International Journal of Communication Networks and Information Security (IJCNIS)
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A Comparative Study of the Legal Systems of Iran and China Regarding the Enforcement of Arbitration Awards in Light of the 1958 New York Convention
No full textThe China International Economic and Trade Arbitration Commission (CIETAC) is one of the prominent arbitration institutions in China, providing a fair environment for the facilitation and assurance of the enforcement of international commercial arbitration awards, in accordance with international standards, by offering clear legal guidelines for the parties involved. This institution plays a significant role in the development of international trade relations. CIETAC has established regulations based on modern arbitration principles and rules. The enforcement of commercial arbitration awards in Iranian law has also gained attention, emphasizing efforts to align with international standards while maintaining the autonomy of the parties involved.
At the international level, the recognition and enforcement of CIETAC’s and Iran’s arbitration awards are carried out in accordance with the 1958 New York Convention rules. Both legal systems, despite deviations from some international legal principles, adhere to these principles overall, though differences exist in the details.
This article offers a comparative analysis of the legal systems of Iran and China regarding the recognition and enforcement of international commercial arbitration awards from the perspective of CIETAC's regulations and Iranian arbitration laws, in light of the 1958 New York Convention. The principles, obstacles, methods of recognition, and enforcement of arbitration awards, along with the specific features and gaps in both legal systems, are examined using a descriptive and analytical method. Ultimately, the study identifies the characteristics and gaps in the enforcement of international arbitration awards in both systems, given their crucial role in the development and promotion of international trade
Developing a Strategic Sense-Making Model of Social Responsibility at Mashhad’s Municipality
No full textSense-making is a pivotal human process within organizations that contributes significantly to gaining key organizational outcomes such as strategic changes, organizational learning, and innovation. That said, this subject is a major and highly repeated theme in management research, as using sense-making in social responsibility is a new development. The main topic of this study was to develop a strategic sense-making model of social responsibility in the Municipality of Mashhad City, Iran, using the mixed research approach (a combination of quantitative and qualitative research). After reviewing the literature review and using the content and thematic analysis approaches, the researcher investigated the dimensions, components, and indicators of the strategic sense-making of social responsibility. The researcher also used the composite ISM-DEMATEL technique to rank and determine the type of variables and to investigate the relationship between the model variables, determine the intensity of the relations, and identify the extent to which the criteria affected and were affected by each other. The final model consisted of 251 basic themes, 16 organizing themes, and 4 inclusive themes. These indicators included the spiritual strategy of social responsibility (consistency with spiritual values, moral decision-making, spiritual leadership, society’s spiritual engagement), the interpretation of the sense of social responsibility (definition and comprehension, social responsibility process, social communication and awareness, cultural sensitivity), the spiritual optimization of social responsibility (holistic approach to social responsibility, resource allocation, development of innovation and creativity, continuous improvement of social responsibility), and the understanding of the sense of social responsibility (citizenship welfare, social justice, consistency with policies, global spiritual citizenship). In the next stage, to investigate the validity of the developed model, the structural equation modeling and partial least squares methods, as well as factor analyses using SPSS and Smart PLS software were used. Finally, the existing and desirable situations as well as the difference between these two situations to make sense of social responsibility in Mashhad’s Municipality were investigated by the components of the extracted model. 
Affirmative Strategic Association of Hedonic, Functional and Symbolic Perspectives on Brand Loyalty: A Structural Equation Model (SEM) Approach
No full textThe complicated and poorly understood relationships that exist between customers and brands in retailing persist despite the abundance of works on the subject. This study examines the direct relationships between three distinct relationship variables-brand trust, brand affect, and brand commitment—and the hedonic, symbolic, and functional aspects of brand images. Additionally, it looks into how they indirectly affect two kinds of loyalty-behavioural and attitude-in relation to face care products. 551 users of face care products in the North Karnataka region provided us with the data. The data was validated using the Smart-PLS software 4.0.9.9 and PLS-SEM. For the FMCG sector, the findings have significant managerial repercussions
IMPACT OF KNOWLWDGE MANAGEMENT ON OPERATIONAL EFFICIENCY OF CONSTRUCTION COMPANIES IN INDIA
No full textThe construction business is one of the world's largest business. In India, the total revenue generation in the construction business accounts for 7.74% of GDP and valued at $120 billion. Though small to medium-sized firms (SMEs) dominate the majority of the industry, they operate in small cities as well as larger urban areas. With new technologies emerging everywhere as a result of globalization and ease of connection via media, such as the internet, many businesses have attempted to implement Information and Communication Technology (ICT). The use of Knowledge Management System (KMS) is uncommon but well-known in Indian sectors; the construction sector lags behind. Many large enterprises utilize KMS or comparable systems; however, there is no evidence of KMS adoption by SMEs in the sector. We used statistical analysis tools to analyze the impact of Knowledge Management on operational efficiency in the SMEs from Indian construction sector. We anticipated main challenges in the sector based on the study and findings, including information and communication technology, human resources, organizational level and market level. The study revealed that the companies were having difficulty finding important knowledge to preserve or determining what they would need in the future. However, the companies who have implemented Knowledge Management System in their organization have got benefited from it by having more operational efficiency and getting more business
Implementation Of Multilevel Inverter For Electric Vehicle Using Fuzzy Mppt
No full textThe main goal of this research is to identify and analyze the factors affecting the development of small and medium businesses in Iraq. This research is placed in the mixed group (qualitative-quantitative) in terms of practical purpose and in terms of paradigm. In order to analyze the data in the qualitative part, the inductive content analysis method was used, and in the quantitative part, pairwise (binary) comparisons with the AHP technique were used to rank the categories. The study population of this research includes faculty members, entrepreneurship experts and small and medium business owners in Iraq, who were selected through theoretical and targeted sampling. According to the knowledge of the researcher and considering the objectives of the research, interviews were conducted with 32 academic staff members, experts and experts of entrepreneurship and business development in Iraq. Collecting research data in the qualitative part with two documentary-library methods, field observation and interview, and in the quantitative part through the pairwise comparison questionnaire. The results showed that after analyzing and coding the information obtained from the interview, 14 main categories were extracted, which were classified from the most important to the least important categories after ranking. These categories in order of importance are as follows: human capital management, market and marketing, technology and innovation, policies and laws, support, organizational culture, networking and social capital, risk management, research and development, access to resources, access to infrastructure, environmental sustainability, security and establishment and positive economic status
Transaction Method of Warehouse Sharing Platform Based on Blockchain Technology
Get PDFWith the continuous development of big data and blockchain technology, there are more applications of warehousing sharing platform, and warehousing transaction method has become the research focus. The original barter method can not solve the problem of accurate warehousing transactions, and the calculation accuracy of warehousing transactions is poor. Therefore, this paper proposes a warehouse transaction model based on blockchain technology, and comprehensively analyzes the form and accuracy of warehouse transactions. Firstly, the warehouse trading platform is used to count the transaction data and transaction methods, and the transaction forms and results are judged according to the warehouse characteristics, and irrelevant transaction information is abandoned. Then, according to the change rate of transaction data and transaction mode, the results are calculated, and compared with the actual transaction situation, and the parameters and indicators of transaction calculation are adjusted. MATLAB simulation test analysis shows that blockchain calculation method can improve the accuracy of warehousing transactions, and the accuracy rate reaches 95.3%. According to different transaction contents, the platform and form are judged, and the transaction time is calculated. It is found that the blockchain calculation method can meet the needs of warehousing transactions
Adapting Users’ Intentions in Pervasive Environments
Get PDFPervasive computing, also called ubiquitous computing, is a revolutionary paradigm that aims to create intelligent environments composed of discrete and interconnected devices. These devices can collect, process, and disseminate various information in an invisible way, in order to provide the user with services tailored to their context and activities. Communicating with these services must be intuitive, not requiring any technical details and far from traditional user interfaces. To fulfill these requirements, we present, in this article, an approach to reformulating user intentions expressed in natural language in order to connect them with the execution context and facilitate the identification of services that best meet user needs. The proposed approach is based on concepts related to lexical semantics, ontologies, and contextual information
Power-aware Intelligent Water Drops Routing Algorithm for Best Path Selection in MANETs
Get PDFThe absence of a central framework, the constantly fluctuating layout, the restricted resources, and the dispersed structure of Mobile Ad hoc Networks (MANETs), among other characteristics, make routing a critical problem. A proficient, energy-aware routing path selection algorithm can improve network performance. In this paper, a routing mechanism for path selection called the Power-aware Intelligent Water Drops Routing Algorithm (PIWDRA) is proposed, which is based on a physics-water metaheuristic called Intelligent Water Drops (IWD). In the algorithm, the global best path is selected based on a cost function that takes into consideration minimum energy, hop count, and time delay. Minimum energy has the highest weight factor. The link cost, Heuristic Undesirability (HUD), local update of the soil of a link and the soil of a drop, as well as the update of the soil of the paths that generated the local best path, incorporate one or more factors, which include time delay, energy, and the number of hops. Results obtained after simulating in Network Simulator 3 (NS-3) under variations in pause times and number of active sources show that the PIWDRA outperforms the Intelligent Water Drops Routing Algorithm (IWDRA), the Intelligent Water Drops-Based Optimization Algorithm for Mobile Ad-hoc Networks (IWDHocNet), the Ad-hoc On-Demand Distance Vector (AODV) routing protocol, and the Destination Sequence Distance Vector (DSDV) routing protocol. The performance metrics involved packet delivery ratio, average end-to-end delay, energy consumption, and network lifetime. In future work, the algorithm can be enhanced with congestion techniques such as cross-layer design, queue management, and rate control. Also, a hybrid metaheuristic routing algorithm can be the focus of future work
Energy Efficient Clustered Load Balanced LEACH Protocol Based on Particle Swarm Optimization in Underwater Wireless Sensor Networks
Get PDFUnderwater wireless sensor networks (UWSN) are generally positioned over a sizeable aquatic area and sensor nodes are mobile due to their distinct environment. The networks' sensor nodes have the ability to self-organize and communicate. The sensor networks are used in many fields, such as habitat monitoring, small energy cost, object/entity tracking, forecasting and remote control of hazardous regions, surveillance, routing etc. Due to their mobility, sensor nodes use more energy, have a lower node distribution density, and require longer localization times. Clustering is an efficient topology control strategy for achieving the goal of conserving energy. This manuscript presents a novel technique for prolonging the lifetime of a network using the LEACH protocol. The proposed load-balanced LEACH protocol uses the concept of PSO (Particle Swarm Optimization) in which a cluster head is chosen based on UWSN's current energy level, load factor, degree of nodes, and distance from the head node are used for clustering to reduce energy consumption. The proposed design has been simulated in NS2.35 and compared with three clustering routing protocols, LEACH, E-LEACH, and C-LEACH on the various performance factors like remaining energy, number of packets transmitted and lost during transmission, bit-rate analysis, number of alive and dead nodes. The proposed design shows an improvement in network lifetime and in energy conservation by selecting optimal cluster heads
Research on the Development and Application of AI-assisted Teaching Robot System Based on Deep Neural Network
No full textThis paper describes an AI-assisted teaching robot system based on a deep neural network, which aims to record the teaching situation in the classroom and continuously improve the teaching method and the quality of education through data analysis. We used the AdaBoost algorithm to implement face detection while using SVM for face classification and recognition. The AdaBoost and SVM algorithms were studied in depth and their effectiveness was verified through experiments. The image acquisition module uses the V4L2 framework to transmit the acquired image data to the client via a wired network, and the network connection adopts the socket network communication mechanism under the Linux system. We also built an Open CV development environment for training the student identification model, realizing student identification, recording the identification, and saving the image data. Based on classroom student behavior detection, this paper achieves more than 90% accuracy by analyzing students' positional features and feature similarity between consecutive video frames. To have a comprehensive understanding of student listening, we quantified students' classroom behaviors using statistical analysis methods, including overall behavioral percentage, behavioral percentage changes, and quantifying students' behaviors into the degree of listening attentiveness by marking scores, to help teachers improve the quality of teaching. This system combines various technologies such as deep learning, image processing, and statistical analysis to bring promising innovations to the field of education