption in a residential building using BIM technology. The (...) main focus of this study was to evaluate energy performance through the simultaneous evaluation of building components using BIM technology with a conceptual design approach, comparison, and reduction of energy consumption. To investigate different design ideas were created several conceptual masses in Autodesk Revit software with a top-down design approach. After reviewing the conceptual masses, the main building form was chosen for modeling. Then, building energy consumption was computed using related tools in this field, based on the type of materials, equipment, and project location. Finally, the most optimal mode was selected by examining different energy consumption forms. The results of parametric studies on alternative schemes of energy optimization showed that 58.46% of energy cost savings could be achieved compared to the initial model of the building on a 30-year time horizon. (shrink)

The project centers on the development and deployment of live digital twins for power plants, designed to seamlessly integrate with existing monitoring and database systems. These digital twins act as dynamic, real-time virtual replicas of physical power plants, capturing the intricate details of plant operations, infrastructure, and environmental interactions. The primary objective is to leverage this technology to enhance the construction, operation, and maintenance phases of power plant management. By continuously receiving real-time data from various operational sensors, equipment, and external (...) monitoring sources, the digital twin models can simulate real-world conditions, providing a holistic view of plant performance. This includes critical output parameters such as energy generation, spill rates, and head loss, particularly in the context of hydroelectric plants. The digital twins serve as a powerful tool for optimizing energy production, identifying potential issues before they escalate, and facilitating proactive maintenance strategies, thereby minimizing downtime and maximizing efficiency. Furthermore, these models allow for a more informed and data-driven approach to plant management, ensuring that every aspect of plant performance, from structural integrity to environmental impact, is closely monitored and analyzed. The integration of digital twin technology into operational workflows enables plant operators and engineers to make smarter, more efficient decisions based on real-time, actionable insights. This project not only aims to improve the day-to-day functionality of power plants but also sets the stage for future advancements in power plant technology, contributing to the broader goals of sustainability, energy efficiency, and the long-term viability of energy infrastructure. By embracing this innovative approach, the project seeks to usher in a new era of smarter, more sustainable power plant management. (shrink)

E-Government refers to the administration of Information and Communication Technologies (ICT) to the procedures and functions of the government with the objective of enhancing the transparency, efficiency and participation of the citizens. E-Government is tough systems that require distribution, protection of privacy and security and collapse of these could result in social and economic costs on a large scale. Many of the available e-government systems like electronic identity system of management (eIDs), websites are established at duplicated databases and servers. (...) An established validation and management system could face a single failure point and the system is prone to Distributed Denial of Service Attacks (DDoS), denial of service attacks (DoS), malware and other cyber attacks. The execution of a privacy preserving and a secure decentralized system is enabled by the block chain technology. Here any third-party organizations do not have any control over the transactions of the Government. With the help of block chain technology, new and existing data are encapsulated within ledger or blocks, which are evenly distributed through the network in an enduring and sustainable way. The privacy and security of information are improved with the help of block chain technology, where distribution and encryption of data are performed through the total network. This analytical paper maps out the analysis of the security in the e-government system, utilizing the block chain technology that provides privacy and security of information and thereby enhancing the trust among the public sector. Qualitative and theoretical analysis is made for the proposed topic and implications of privacy and security of the proposed system is made. (shrink)

Banking sector is one of the fastest growing sectors in India. Today’s banking sector becoming more complex. The objective of this study is to analyze the Financial Position and Performance of the Bank of Baroda and Punjab National Bank in India based on their financial characteristics. This study attempts to measure the relative performance of Indian banks. For this study, we have used public sector banks. We know that in the service sector, it is difficult to quantify the (...) output because it is intangible. We have chosen the CAMEL model and t-test which measures the performance of bank from each of the important parameter like capital adequacy, asset quality, management efficiency, earning quality, liquidity and Sensitivity. (shrink)

The aim of this study was to identify the reality of the performance of the employees in The Palestinian Cellular Telecommunications Company (Jawwal), and to find the differences between the views of the study sample on the variables of the study according to the variables (age, scientific qualification, field of work and years of service). To achieve the objectives of the study, a questionnaire was designed and developed to measure the variables of the study applied to the company's 70 (...) employees. The Complete Census method was used and 60 samples were recovered for analysis with a recovery rate (85.7%). The SPSS statistical package was adopted. The study reached several results, the most important of which is that the degree of approval for the job performance of the employees working in The Palestinian Cellular Telecommunications Company (Jawwal) is 81.56%. The results showed that there were no statistically significant differences at the level of α≤ 0.05 between the average of the respondents' opinions on the performance of the workers in the Palestinian Cellular Telecommunications Company (Jawwal) due to the following variables (age, scientific qualification, field of work, number of years of service). The most important recommendations were to increase the efficiency of the employees of the company using the equipment of their work, and the need to pay attention to the development of the skills of employees through specialized training programs to improve their performance. And focus on moral incentives because of their role in improving the performance of employees by spreading the spirit of cooperation between … . (shrink)

cloud computing is a general term used to depict another class of system based computing that happens over the web. The essential advantage of moving to Clouds is application versatility. Cloud computing is extremely advantageous for the application which are sharing their resources on various hubs. Scheduling the errand is a significant testing in cloud condition. Typically undertakings are planned by client prerequisites. New scheduling techniques should be proposed to defeat the issues proposed by organize properties amongst client and resources. (...) New scheduling systems may utilize a portion of the customary scheduling ideas to consolidate them with some system mindful procedures to give answers for better and more effective employment scheduling. Scheduling technique is the key innovation in cloud computing. This paper gives the study on scheduling calculations. There working regarding the resource sharing. We systemize the scheduling issue in cloud computing, and present a cloud scheduling pecking order. (shrink)

This paper provides a comprehensive workflow for organizations considering a move from legacy database systems to Snowflake, demonstrating how a structured migration process can result in enhanced data accessibility, operational flexibility, and long-term scalability. Future directions for research are also discussed, including integration with advanced analytics and machine learning applications, which could further augment Snowflake’s utility in big data ecosystems.

Data preparation, feature engineering, model training, and performance evaluation are all part of the study methodology. To ensure reliable and broadly applicable models, we utilize optimization techniques like Grid Search and Genetic Algorithms to precisely adjust model parameters. Features including age, blood pressure, cholesterol levels, and lifestyle choices are employed as inputs for the machine learning models in the dataset, which consists of patient medical information. The predictive capacity of the model is evaluated using evaluation measures, such as accuracy, (...) precision, recall, F1-score, and the area under the ROC curve (AUC-ROC). Our findings show that improved machine learning models perform better than conventional methods, offering trustworthy forecasts that can help medical practitioners with early diagnosis and individualized treatment planning. In order to achieve even higher predicted accuracy, the study's conclusion discusses the significance of its findings for clinical practice as well as future improvements that might be made, like adding wearable device data in real-time or investigating deep learning techniques. (shrink)

The implementation of this project has numerous practical applications. For instance, it can be integrated into mobile or web-based platforms to provide real-time bird identification tools for researchers, birdwatchers, and environmental agencies. It can also be utilized in wildlife monitoring programs to track species distribution and migration patterns. Furthermore, the system can support educational initiatives, allowing individuals to learn about bird species and their significance in the ecosystem. The scientific significance of this project lies in its potential to contribute to (...) biodiversity conservation efforts. By enabling efficient monitoring of bird populations, it provides valuable data that can inform policymaking and conservation planning. Moreover, the project highlights the intersection of technology and ecology, demonstrating how AI can address real-world environmental challenges. (shrink)

In general, CEO turnover has been researched widely following numerous studies in developed countries. Nevertheless, the determinants of CEO turnover are still unclear in transition countries of which the legal and regulatory framework are weak and financial systems and corporate govemance are underdeveloped. Therefore, examining determinants of CEO turnover in Vietnam, a transition country, helps to provide more evidence on the efficiency and effectiveness of corporate governance in transition countries. Furthermore, the examination helps to define weaknesses, and it, therefore, (...) could provide guidance to improve corporate governance in Vietnamese enterprises. (shrink)