diff --git a/fedn/fedn/network/clients/client.py b/fedn/fedn/network/clients/client.py
index 9afef9956..c8c4ac020 100644
--- a/fedn/fedn/network/clients/client.py
+++ b/fedn/fedn/network/clients/client.py
@@ -766,11 +766,11 @@ def run(self):
             old_state = self.state
             while True:
                 time.sleep(1)
-                cnt += 1
+                if cnt == 0:
+                    logger.info("Client is active, waiting for model update requests.")
+                    cnt = 1
                 if self.state != old_state:
                     logger.info("Client in {} state.".format(ClientStateToString(self.state)))
-                if cnt > 5:
-                    cnt = 0
                 if not self._attached:
                     logger.info("Detached from combiner.")
                     # TODO: Implement a check/condition to ulitmately close down if too many reattachment attepts have failed. s
diff --git a/fedn/fedn/utils/dispatcher.py b/fedn/fedn/utils/dispatcher.py
index 8b80a5e16..c7ace0ab5 100644
--- a/fedn/fedn/utils/dispatcher.py
+++ b/fedn/fedn/utils/dispatcher.py
@@ -1,3 +1,5 @@
+import os
+
 from fedn.common.log_config import logger
 from fedn.utils.process import run_process
 
@@ -32,7 +34,10 @@ def run_cmd(self, cmd_type):
             args = cmdsandargs[1:]
 
             # shell (this could be a venv, TODO: parametrize)
-            shell = ['/bin/sh', '-c']
+            if os.name == "nt":
+                shell = []
+            else:
+                shell = ['/bin/sh', '-c']
 
             # add the corresponding process defined in project.yaml and append arguments from invoked command
             args = shell + [' '.join(cmd + args)]
diff --git a/fedn/fedn/utils/plugins/kerashelper.py b/fedn/fedn/utils/plugins/kerashelper.py
index 195858c76..7a931ae34 100644
--- a/fedn/fedn/utils/plugins/kerashelper.py
+++ b/fedn/fedn/utils/plugins/kerashelper.py
@@ -30,7 +30,7 @@ def increment_average(self, model, model_next, num_examples, total_examples):
         w = num_examples / total_examples
         weights = []
         for i in range(len(model)):
-            weights.append(w * model[i] + (1 - w) * model_next[i])
+            weights.append(w * model_next[i] + (1 - w) * model[i])
 
         return weights