Navigating Market Choices: Understanding Carrot Market Outlet Selection among Smallholder Farmers in Kenya

This research delves into the hurdles and strategies aimed at augmenting the market involvement of smallholder carrot farmers in Nakuru County, Kenya. Employing a Multinomial Logit (MNL) model, it scrutinizes the factors influencing the selection of marketing outlets among carrot farmers. The findings unveil that a significant majority (81%) of surveyed farmers actively participate in diverse market outlets, encompassing the farm gate, cleaning point, local market, external market, and export market. Notably, pivotal buyers include aggregators, brokers, wholesalers, retailers, and consumers, with transactions predominantly occurring at the farm level. Additionally, the analysis discerns substantial influences of socio-economic characteristics, experiential factors, and geographical proximity on farmers’ choices of market outlets. Specifically, gender, age, land size, farming experience, and distance to markets emerge as critical determinants. Moreover, the study delves into the examination of market margins along the carrot value chain, shedding light on the potential profitability of carrot farming in the region. Remarkably, higher average gross margins are identified in export and external markets, signaling lucrative prospects for farmers targeting these segments. However, disparities in profit distribution between farmers and traders underscore the necessity for interventions to ensure equitable value distribution throughout the value chain. These findings underscore the imperative for tailored interventions to tackle challenges and foster inclusive agricultural development. Strategies such as farmer organizations, contracting, and vertical integration are advocated to enhance market access and profitability for smallholder carrot farmers. Thus, this study enriches our comprehension of the dynamics within carrot value chains and provides valuable insights for policymakers and development practitioners aiming to uplift rural livelihoods and bolster food security.

OTFS on Overspread Doubly Selective Channel

The orthogonal time frequency space(OTFS)modulation proposed in recent years is considered to have superior performance than orthogonal frequency division multiplexing(OFDM)for the doubly selective(DS)channels.The works in the existing literature on OTFS mainly focus on the cases where the channels are underspread(i.e.,the product of the delay spread and the Doppler spread is less than 1).In the scenario of overspread DS channel,which has large delay spread and severe Doppler spread,such as underwater acoustic(UWA)channel,the channel model in delay-Doppler(DD)Domain derived by existing work is no longer applicable.In this paper,we derive a more generalized expression of the channel model in delay-Doppler domain,which allows the product of the delay spread and Doppler spread to be larger than1.The result shows that the existing channel model is just a special case of the one we proposed.Using the proposed channel matrix in DD domain,we build the OTFS detectors with the minimum mean square error(MMSE)and message passing(MP)algorithms on overspread doubly selective channel.Finally,simulation results are presented to verify the theoretical derivation and the effectiveness of the detectors.

Cooperative Channel and Optimized Route Selection in Adhoc Network

Over the last decade,mobile Adhoc networks have expanded dramati-cally in popularity,and their impact on the communication sector on a variety of levels is enormous.Its uses have expanded in lockstep with its growth.Due to its instability in usage and the fact that numerous nodes communicate data concur-rently,adequate channel and forwarder selection is essential.In this proposed design for a Cognitive Radio Cognitive Network(CRCN),we gain the confidence of each forwarding node by contacting one-hop and second level nodes,obtaining reports from them,and selecting the forwarder appropriately with the use of an optimization technique.At that point,we concentrate our efforts on their channel,selection,and lastly,the transmission of data packets via the designated forwarder.The simulation work is validated in this section using the MATLAB program.Additionally,steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate,allowing for more packet bits to be transmitted by conveniently picking the channel between them.We cal-culate the confidence of the node at the start of the network by combining the reliability report for thefirst hop and the reliability report for the secondary hop.We then refer to the same node as the confident node in order to operate as a forwarder.As a result,we witness an increase in the leftover energy in the output.The percentage of data packets delivered has also increased.

A test on adverse selection of farmers in crop insurance:Results from Inner Mongolia,China

Adverse selection is an operating risk of crop insurance. Based on survey data on crop insurance collected by questionnaires in Inner Mongolia, China, the paper uses non-parametric analysis and econometric models to estimate the relationship between conditions for crop production and farmers＇ insurance decision in order to test the existence of farmers＇ adverse selection. The results show farmers＇ adverse selection does exist, but settling a claim by negotiation and premium subsidy from governments at all levels can defuse farmers＇ adverse selection under the current system of crop insurance. Risk regionalization, heterogeneous insurance contract and product innovation may decrease adverse selection to some extent.

Farmers'participatory selection of new rice varieties to boost production under temperate agro-ecosystems

In mountain agriculture, early maturity, high grain yield and high biomass are generally considered as farmer preferred traits in rice crop in addition to a multiple set of traits collectively responsible for variety adoption or rejection. The varieties tested only on station evaluation trials without taking the data from the farmers＇ fields by not including farmers as partners for variety evaluation are the reasons of low adoption of varieties. In this regard, a participatory methodology was followed by conducting a number of participatory trials in the farmers＇ fields during 2012-2014 in six districts of Kashmir Valley, India. The mother trials in the farmers＇ fields showed that the test variety SKUA-408 consistently and significantly out yielded Jhelum and farmers＇ variety followed by Shalimar rice 3 （SR3）. The other released varieties like SR1 and SR2 could not perform nicely in the farmers＇ fields because of late maturity. After making the t-test comparison of baby trials （paired plots）, the mean yield superiority of test varieties SKUA-408, SR3, and SKUA-403 over farmers＇ variety during 2013 was around 23, 25, and 22％, respectively, whereas in 2014 the respective yield advantage was recorded as 16.3, 17.7, and 16.2％. In all districts, SKUA-408 and SR3 were significantly preferred by farmers （P〈0.05 or 0.01） in terms of pre-harvest traits namely, tillering ability and general phenotypic acceptability, early maturity and biomass and for post-harvest traits such as general cooking quality besides, the intention to grow the variety for next year. Adoption and dissemination of SKUA-408 began in 2014 from the farm-saved seed in the form of farmer to farmer seed exchange. Farmers are the end users of a variety so the decision by the farmers while judging the variety should be taken into consideration to make the varietal choice more effective for its widespread adoption.

Research on Contractual Model Selection of Farmers' Cooperatives——A Case Study of Production and Marketing Cooperative of Sweet Pomegranate in Mengzi,Yunnan

In the perspective of new institutional economics,we regard farmers' cooperatives as a "contractual set" integrating a series of long-term contractual relations,and transform the selection problem of organization forms into selection problem of contractual model within organization.By the theoretical framework of Transaction Cost Economics,we analyze the formation mechanism and determinant factors of contractual model of different farmers' cooperatives and conduct case study on Production and Marketing Cooperative of Sweet Pomegranate in Mengzi,Yunnan.The results show that selecting contractual forms of cooperatives is the result of weighing many factors;new organization model or contractual arrangement is complementary to the former system arrangement;the selection of cooperatives model is an important factor impacting cooperation efficiency and stability of organization.One organization model with efficiency not only hinges on the transaction characteristic of organization,but also considers the compatibility with exterior transaction environment.In the process of selecting contractual model,we should conform to objective evolving law,but not be in thrall to a certain given form.

Logical Framework,Path Selection and Mechanism Design for Cultivation of New Type Professional Farmers

New type professional farmers are farmers who possess certain resources and capitals,have certain extent of spirit of entrepreneurship,and are fully capable of obtaining and allocating resources related to agricultural production and management,and engaged in agricultural production and management for obtaining average profit.Cultivation of new type professional farmers should be promoted in the process and at the background of"coordinated development of industrialization,informationization,urbanization and agricultural modernization".It should establish a proper cultivation subject system consisting of government,enterprises,rural communities and nonprofit organizations.Relying on multiple motive forces,efforts should be concentrated on cultivating those farmers with enterprising,highly innovative and learning ability,to guide traditional farmers to change into learning,enterprising and innovative ones.In addition,cultivation of new type professional farmers must rely on farmer education and training,modern agricultural development,increase in agricultural comparative advantage,innovation of rural management system and mechanism,multiple types of agricultural operation on a fairly large scale,as well as construction and regulation of new rural communities.Finally,it is recommended to provide system guarantee from long-term input mechanism of new type professional farmer education and training,incentive and restrictive mechanism of new type professional farmer cultivation,and construction of favorable environment for agricultural entrepreneurship.

Employing temporal channel correlation in user selection for MIMO broadcast systems

Taking the time varying nature of wireless channels into account, two user selection schemes with lower complexity are developed for multiple-input multiple-output broadcast （MIMO BC）systems. According to the relationship between coherence time and Doppler frequency, an information frame is divided into several segments. At the beginning of each segment, the user selection is carded out with the greedy selection algorithm. In the simplified user selection algorithms employing the temporal correlation （SUSTC）, the selection results are applied for all the remaining slots in each segment. But in the improved simplified user selection algorithms employing the temporal correlation（ISUSTC）, at the remaining slots, users are kept with favorable channel conditions selected at the previous slot, and other users are updated from the candidate pool to communicate simultaneously. Simulations show that compared with the greedy user selection method, the proposed algorithms can reduce the selection complexity with a little sum capacity loss.

A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer （IASI） channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis （1D-Var） for the Unified Model （UM） data assimilation system at the Met Office, using the channel score index （CSI） as a figure of merit. Then, 200 channels were selected in order by counting each individual channel＇s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach, Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

Multi-Agent Few-Shot Meta Reinforcement Learning for Trajectory Design and Channel Selection in UAV-Assisted Networks

Unmanned aerial vehicle(UAV)-assisted communications have been considered as a solution of aerial networking in future wireless networks due to its low-cost, high-mobility, and swift features. This paper considers a UAV-assisted downlink transmission,where UAVs are deployed as aerial base stations to serve ground users. To maximize the average transmission rate among the ground users, this paper formulates a joint optimization problem of UAV trajectory design and channel selection, which is NP-hard and non-convex. To solve the problem, we propose a multi-agent deep Q-network(MADQN) scheme.Specifically, the agents that the UAVs act as perform actions from their observations distributively and share the same reward. To tackle the tasks where the experience is insufficient, we propose a multi-agent meta reinforcement learning algorithm to fast adapt to the new tasks. By pretraining the tasks with similar distribution, the learning model can acquire general knowledge. Simulation results have indicated the MADQN scheme can achieve higher throughput than fixed allocation. Furthermore, our proposed multiagent meta reinforcement learning algorithm learns the new tasks much faster compared with the MADQN scheme.

Mode Selection Strategy of Dual Distribution Channel Based on Revenue Analysis

Within the scope of dual distribution channel(DDC)modes—ME&T-C and M-T&E-C,a game model designed for channel members was proposed.Based on this game model,the game equilibrium under both centralized and decentralized decisionmaking situations was analyzed,the channel members' and overall revenues of two modes under the same decision-making situation are compared,and the influence of demand shift coefficient to the overall and members' revenue was also studied through example analysis.Based on the comparison and analysis of the revenue yielded from the two DDC modes,it's discovered that within a certain hypothetical range,the M-T&E-C mode seems to be a better option for the manufacturer than the ME&T-C mode.Therefore,this discovery can be served as a theoretical reference for manufacturers when choosing the optimal DDC mode in real life.

Channel Allocation and Relay Selection Scheme in Relay-Based Networks

It has been demonstrated that either Channel Allocation （CA） or Relay Selection （RS） can improve the performance in relaying networks separately. However, there is little work concerning their combination in multi-cell uplink scenarios. In this paper, we investigate the issue which considers the CA and RS to optimize the system transmission rate in an uplink scenario, while maintaining the resource distribution fairness among users. This is first formulated as an optimization problem for a linear cellular system, where the same frequency channels can be reused in different cells. Based on the link and co-channel interference conditions, two low-complexity CA and RS schemes are then proposed with different decomposition se quences. Finally, numerical results are con ducted to verify the effectiveness of the pro posed CA and RS methods. Simulations re suits show that the proposed methods can yield significant improvements in system per formance in terms of average sum rate.

A Bintree Energy Approach for Colour Image Segmentation Using Adaptive Channel Selection

A new hierarchical approach called bintree energy segmentation was presented for color image segmentation. The image features are extracted by adaptive clustering on multi-channel data at each level and used as the criteria to dynamically select the best chromatic channel, where the segmentation is carried out. In this approach, an extended direct energy computation method based on the Chan-Vese model was proposed to segment the selected channel, and the segmentation outputs are then fused with other channels into new images, from which a new channel with better features is selected for the second round segmentation. This procedure is repeated until the preset condition is met. Finally, a binary segmentation tree is formed, in which each leaf represents a class of objects with a distinctive color. To facilitate the data organization, image background is employed in segmentation and channels fusion. The bintree energy segmentation exploits color information involved in all channels data and tries to optimize the global segmentation result by choosing the 'best' channel for segmentation at each level. The experiments show that the method is effective in speed, accuracy and flexibility.

Assessment of Farmer’s Practices on the Rubber Nursery Management Using Growing Medium and Varietal Selection in Mon State

Rubber is an economically important perennial crop in Myanmar for latex production. As the rubber plantation area increases yearly, the requirement of vigorous rubber seedlings for its establishment plays a central role. The success of rubber plantations depends on some farming practices such as using different compost or other materials in the potting soil-medium, varietal selection for stock and scion in the budding process, and fertilizer application methods. The objective of this study was to assess the farmer’s practices in the establishment of rubber nurseries in mostly rubber planted areas in Myanmar. The survey interviewed 60 respondents from three townships in Mon State, namely Mudon, Kyaikmaraw, and Thanbyuzayat. The response data were analyzed through the descriptive method. This survey exposed the potentially active operators (middle age of 30 - 60 years) in rubber nursery production. Local experienced farmers usually raised the budded seedlings with 15 cm × 23 cm polyethylene bag in all study regions. Most farmers selected multi-clonal seed for stock and BPM 24 for scion according to the local market demand and high latex yield. All survey areas used both organic and inorganic fertilizers for nutrient management. Compost is a chief component of growing medium in their nursery production. However, making compost and high demand of the compost were local constraints. Therefore, this survey suggested improving the proper composting method for rubber nursery establishment.

Performance analysis of selection cooperative networks over asymmetric fading channels

The performances of selection cooperation are investigated over asymmetric fading channels where the source-relay and the relay-destination channels experience Nakagami-m and Rayleigh fading,respectively.Decode-and-forward(DF)protocol is adopted and the Nth best relay is selected from M available relays.Probability density function(PDF)for the instantaneous signal-to-noise ratio(SNR)at the destination is derived first.Then,it is used to derive the exact expressions for outage probability and average symbol error rate(SER).The results hold for arbitrary M or N.Finally,simulations are carried out to verify the correctness of our theoretical analysis and results show that M and N almost have the same effect on the performance of outage probability and SER.

Antenna selection for V-BLAST systems in correlated channel

Spatial multiplexing systems can provide significant capacity improvement but are sensitive to channel correlation. Antenna selection is a low-cost low-complexity ahemative to resolve these problems. This paper proposes a new transmit antenna selection algorithm for the spatial multiplexing systems with the Vertical-Bell Labs Layered Space-Time （V-BLAST） nonlinear receiver in correlated channel. The proposed scheme separates the optimization into two parts： it first chooses the optimal number of substreams in terms of the singular values of the channel matrix, then adapts the mapping of substreams to antennas according to the post-detection signal-to-noise ratio （SNR）. Simulation results illustrate that the proposed two-step selection criterion can provide greater selection gain than the existing singnlar value based selection criterion as SNR and scattering angle increases. The proposed criterion outperforms the existing one by 0.3 dB at a vector symbol error rate of 10^- 3 and scattering angle of 20 degree.

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

A Concise Joint Transmit/Receive Antenna Selection Algorithm

For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the channel matrix in such a way that the computational complexity of the greedy Joint Transmit/Receive Antenna Selection (JTRAS) algorithm is reduced by a factor of 4n L , where n L is the number of selected antennas. A decoupled version of the proposed algorithm is also proposed to further improve the efficiency of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the performance of the proposed approaches are evaluated mathematically and verified by computer simulations. The results have shown that the proposed joint antenna selection algorithm maintains the capacity perormance of the JTRAS algorithm while its computational complexity is only 1/4n L of that of the JTRAS algorithm. The decoupled version of the proposed algorithm further reduces the computational complexity of the joint antenna selection and has better performance than other decoupling-based algorithms when the selected antenna subset is small as compared to the total number of antennas.

A new layered space-time detection algorithm for frequency selective fading multiple-input multiple-output channels based on particle filter

In this paper, a new observation equation of non-Gaussian frequency selective fading Bell Labs layered space time （BLAST） architecture system is proposed, which is used for frequency selective fading channels and non-Gaussian noise in an application environment of BLAST system. With othogonal matrix triangularization （QR decomposition） of the channel matrix, the static observation equation of frequency selective fading BLAST system is transformed into a dynamic state space model, and then the particle filter is used for space-time layered detection. Making the full use of the finite alphabet of the digital modulation communication signal, the optimal proposal distribution can be chosen to produce particle and update the weight. Incorporated with current method of reducing error propagation, a new space-time layered detection algorithm is proposed. Simulation result shows the validity of the proposed algorithm.

Joint Antenna Selection and Robust Beamforming Design in Multi-cell Distributed Antenna System

Most of studies on Distributed Antenna System(DAS) focus on maximizing the sum capacity and perfect channel state information at transmitter(CSIT).However,CSI is inevitable imperfect in practical wireless networks.Based on the sources of error,there are two models.One assumes error lies in a bounded region,the other assumes random error.Accordingly,we propose two joint antenna selection(AS) and robustbeamforming schemes aiming to minimize the total transmit power at antenna nodes subject to quality of service(QoS) guarantee for all the mobile users(MUs) in multicell DAS.This problem is mathematically intractable.For the bounded error model,we cast it into a semidefinite program(SDP) using semidefinite relaxation(SDR) and S-procedure.For the second,we first design outage constrained robust beamforming and then formulate it as an SDP based on the Bernstein-type inequality,which we generalize it to the multi-cell DAS.Simulation results verify the effectiveness of the proposed methods.