Journal articles on the topic 'Multi-sender index coding problem'

This paper studies index coding with two senders. In this setup, source messages are distributed among the senders possibly with common messages. In addition, there are multiple receivers, with each receiver having some messages a priori, known as side-information, and requesting one unique message such that each message is requested by only one receiver. Index coding in this setup is called two-sender unicast index coding (TSUIC). The main goal is to find the shortest aggregate normalized codelength, which is expressed as the optimal broadcast rate. In this work, firstly, for a given TSUIC problem, we form three independent sub-problems each consisting of the only subset of the messages, based on whether the messages are available only in one of the senders or in both senders. Then, we express the optimal broadcast rate of the TSUIC problem as a function of the optimal broadcast rates of those independent sub-problems. In this way, we discover the structural characteristics of TSUIC. For the proofs of our results, we utilize confusion graphs and coding techniques used in single-sender index coding. To adapt the confusion graph technique in TSUIC, we introduce a new graph-coloring approach that is different from the normal graph coloring, which we call two-sender graph coloring, and propose a way of grouping the vertices to analyze the number of colors used. We further determine a class of TSUIC instances where a certain type of side-information can be removed without affecting their optimal broadcast rates. Finally, we generalize the results of a class of TSUIC problems to multiple senders.

The connections between index coding and matroid theory have been well studied in the recent past. Index coding solutions were first connected to multi linear representation of matroids. For vector linear index codes, discrete polymatroids, which can be viewed as a generalization of the matroids, were used. The index coding problem has been generalized recently to accommodate receivers that demand functions of messages and possess functions of messages. In this work we explore the connections between generalized index coding and discrete polymatroids. The conditions that need to be satisfied by a representable discrete polymatroid for a generalized index coding problem to have a vector linear solution is established. From a discrete polymatroid, an index coding problem with coded side information is constructed and it is shown that if the index coding problem has a certain optimal length solution then the discrete polymatroid is representable. If the generalized index coding problem is constructed from a matroid, it is shown that the index coding problem has a binary scalar linear solution of optimal length if and only if the matroid is binary representable.

The receiver of OFDM with Index Modulation (OFDM-IM) usually adopts a Log Likelihood Ratio (LLR) detection algorithm based on the activation state of subcarriers. However, the LLR detection algorithm will cause detection errors in subcarrier activation pattern (SAP) or get illegal SAP. Consequently, further errors occur in demodulation, increasing the bit error rate (BER). To solve this problem, we propose the protection scheme of subcarrier index aided by LDPC coding, which reduces the SAP detection errors by encoding the index information bits. On the receiver, the LDPC Coding Aided (LA) detection algorithm is designed, and the formula of LLR of index information bits is derived in detail. Monte Carlo simulation is carried out over multi-path fading channel by MATLAB software. The results show that under the condition that the spectrum efficiency is not lower than the classical OFDM-IM scheme, the proposed protection scheme can obtain a gain of about 5~9 dB when the BER is 10-4, effectively improving the BER performance of OFDM-IM scheme.

The problem of data exchange between multiple nodes with storage and communication capabilities models several current multi-user communication problems like Coded Caching, Data Shuffling, Coded Computing, etc. The goal in such problems is to design communication schemes which accomplish the desired data exchange between the nodes with the optimal (minimum) amount of communication load. In this work, we present a converse to such a general data exchange problem. The expression of the converse depends only on the number of bits to be moved between different subsets of nodes, and does not assume anything further specific about the parameters in the problem. Specific problem formulations, such as those in Coded Caching, Coded Data Shuffling, and Coded Distributed Computing, can be seen as instances of this generic data exchange problem. Applying our generic converse, we can efficiently recover known important converses in these formulations. Further, for a generic coded caching problem with heterogeneous cache sizes at the clients with or without a central server, we obtain a new general converse, which subsumes some existing results. Finally we relate a “centralized” version of our bound to the known generalized independence number bound in index coding and discuss our bound’s tightness in this context.

An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations.

With the development of big data and deep learning, bus passenger flow prediction considering real-time data becomes possible. Real-time traffic flow prediction helps to grasp real-time passenger flow dynamics, provide early warning for a sudden passenger flow and data support for real-time bus plan changes, and improve the stability of urban transportation systems. To solve the problem of passenger flow prediction considering real-time data, this paper proposes a novel passenger flow prediction network model based on long short-term memory (LSTM) networks. The model includes four parts: feature extraction based on Xgboost model, information coding based on historical data, information coding based on real-time data, and decoding based on a multi-layer neural network. In the feature extraction part, the data dimension is increased by fusing bus data and points of interest to improve the number of parameters and model accuracy. In the historical information coding part, we use the date as the index in the LSTM structure to encode historical data and provide relevant information for prediction; in the real-time data coding part, the daily half-hour time interval is used as the index to encode real-time data and provide real-time prediction information; in the decoding part, the passenger flow data for the next two 30 min interval outputs by decoding all the information. To our best knowledge, it is the first time to real-time information has been taken into consideration in passenger flow prediction based on LSTM. The proposed model can achieve better accuracy compared to the LSTM and other baseline methods.

The cloud provides on-demand, high-quality services to its users without the burden of managing hardware and software. Though the users benefit from the remote services provided by the cloud, they do not have their personal data in their physical possession. This certainly poses new security threats for personal and confidential data, bringing the focus back on trusting the use of the cloud for sensitive data. The benefits of the cloud outweigh the concerns raised earlier, and with an increase in cloud usage, it becomes more important for security services to evolve in order to address the ever-changing threat landscape. Advanced encryption standard (AES), being one of the most widely used encryption techniques, has inherent disadvantages related to the secret key that is shared, and predictable patterns in subkey generation. In addition, since cloud storage involves data transfer over a wireless channel, it is important to address the effect of noise and multipath propagation on the transmitted data. Catering to this problem, we propose a new approach—the secure and reliable neural cryptcoding (SARNC) technique—which provides a superior algorithm, dealing with better encryption techniques combined with channel coding. A chain is as strong as the weakest link and, in the case of symmetric key encryption, the weakest link is the shared key. In order to overcome this limitation, we propose an approach wherein the key used for cryptographic purposes is different from the key shared between the sender and the receiver. The shared key is used to derive the secret private key, which is generated by the neural key exchange protocol. In addition, the proposed approach emphasizes strengthening the sub-key generation process and integrating advanced encryption standard (AES) with low-density parity check (LDPC) codes to provide end-to-end security and reliability over wireless channels. The proposed technique was tested against research done in related areas. A comparative study shows a significant improvement in PSNR, MSE, and the structural similarity index (SSIM). The key strength analysis was carried out to understand the strength and weaknesses of the keys generated.

One of the main important aspects in designing an active control system is the optimization of position and number of sensors and actuators. In this paper this problem is addressed for the implementation of a multi-channel active noise control (ANC) system with the aim of global reduction of broadband noise in a telephone kiosk. This includes optimizing the locations for loudspeakers and microphones, finding proper size of the control system, i.e. the number of loudspeakers and microphones, and optimization of the control signals. The mean of acoustic potential energy in the enclosure in a frequency range of 50 Hz to 300 Hz is selected as the performance index for optimization purpose. Several genetic algorithms are proposed and compared to find the global minimum of this performance index. In order to have a better performance in reaching the global minimum, the parameters of these genetic algorithms are tuned, and the best genetic algorithm is selected among them. The main difference between the proposed algorithms is the used coding scheme. Numerical simulations of the acoustical potential energy and also sound pressure at the height where the head of a person may be located, confirms the optimality of the locations proposed by the genetic algorithm.

<abstract><p>In synthetic biology, it is a challenge to increase the production of target proteins by maximizing their expression levels. In order to augment expression levels, we need to focus on both homologous recombination and codon adaptation, which are estimated by three objective functions, namely HD (Hamming distance), LRCS (length of repeated or common substring) and CAI (codon adaptation index). Optimizing these objective functions simultaneously becomes a multi-objective optimization problem. The aim is to find satisfying solutions that have high codon adaptation and a low incidence of homologous recombination. However, obtaining satisfactory solutions requires calculating the objective functions multiple times with many cycles and solutions. In this paper, we propose an approach to accelerate the method of designing a set of CDSs (CoDing sequences) based on NSGA-II (non-dominated sorting genetic algorithm II) on NVIDIA GPUs. The implementation accelerated by GPUs improves overall performance by 187.5$ \times $ using $ 100 $ cycles and $ 128 $ solutions. Our implementation allows us to use larger solutions and more cycles, leading to outstanding solution quality. The improved implementation provides much better solutions in a similar amount of time compared to other available methods by 1.22$ \times $ improvements in hypervolume. Furthermore, our approach on GPUs also suggests how to efficiently utilize the latest computational resources in bioinformatics. Finally, we discuss the impacts of the number of cycles and the number of solutions on designing a set of CDSs.</p></abstract>

Insects play a vital role for humans. Apart from well-known ecosystem services (e.g., pollination, biological control, decomposition), they also serve as food for humans. An increasing number of research reports (Mitsuhashi 2017, Jongema 2018) indicate that entomophagy (the practice of eating insects by humans), is a long-standing practice in many countries around the globe. In Africa notably, more than 524 insects have been reported to be consumed by different ethnic groups, serving as a cheap, ecofriendly and renewable source of nutrients on the continent. Given the global recession due to the pandemic (COVID-19) and the threat induced to food security and food production systems, edible insects are of special interest in African countries, particularly the Democratic Republic of the Congo (DRC), where they have been reported as vital to sustain food security. Indeed, to date, the broadest lists of edible insects of the DRC reported (a maximum) 98 insects identified at species level (Monzambe 2002, Mitsuhashi 2017, Jongema 2018). But these lists are hampered by spelling mistakes or by redundancy. An additional problem is raised by insects only known by their vernacular names (ethnospecies) as local languages (more than 240 living ones) do not necessarily give rigorous information due to polysemy concerns. Based on the aforementioned challenges, entomophagy practices and edible insect species reported for DRC (from the independence year, 1960, to date) have been reviewed using four authoritative taxonomic databases: Catalogue of Life (CoL), Integrated Taxonomic Information System, Global Biodiversity Information Facility taxonomic backbone, and the Global Lepidoptera Names Index. Results confirm the top position of edible caterpillars (Lepidoptera, 50.8%) followed by Orthoptera (12.5%), Coleoptera and Hymenoptera (10.0% each). A total of 120 edible species (belonging to eighty genera, twenty-nine families and nine orders of insects) have been listed and mapped on a national scale. Likewise, host plants of edible insects have been inventoried after checking (using CoL, Plant Resources of Tropical Africa, and the International Union for Conservation of Nature's Red List of Threatened Species). The host plant diversity is dominated by multi-use trees belonging to Fabaceae (34.4%) followed by Phyllanthaceae (10.6%) and Meliaceae (4.9%). However, data indicated endangered (namely Millettia laurentii, Prioria balsamifera ) or critically endangered (Autranella congolensis) host plant species that call for conservation strategies. To the best of our knowledge, aforementioned results are the very first reports of such findings in Africa. Moreover, given issues encountered during data compilation and during cross-checking of scientific names, a call was made for greater collaboration between local people and expert taxonomists (through citizen science), in order to unravel unidentified ethnospecies. Given the challenge of information technology infrastructure in Africa, such a target could be achieved thanks to mobile apps. Likewise, a further call should be made for: bеtter synchronization of taxonomic databases, the need of qualitative scientific photographs in taxonomic databases, and additional data (i.e., conservational status, proteins or DNA sequences notably) as edible insects need to be rigorously identified and durably managed. bеtter synchronization of taxonomic databases, the need of qualitative scientific photographs in taxonomic databases, and additional data (i.e., conservational status, proteins or DNA sequences notably) as edible insects need to be rigorously identified and durably managed. Indeed, these complementary data are very crucial, given the limitations and issues of conventional/traditional identification methods based on morphometric or dichotomous keys and the lack of voucher specimens in many African museums and/or collections. This could be achieved by QR (Quick Response) coding insect species and centralizing data about edible insects in a main authoritative taxonomic database whose role is undebatable, as edible insects are today earmarked as nutrient-rich source of proteins, fat, vitamins and fiber to mitigate food insecurity and poor diets, which are an aggravating factor for the impact of COVID-19.

Introduction: Birth and presence of children with vision problems in every household could be considered a challenging event which will follow with stress, frustration and hopelessness. Objective: This study aimed to determine the relation between parenting stress with student’s self-efficacy who has visual impairment. Method: This study was conducted as a causal-comparative design in the form of a multi-site in the descriptive study field. The target formed the population included all male students with visual impairment living in Tehran and Karaj. For this purpose sixty (N =60) students (age range 22-12 with average age: 18.2) were selected by available sampling method. Data collection was based on survey methods to assess parenting stress in the index of Schiffer work questionnaires (response rate = 91%) was used. The collected data were analyzed using Pearson correlation test and F-test. As well as qualitative data were analyzed obtained from the assessment coding demographic and qualitative data analysis tool Atlas.ti-5.2. Results: Data analysis showed that between parenting stress of mothers There is a significant relationship with three levels of academic self-efficacy (r=-0.35), social (r=-0.27) and emotional (r=-0.28) .Conclusion: in line of management background, the results of this study indicate that there is a linear relationship between stress of parenting and efficacy in children, these findings could be promising outlook for future interventions.